Classification of brain tumours from MR spectra: the INTERPRET collaboration and its outcomes.

The INTERPRET project was a multicentre European collaboration, carried out from 2000 to 2002, which developed a decision-support system (DSS) for helping neuroradiologists with no experience of MRS to utilize spectroscopic data for the diagnosis and grading of human brain tumours. INTERPRET gathered a large collection of MR spectra of brain tumours and pseudo-tumoural lesions from seven centres. Consensus acquisition protocols, a standard processing pipeline and strict methods for quality control of the aquired data were put in place. Particular emphasis was placed on ensuring the diagnostic certainty of each case, for which all cases were evaluated by a clinical data validation committee. One outcome of the project is a database of 304 fully validated spectra from brain tumours, pseudotumoural lesions and normal brains, along with their associated images and clinical data, which remains available to the scientific and medical community. The second is the INTERPRET DSS, which has continued to be developed and clinically evaluated since the project ended. We also review here the results of the post-INTERPRET period. We evaluate the results of the studies with the INTERPRET database by other consortia or research groups. A summary of the clinical evaluations that have been performed on the post-INTERPRET DSS versions is also presented. Several have shown that diagnostic certainty can be improved for certain tumour types when the INTERPRET DSS is used in conjunction with conventional radiological image interpretation. About 30 papers concerned with the INTERPRET single-voxel dataset have so far been published. We discuss stengths and weaknesses of the DSS and the lessons learned. Finally we speculate on how the INTERPRET concept might be carried into the future.Funding from project MARESCAN (SAF2011-23870) from Ministerio de Economia y Competitividad in Spain. This work was also partially funded by CIBER-BBN, which is an initiative of the VI National R&D&i Plan 2008-2011, CIBER Actions and financed by the Instituto de Salud Carlos III with assistance from the European Regional Development Fund. JRG acknowledges support from Cancer Research UK, the University of Cambridge and Hutchison Whampoa Ltd.This is the author accepted manuscript. The final version is available from Wiley via http://dx.doi.org/10.1002/nbm.343

Integration of Distributed Services and Hybrid Models Based on Process Choreography to Predict and Detect Type 2 Diabetes

[EN] Life expectancy is increasing and, so, the years that patients have to live with chronic diseases and co-morbidities. Type 2 diabetes is one of the most prevalent chronic diseases, specifically linked to being overweight and ages over sixty. Recent studies have demonstrated the effectiveness of new strategies to delay and even prevent the onset of type 2 diabetes by a combination of active and healthy lifestyle on cohorts of mid to high risk subjects. Prospective research has been driven on large groups of the population to build risk scores that aim to obtain a rule for the classification of patients according to the odds for developing the disease. Currently, there are more than two hundred models and risk scores for doing this, but a few have been properly evaluated in external groups and integrated into a clinical application for decision support. In this paper, we present a novel system architecture based on service choreography and hybrid modeling, which enables a distributed integration of clinical databases, statistical and mathematical engines and web interfaces to be deployed in a clinical setting. The system was assessed during an eight-week continuous period with eight endocrinologists of a hospital who evaluated up to 8080 patients with seven different type 2 diabetes risk models implemented in two mathematical engines. Throughput was assessed as a matter of technical key performance indicators, confirming the reliability and efficiency of the proposed architecture to integrate hybrid artificial intelligence tools into daily clinical routine to identify high risk subjects.The authors wish to acknowledge the consortium of the MOSAIC project (funded by the European Commission, Grant No. FP7-ICT 600914) for their commitment during concept development, which led to the development of the research reported in this manuscriptMartinez-Millana, A.; Bayo-Monton, JL.; Argente-Pla, M.; Fernández Llatas, C.; Merino-Torres, JF.; Traver Salcedo, V. (2018). Integration of Distributed Services and Hybrid Models Based on Process Choreography to Predict and Detect Type 2 Diabetes. Sensors. 18 (1)(79):1-26. https://doi.org/10.3390/s18010079S12618 (1)79Thomas, C. C., & Philipson, L. H. (2015). Update on Diabetes Classification. Medical Clinics of North America, 99(1), 1-16. doi:10.1016/j.mcna.2014.08.015Kahn, S. 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Genotype Score in Addition to Common Risk Factors for Prediction of Type 2 Diabetes. New England Journal of Medicine, 359(21), 2208-2219. doi:10.1056/nejmoa0804742Gillies, C. L., Abrams, K. R., Lambert, P. C., Cooper, N. J., Sutton, A. J., Hsu, R. T., & Khunti, K. (2007). Pharmacological and lifestyle interventions to prevent or delay type 2 diabetes in people with impaired glucose tolerance: systematic review and meta-analysis. BMJ, 334(7588), 299. doi:10.1136/bmj.39063.689375.55Noble, D., Mathur, R., Dent, T., Meads, C., & Greenhalgh, T. (2011). Risk models and scores for type 2 diabetes: systematic review. BMJ, 343(nov28 1), d7163-d7163. doi:10.1136/bmj.d7163Collins, G. S., Reitsma, J. B., Altman, D. G., & Moons, K. G. M. (2015). Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): The TRIPOD Statement. Annals of Internal Medicine, 162(1), 55. doi:10.7326/m14-0697Steyerberg, E. W., Moons, K. G. M., van der Windt, D. A., Hayden, J. A., Perel, P., … Schroter, S. (2013). Prognosis Research Strategy (PROGRESS) 3: Prognostic Model Research. PLoS Medicine, 10(2), e1001381. doi:10.1371/journal.pmed.1001381Collins, G. S., & Moons, K. G. M. (2012). Comparing risk prediction models. BMJ, 344(may24 2), e3186-e3186. doi:10.1136/bmj.e3186Riley, R. D., Ensor, J., Snell, K. I. E., Debray, T. P. A., Altman, D. G., Moons, K. G. M., & Collins, G. S. (2016). External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges. BMJ, i3140. doi:10.1136/bmj.i3140Reilly, B. M., & Evans, A. T. (2006). Translating Clinical Research into Clinical Practice: Impact of Using Prediction Rules To Make Decisions. Annals of Internal Medicine, 144(3), 201. doi:10.7326/0003-4819-144-3-200602070-00009Altman, D. G., Vergouwe, Y., Royston, P., & Moons, K. G. M. (2009). Prognosis and prognostic research: validating a prognostic model. BMJ, 338(may28 1), b605-b605. doi:10.1136/bmj.b605Moons, K. G. M., Royston, P., Vergouwe, Y., Grobbee, D. E., & Altman, D. G. (2009). Prognosis and prognostic research: what, why, and how? BMJ, 338(feb23 1), b375-b375. doi:10.1136/bmj.b375Steyerberg, E. W., Vickers, A. J., Cook, N. R., Gerds, T., Gonen, M., Obuchowski, N., … Kattan, M. W. (2010). Assessing the Performance of Prediction Models. Epidemiology, 21(1), 128-138. doi:10.1097/ede.0b013e3181c30fb2Kayacan, E., Ulutas, B., & Kaynak, O. (2010). Grey system theory-based models in time series prediction. Expert Systems with Applications, 37(2), 1784-1789. doi:10.1016/j.eswa.2009.07.064Schmidt, M. I., Duncan, B. B., Bang, H., Pankow, J. S., Ballantyne, C. M., … Golden, S. H. (2005). Identifying Individuals at High Risk for Diabetes: The Atherosclerosis Risk in Communities study. Diabetes Care, 28(8), 2013-2018. doi:10.2337/diacare.28.8.2013Talmud, P. J., Hingorani, A. D., Cooper, J. A., Marmot, M. G., Brunner, E. J., Kumari, M., … Humphries, S. E. (2010). Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study. BMJ, 340(jan14 1), b4838-b4838. doi:10.1136/bmj.b4838Sackett, D. L. (1997). Evidence-based medicine. Seminars in Perinatology, 21(1), 3-5. doi:10.1016/s0146-0005(97)80013-4Segagni, D., Ferrazzi, F., Larizza, C., Tibollo, V., Napolitano, C., Priori, S. G., & Bellazzi, R. (2011). R Engine Cell: integrating R into the i2b2 software infrastructure. Journal of the American Medical Informatics Association, 18(3), 314-317. doi:10.1136/jamia.2010.007914Semantic Webhttp://www.w3.org/2001/sw/Murphy, S. N., Weber, G., Mendis, M., Gainer, V., Chueh, H. C., Churchill, S., & Kohane, I. (2010). Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2). Journal of the American Medical Informatics Association, 17(2), 124-130. doi:10.1136/jamia.2009.000893Murphy, S., Churchill, S., Bry, L., Chueh, H., Weiss, S., Lazarus, R., … Kohane, I. (2009). Instrumenting the health care enterprise for discovery research in the genomic era. Genome Research, 19(9), 1675-1681. doi:10.1101/gr.094615.109Lindstrom, J., & Tuomilehto, J. (2003). The Diabetes Risk Score: A practical tool to predict type 2 diabetes risk. Diabetes Care, 26(3), 725-731. doi:10.2337/diacare.26.3.725Alssema, M., Vistisen, D., Heymans, M. W., Nijpels, G., Glümer, C., … Dekker, J. M. (2010). The Evaluation of Screening and Early Detection Strategies for Type 2 Diabetes and Impaired Glucose Tolerance (DETECT-2) update of the Finnish diabetes risk score for prediction of incident type 2 diabetes. Diabetologia, 54(5), 1004-1012. doi:10.1007/s00125-010-1990-7Mann, D. M., Bertoni, A. G., Shimbo, D., Carnethon, M. R., Chen, H., Jenny, N. S., & Muntner, P. (2010). Comparative Validity of 3 Diabetes Mellitus Risk Prediction Scoring Models in a Multiethnic US Cohort: The Multi-Ethnic Study of Atherosclerosis. American Journal of Epidemiology, 171(9), 980-988. doi:10.1093/aje/kwq030Stern, M. P., Williams, K., & Haffner, S. M. (2002). Identification of Persons at High Risk for Type 2 Diabetes Mellitus: Do We Need the Oral Glucose Tolerance Test? Annals of Internal Medicine, 136(8), 575. doi:10.7326/0003-4819-136-8-200204160-00006Abdul-Ghani, M. A., Abdul-Ghani, T., Stern, M. P., Karavic, J., Tuomi, T., Bo, I., … Groop, L. (2011). Two-Step Approach for the Prediction of Future Type 2 Diabetes Risk. Diabetes Care, 34(9), 2108-2112. doi:10.2337/dc10-2201Rahman, M., Simmons, R. K., Harding, A.-H., Wareham, N. J., & Griffin, S. J. (2008). A simple risk score identifies individuals at high risk of developing Type 2 diabetes: a prospective cohort study. Family Practice, 25(3), 191-196. doi:10.1093/fampra/cmn024Guasch-Ferré, M., Bulló, M., Costa, B., Martínez-Gonzalez, M. Á., Ibarrola-Jurado, N., … Estruch, R. (2012). A Risk Score to Predict Type 2 Diabetes Mellitus in an Elderly Spanish Mediterranean Population at High Cardiovascular Risk. PLoS ONE, 7(3), e33437. doi:10.1371/journal.pone.0033437Wilson, P. W. F. (2007). Prediction of Incident Diabetes Mellitus in Middle-aged Adults. Archives of Internal Medicine, 167(10), 1068. doi:10.1001/archinte.167.10.1068Franzin, A., Sambo, F., & Di Camillo, B. (2016). bnstruct: an R package for Bayesian Network structure learning in the presence of missing data. Bioinformatics, btw807. doi:10.1093/bioinformatics/btw807Rood, B., & Lewis, M. J. (2009). Grid Resource Availability Prediction-Based Scheduling and Task Replication. Journal of Grid Computing, 7(4), 479-500. doi:10.1007/s10723-009-9135-2Ramakrishnan, L., & Reed, D. A. (2009). Predictable quality of service atop degradable distributed systems. Cluster Computing, 16(2), 321-334. doi:10.1007/s10586-009-0078-yKianpisheh, S., Kargahi, M., & Charkari, N. M. (2017). Resource Availability Prediction in Distributed Systems: An Approach for Modeling Non-Stationary Transition Probabilities. IEEE Transactions on Parallel and Distributed Systems, 28(8), 2357-2372. doi:10.1109/tpds.2017.2659746Weber, G. M., Murphy, S. N., McMurry, A. J., MacFadden, D., Nigrin, D. J., Churchill, S., & Kohane, I. S. (2009). The Shared Health Research Information Network (SHRINE): A Prototype Federated Query Tool for Clinical Data Repositories. Journal of the American Medical Informatics Association, 16(5), 624-630. doi:10.1197/jamia.m3191Martinez-Millana, A., Fico, G., Fernández-Llatas, C., & Traver, V. (2015). Performance assessment of a closed-loop system for diabetes management. Medical & Biological Engineering & Computing, 53(12), 1295-1303. doi:10.1007/s11517-015-1245-3Foundation for Intelligent Physical Agentshttp://www.pa.org/González-Vélez, H., Mier, M., Julià-Sapé, M., Arvanitis, T. N., García-Gómez, J. M., Robles, M., … Lluch-Ariet, M. (2007). HealthAgents: distributed multi-agent brain tumor diagnosis and prognosis. Applied Intelligence, 30(3), 191-202. doi:10.1007/s10489-007-0085-8Bellazzi, R. (2014). Big Data and Biomedical Informatics: A Challenging Opportunity. Yearbook of Medical Informatics, 23(01), 08-13. doi:10.15265/iy-2014-0024Maximilien, E. M., & Singh, M. P. (2004). A framework and ontology for dynamic Web services selection. IEEE Internet Computing, 8(5), 84-93. doi:10.1109/mic.2004.2

Agent-based management of clinical guidelines

Les guies de pràctica clínica (GPC) contenen un conjunt d'accions i dades que ajuden a un metge a prendre decisions sobre el diagnòstic, tractament o qualsevol altre procediment a un pacient i sobre una determinada malaltia. És conegut que l'adopció d'aquestes guies en la vida diària pot millorar l'assistència mèdica als pacients, pel fet que s'estandarditzen les pràctiques. Sistemes computeritzats que utilitzen GPC poden constituir part de sistemes d'ajut a la presa de decisions més complexos amb la finalitat de proporcionar el coneixement adequat a la persona adequada, en un format correcte i en el moment precís. L'automatització de l'execució de les GPC és el primer pas per la seva implantació en els centres mèdics.Per aconseguir aquesta implantació final, hi ha diferents passos que cal solucionar com per exemple, l'adquisició i representació de les GPC, la seva verificació formal, i finalment la seva execució. Aquesta Tesi està dirigida en l'execució de GPC i proposa la implementació d'un sistema multi-agent. En aquest sistema els diferents actors dels centres mèdics coordinen les seves activitats seguint un pla global determinat per una GPC. Un dels principals problemes de qualsevol sistema que treballa en l'àmbit mèdic és el tractament del coneixement. En aquest cas s'han hagut de tractar termes mèdics i organitzatius, que s'ha resolt amb la implementació de diferents ontologies. La separació de la representació del coneixement del seu ús és intencionada i permet que el sistema d'execució de GPC sigui fàcilment adaptable a les circumstàncies concretes dels centres, on varien el personal i els recursos disponibles.En paral·lel a l'execució de GPC, el sistema proposat manega preferències del pacient per tal d'implementar serveis adaptats al pacient. En aquesta àrea concretament, a) s'han definit un conjunt de criteris, b) aquesta informació forma part del perfil de l'usuari i serveix per ordenar les propostes que el sistema li proposa, i c) un algoritme no supervisat d'aprenentatge permet adaptar les preferències del pacient segons triï.Finalment, algunes idees d'aquesta Tesi actualment s'estan aplicant en dos projectes de recerca. Per una banda, l'execució distribuïda de GPC, i per altra banda, la representació del coneixement mèdic i organitzatiu utilitzant ontologies.Clinical guidelines (CGs) contain a set of directions or principles to assist the health care practitioner with patient care decisions about appropriate diagnostic, therapeutic, or other clinical procedures for specific clinical circumstances. It is widely accepted that the adoption of guideline-execution engines in daily practice would improve the patient care, by standardising the care procedures. Guideline-based systems can constitute part of a knowledge-based decision support system in order to deliver the right knowledge to the right people in the right form at the right time. The automation of the guideline execution process is a basic step towards its widespread use in medical centres.To achieve this general goal, different topics should be tackled, such as the acquisition of clinical guidelines, its formal verification, and finally its execution. This dissertation focuses on the execution of CGs and proposes the implementation of an agent-based platform in which the actors involved in health care coordinate their activities to perform the complex task of guideline enactment. The management of medical and organizational knowledge, and the formal representation of the CGs, are two knowledge-related topics addressed in this dissertation and tackled through the design of several application ontologies. The separation of the knowledge from its use is fully intentioned, and allows the CG execution engine to be easily customisable to different medical centres with varying personnel and resources.In parallel with the execution of CGs, the system handles citizen's preferences and uses them to implement patient-centred services. With respect this issue, the following tasks have been developed: a) definition of the user's criteria, b) use of the patient's profile to rank the alternatives presented to him, c) implementation of an unsupervised learning method to adapt dynamically and automatically the user's profile.Finally, several ideas of this dissertation are being directly applied in two ongoing funded research projects, including the agent-based execution of CGs and the ontological management of medical and organizational knowledge

Securing open multi-agent systems governed by electronic institutions

One way to build large-scale autonomous systems is to develop an open multi-agent system using peer-to-peer architectures in which agents are not pre-engineered to work together and in which agents themselves determine the social norms that govern collective behaviour. The social norms and the agent interaction models can be described by Electronic Institutions such as those expressed in the Lightweight Coordination Calculus (LCC), a compact executable specification language based on logic programming and pi-calculus. Open multi-agent systems have experienced growing popularity in the multi-agent community and are expected to have many applications in the near future as large scale distributed systems become more widespread, e.g. in emergency response, electronic commerce and cloud computing. A major practical limitation to such systems is security, because the very openness of such systems opens the doors to adversaries for exploit existing vulnerabilities. This thesis addresses the security of open multi-agent systems governed by electronic institutions. First, the main forms of attack on open multi-agent systems are introduced and classified in the proposed attack taxonomy. Then, various security techniques from the literature are surveyed and analysed. These techniques are categorised as either prevention or detection approaches. Appropriate countermeasures to each class of attack are also suggested. A fundamental limitation of conventional security mechanisms (e.g. access control and encryption) is the inability to prevent information from being propagated. Focusing on information leakage in choreography systems using LCC, we then suggest two frameworks to detect insecure information flows: conceptual modeling of interaction models and language-based information flow analysis. A novel security-typed LCC language is proposed to address the latter approach. Both static (design-time) and dynamic (run-time) security type checking are employed to guarantee no information leakage can occur in annotated LCC interaction models. The proposed security type system is then formally evaluated by proving its properties. A limitation of both conceptual modeling and language-based frameworks is difficulty of formalising realistic policies using annotations. Finally, the proposed security-typed LCC is applied to a cloud computing configuration case study, in which virtual machine migration is managed. The secrecy of LCC interaction models for virtual machine management is analysed and information leaks are discussed

ASSESSMENT OF RISK SCORES FOR THE PREDICTION AND DETECTION OF TYPE 2 DIABETES MELLITUS IN CLINICAL SETTINGS

Health and sociological indicators confirm that life expectancy is increasing, and so, the years that patients have to live with chronic diseases and co-morbidities. Type 2 Diabetes is one of the most common chronic diseases, specially linked to overweight and ages over sixty. As a metabolic disease, Type 2 Diabetes affects multiple organs by causing damage in blood vessels and nervous system at micro and macro scale. Mortality of subjects with diabetes is three times higher than the mortality for subjects with other chronic diseases. On the one hand, the management of diabetes is focused on the maintenance of the blood glucose levels under a threshold by the prescription of anti-diabetic drugs and a combination of healthy food habits and moderate physical activity. Recent studies have demonstrated the effectiveness of new strategies to delay and even prevent the onset of Type 2 Diabetes by a combination of active and healthy lifestyle on cohorts of mid to high risk subjects. On the other hand, prospective research has been driven on large groups of population to build risk scores which aim to obtain a rule for the classification of patients according to the odds for developing the disease. Currently there are more than two hundred models and risk scores for doing this, but a few have been properly evaluated in external groups and, to date, none of them has been tested on a population based study. The research study presented in this doctoral thesis strives to use externally validated risk scores for the prediction and detection of Type 2 Diabetes on a population data base in Hospital La Fe (Valencia, Spain). The study hypothesis is that the integration of existing prediction and detection risk scores on Electronic Health Records increases the early-detection of high risk cases. To evaluate this hypothesis three studies on the clinical, user and technology dimensions have been driven to evaluate the extent to which the models and the hospital is ready to exploit such models to identify high risk groups and drive efficient preventive strategies. The findings presented in this thesis suggest that Electronic Health Records are not prepared to massively feed risk models. Some of the evaluated models have shown a good classification performance, which accompanied to the well-acceptance of web-based tools and the acceptable technical performance of the information and communication technology system, suggests that after some work these models can effectively drive a new paradigm of active screening for Type 2 Diabetes.Los indicadores de salud y sociológicos confirman que la esperanza de vida está aumentando, y por lo tanto, los años que los pacientes tienen que vivir con enfermedades crónicas y comorbilidades. Diabetes tipo 2 es una de las enfermedades crónicas más comunes, especialmente relacionadas con el sobrepeso y edades superiores a los sesenta años. Como enfermedad metabólica, la diabetes tipo 2 afecta a múltiples órganos causando daño en los vasos sanguíneos y el sistema nervioso a escala micro y macro. La mortalidad de sujetos con diabetes es tres veces mayor que la mortalidad de sujetos con otras enfermedades crónicas. Por un lado, la estrategia de manejo se centra en el mantenimiento de los niveles de glucosa en sangre bajo un umbral mediante la prescripción de fármacos antidiabéticos y una combinación de hábitos alimentarios saludables y actividad física moderada. Estudios recientes han demostrado la eficacia de nuevas estrategias para retrasar e incluso prevenir la aparición de la diabetes tipo 2 mediante una combinación de estilo de vida activo y saludable en cohortes de sujetos de riesgo medio a alto. Por otro lado, la investigación prospectiva se ha dirigido a grupos de la población para construir modelos de riesgo que pretenden obtener una regla para la clasificación de las personas según las probabilidades de desarrollar la enfermedad. Actualmente hay más de doscientos modelos de riesgo para hacer esta identificación, no obstante la inmensa mayoría no han sido debidamente evaluados en grupos externos y, hasta la fecha, ninguno de ellos ha sido probado en un estudio poblacional. El estudio de investigación presentado en esta tesis doctoral pretende utilizar modelos riesgo validados externamente para la predicción y detección de la Diabetes Tipo 2 en una base de datos poblacional del Hospital La Fe de Valencia (España). La hipótesis del estudio es que la integración de los modelos de riesgo de predicción y detección existentes la práctica clínica aumenta la detección temprana de casos de alto riesgo. Para evaluar esta hipótesis, se han realizado tres estudios sobre las dimensiones clínicas, del usuario y de la tecnología para evaluar hasta qué punto los modelos y el hospital están dispuestos a explotar dichos modelos para identificar grupos de alto riesgo y conducir estrategias preventivas eficaces. Los hallazgos presentados en esta tesis sugieren que los registros de salud electrónicos no están preparados para alimentar masivamente modelos de riesgo. Algunos de los modelos evaluados han demostrado un buen desempeño de clasificación, lo que acompañó a la buena aceptación de herramientas basadas en la web y el desempeño técnico aceptable del sistema de tecnología de información y comunicación, sugiere que después de algún trabajo estos modelos pueden conducir un nuevo paradigma de la detección activa de la Diabetes Tipo 2.Els indicadors sociològics i de salut confirmen un augment en l'esperança de vida, i per tant, dels anys que les persones han de viure amb malalties cròniques i comorbiditats. la diabetis de tipus 2 és una de les malalties cròniques més comunes, especialment relacionades amb l'excés de pes i edats superiors als seixanta anys. Com a malaltia metabòlica, la diabetis de tipus 2 afecta múltiples òrgans causant dany als vasos sanguinis i el sistema nerviós a escala micro i macro. La mortalitat de subjectes amb diabetis és tres vegades superior a la mortalitat de subjectes amb altres malalties cròniques. D'una banda, l'estratègia de maneig se centra en el manteniment dels nivells de glucosa en sang sota un llindar mitjançant la prescripció de fàrmacs antidiabètics i una combinació d'hàbits alimentaris saludables i activitat física moderada. Estudis recents han demostrat l'eficàcia de noves estratègies per a retardar i fins i tot prevenir l'aparició de la diabetis de tipus 2 mitjançant una combinació d'estil de vida actiu i saludable en cohorts de subjectes de risc mitjà a alt. D'altra banda, la investigació prospectiva s'ha dirigit a grups específics de la població per construir models de risc que pretenen obtenir una regla per a la classificació de les persones segons les probabilitats de desenvolupar la malaltia. Actualment hi ha més de dos-cents models de risc per fer aquesta identificació, però la immensa majoria no han estat degudament avaluats en grups externs i, fins ara, cap d'ells ha estat provat en un estudi poblacional. L'estudi d'investigació presentat en aquesta tesi doctoral utilitza models de risc validats externament per a la predicció i detecció de diabetis de tipus 2 en una base de dades poblacional de l'Hospital La Fe de València (Espanya). La hipòtesi de l'estudi és que la integració dels models de risc de predicció i detecció existents la pràctica clínica augmenta la detecció de casos d'alt risc. Per avaluar aquesta hipòtesi, s'han realitzat tres estudis sobre les dimensions clíniques, de l'usuari i de la tecnologia per avaluar fins a quin punt els models i l'hospital estan disposats a explotar aquests models per identificar grups d'alt risc i conduir estratègies preventives. Les troballes presentades sugereixen que els registres de salut electrònics no estan preparats per alimentar massivament models de risc. Alguns dels models avaluats han demostrat una bona classificació, el que va acompanyar a la bona acceptació d'eines basades en el web i el rendiment tècnic acceptable del sistema de tecnologia d'informació i comunicacions implementat. La conclusió es que encara es necesari treball per que aquests models poden conduir un nou paradigma de la detecció activa de la diabetis de tipus 2.Martínez Millana, A. (2017). ASSESSMENT OF RISK SCORES FOR THE PREDICTION AND DETECTION OF TYPE 2 DIABETES MELLITUS IN CLINICAL SETTINGS [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/86209TESI

Análise colaborativa de grandes conjuntos de séries temporais

The recent expansion of metrification on a daily basis has led to the production of massive quantities of data, and in many cases, these collected metrics are only useful for knowledge building when seen as a full sequence of data ordered by time, which constitutes a time series. To find and interpret meaningful behavioral patterns in time series, a multitude of analysis software tools have been developed. Many of the existing solutions use annotations to enable the curation of a knowledge base that is shared between a group of researchers over a network. However, these tools also lack appropriate mechanisms to handle a high number of concurrent requests and to properly store massive data sets and ontologies, as well as suitable representations for annotated data that are visually interpretable by humans and explorable by automated systems. The goal of the work presented in this dissertation is to iterate on existing time series analysis software and build a platform for the collaborative analysis of massive time series data sets, leveraging state-of-the-art technologies for querying, storing and displaying time series and annotations. A theoretical and domain-agnostic model was proposed to enable the implementation of a distributed, extensible, secure and high-performant architecture that handles various annotation proposals in simultaneous and avoids any data loss from overlapping contributions or unsanctioned changes. Analysts can share annotation projects with peers, restricting a set of collaborators to a smaller scope of analysis and to a limited catalog of annotation semantics. Annotations can express meaning not only over a segment of time, but also over a subset of the series that coexist in the same segment. A novel visual encoding for annotations is proposed, where annotations are rendered as arcs traced only over the affected series’ curves in order to reduce visual clutter. Moreover, the implementation of a full-stack prototype with a reactive web interface was described, directly following the proposed architectural and visualization model while applied to the HVAC domain. The performance of the prototype under different architectural approaches was benchmarked, and the interface was tested in its usability. Overall, the work described in this dissertation contributes with a more versatile, intuitive and scalable time series annotation platform that streamlines the knowledge-discovery workflow.A recente expansão de metrificação diária levou à produção de quantidades massivas de dados, e em muitos casos, estas métricas são úteis para a construção de conhecimento apenas quando vistas como uma sequência de dados ordenada por tempo, o que constitui uma série temporal. Para se encontrar padrões comportamentais significativos em séries temporais, uma grande variedade de software de análise foi desenvolvida. Muitas das soluções existentes utilizam anotações para permitir a curadoria de uma base de conhecimento que é compartilhada entre investigadores em rede. No entanto, estas ferramentas carecem de mecanismos apropriados para lidar com um elevado número de pedidos concorrentes e para armazenar conjuntos massivos de dados e ontologias, assim como também representações apropriadas para dados anotados que são visualmente interpretáveis por seres humanos e exploráveis por sistemas automatizados. O objetivo do trabalho apresentado nesta dissertação é iterar sobre o software de análise de séries temporais existente e construir uma plataforma para a análise colaborativa de grandes conjuntos de séries temporais, utilizando tecnologias estado-de-arte para pesquisar, armazenar e exibir séries temporais e anotações. Um modelo teórico e agnóstico quanto ao domínio foi proposto para permitir a implementação de uma arquitetura distribuída, extensível, segura e de alto desempenho que lida com várias propostas de anotação em simultâneo e evita quaisquer perdas de dados provenientes de contribuições sobrepostas ou alterações não-sancionadas. Os analistas podem compartilhar projetos de anotação com colegas, restringindo um conjunto de colaboradores a uma janela de análise mais pequena e a um catálogo limitado de semântica de anotação. As anotações podem exprimir significado não apenas sobre um intervalo de tempo, mas também sobre um subconjunto das séries que coexistem no mesmo intervalo. Uma nova codificação visual para anotações é proposta, onde as anotações são desenhadas como arcos traçados apenas sobre as curvas de séries afetadas de modo a reduzir o ruído visual. Para além disso, a implementação de um protótipo full-stack com uma interface reativa web foi descrita, seguindo diretamente o modelo de arquitetura e visualização proposto enquanto aplicado ao domínio AVAC. O desempenho do protótipo com diferentes decisões arquiteturais foi avaliado, e a interface foi testada quanto à sua usabilidade. Em geral, o trabalho descrito nesta dissertação contribui com uma abordagem mais versátil, intuitiva e escalável para uma plataforma de anotação sobre séries temporais que simplifica o fluxo de trabalho para a descoberta de conhecimento.Mestrado em Engenharia Informátic

Policy options for improving the performance of community health workers (CHWs) in maternal and child health in Brazil: analysis of barriers and facilitators to CHW national programme and evaluation of a community-based trial in Recife

Background and objectives. Studies and international agencies\u2019 policy documents, while acknowledging the potential of Community Health Worker (CHW) programs in improving reproductive maternal newborn and child health (RMNCH) outcomes, underline the scarcity of strong evidence of effectiveness and solicit more in-depth investigations on the implementation process of such programs. Recent developments about how to improve service quality in RMNCH emphasize the need of a system approach, according to which any attempt to evaluate and improve the overall system, or part of it, should take into account the overall complexity and interdependency across actors and components. Moving from the intersection between the current debate on CHWs, the emphasis on quality improvement and system approaches to health systems, the research is aimed at developing analytical and policy tools that may be used to improve the performance of CHWs in Brazil, a country whose CHW program is considered among the most valuable models globally. Methods. A three step process has been envisaged. The first step, through a systematic review of qualitative studies conducted in Brazil on CHWs and building on concepts driven from the international literature, develops a logic model to describe factors influencing CHWs\u2019 performance in Brazil and their underlying mechanisms. The second step, moving from a case study built around the impact evaluation of an intervention trial targeting CHWs in the city of Recife and aimed at supporting quality home visits to pregnant women and mothers, is aimed at providing further insights on barriers and facilitators to interventions designed to improve CHWs\u2019 performance, and at further validating the model. The third step uses the logic model to identify and systematize policy options, contextualized to the Brazilian system, to improve the performance of CHWs across all their attributions and tasks as well as in a specific area such as RMNCH. Results. The systematic review, confirming the findings of international literature, showed that, although the main factors influencing CHWs\u2019 performance reside in the formal health system components and in the sub-system elements of the CHW program, the community system is a powerful source of complex interactions that may act either as facilitators or as barriers of CHWs\u2019 performance. A logic model was developed to facilitate the identification, analysis and visualization of these factors and their dynamics. The case study confirmed the validity of the model for analyzing and interpreting the results of the intervention and, by explaining the reasons for its partial failure, provided hints about how interventions and policies aimed at improving CHWs\u2019 performances should be conceived. Using the model as the reference framework, policy options were systematized according to the health and community system components and proposed as a comprehensive compendium and as policy packages according to the various levels of responsibility regarding CHW program in the Brazilian health system. A model for prioritization criteria was also proposed. Conclusions. The analytical and policy tools that were developed may be useful for a more systematic and evidence-based approach to improving the performance of CHWs in Brazil. The systematization of influencers of CHWs\u2019 performance and their mediators can be used to describe the institutional and stakeholders\u2019 response to CHW program. The logical model, populated with institutional and behavioral facilitators and barriers, can serve to identify areas that requires action for program strengthening. The policy compendium can facilitate, at various levels of the system, the development and prioritization of policy packages aimed at improving RMNCH-related tasks of CHWs in a broader systemic perspective, recognizing that most factors influencing specific tasks of CHWs are cross-cutting and need to be addressed as such

Modèle multi-agents d'aide à la décision pour la gestion des services préhospitaliers d'urgence

La nécessité de mieux comprendre et maîtriser la complexité des systèmes d’information exige le développement de nouvelles méthodes de modélisation et de résolution de problèmes. Ce travail de recherche s’intéresse à la conception et la modélisation d’un système d’aide à la décision dans lequel le savoir et les compétences de l’expert permettent d’analyser et de proposer de nouveaux modèles multi-agents. Le développement d’un tel modèle relève un certain nombre de difficultés de conception, liés notamment à l’efficience et l’efficacité du processus de calcul et de résolution du problème, auxquels on apporte des éléments de solution. Beaucoup de systèmes complexes se caractérisent par des dynamiques non linéaires, désordonnées et aléatoires, en résumé compliquées dans le sens où leur assimilation demande du temps et du talent. Les méthodes mathématiques classiques (équations différentielles, modèles probabilistes, etc.) peuvent s’avérer inappropriées pour modéliser de tels systèmes dans lesquels l’interaction occupe un rôle très important. La modélisation à base d’agents réactifs est l’une des techniques de modélisation microscopique les plus répandues. Pourquoi choisir une modélisation orientée agent plutôt qu’un autre méta-modèle de modélisation? Premièrement, le modèle agent est très riche. Il aide ainsi le concepteur à schématiser facilement des processus qualitatifs et quantitatifs et permet d’interagir des entités hétérogènes aux architectures diverses. Pourtant, la raison principale est souvent liée à la vocation de modélisation : bien appréhender la relation entre actions/comportements individuels et action/comportement collectif. Ce travail est mené principalement dans un cadre applicatif lié au problème de planification et de gestion des services préhospitaliers d’urgence (SPU). En effet, on trouve un ensemble de recherches qui traitent le sujet de la gestion et de la planification des SPU. Chaque travail de recherche traite une problématique bien spécifique de ce domaine, soit la confection des horaires des ambulanciers, soit la gestion de la demande en services préhospitaliers, ou la gestion des véhicules/ambulances, etc. Cette thèse s’intéresse à la problématique de planification des services préhospitaliers d’urgence afin de mieux répondre à la demande de service et par conséquence diminuer le temps-réponse des ambulanciers. Elle adopte une approche de résolution globale et intégrée. Elle vise la proposition d’un modèle sous forme de différentes composantes d’aide à la décision. Elle intègre des techniques d’optimisation touchant à la fois la planification des horaires, la gestion des remplacements, la gestion de la flotte de véhicules, la gestion de la capacité des dépôts, la couverture de la demande et la gestion des événements spéciaux. Le modèle proposé est basé sur une architecture multi-agents et permet de répondre aux contraintes et aux aléas survenus lors de la planification des SPU. Le travail réalisé dans le cadre de cette thèse est articulé autour de trois articles suivants : • « Integrated and global approach (IGAP) based on multi-agent systems for the management of prehospital emergency services », soumis à Computers & Industrial Engineering de Elsevier. Cet article présente une introduction aux systèmes multiagents appliqués aux SPU et propose une nouvelle approche globale et intégrée pour sa résolution appelée IGAP. • « Scheduling Model for Prehospital Emergency Services », soumis à l’European Journal of Operational Research de Elsevier. Cet article traite le problème de confection d’horaires des techniciens ambulanciers. Notre contribution réside dans la proposition d’un modèle mathématique appelé « set covering » qui résout un problème de couverture intégré dans un nouveau système suffisamment flexible de confection d’horaires. • « Multi-Agent Decision-Making Support Model for the Management of Prehospital Emergency Services », publié dans International Journal of Machine Learning and Computing, de IACSIT. Cet article porte sur le thème de la modélisation et de l’aide à la décision dans le cadre des systèmes complexes dont on propose une architecture à base d’agents d’aide à la décision dédiée à la gestion des services préhospitaliers d’urgence

A distributed architecture for the monitoring and analysis of time series data

It is estimated that the quantity of digital data being transferred, processed or stored at any one time currently stands at 4.4 zettabytes (4.4 × 2 70 bytes) and this figure is expected to have grown by a factor of 10 to 44 zettabytes by 2020. Exploiting this data is, and will remain, a significant challenge. At present there is the capacity to store 33% of digital data in existence at any one time; by 2020 this capacity is expected to fall to 15%. These statistics suggest that, in the era of Big Data, the identification of important, exploitable data will need to be done in a timely manner. Systems for the monitoring and analysis of data, e.g. stock markets, smart grids and sensor networks, can be made up of massive numbers of individual components. These components can be geographically distributed yet may interact with one another via continuous data streams, which in turn may affect the state of the sender or receiver. This introduces a dynamic causality, which further complicates the overall system by introducing a temporal constraint that is difficult to accommodate. Practical approaches to realising the system described above have led to a multiplicity of analysis techniques, each of which concentrates on specific characteristics of the system being analysed and treats these characteristics as the dominant component affecting the results being sought. The multiplicity of analysis techniques introduces another layer of heterogeneity, that is heterogeneity of approach, partitioning the field to the extent that results from one domain are difficult to exploit in another. The question is asked can a generic solution for the monitoring and analysis of data that: accommodates temporal constraints; bridges the gap between expert knowledge and raw data; and enables data to be effectively interpreted and exploited in a transparent manner, be identified? The approach proposed in this dissertation acquires, analyses and processes data in a manner that is free of the constraints of any particular analysis technique, while at the same time facilitating these techniques where appropriate. Constraints are applied by defining a workflow based on the production, interpretation and consumption of data. This supports the application of different analysis techniques on the same raw data without the danger of incorporating hidden bias that may exist. To illustrate and to realise this approach a software platform has been created that allows for the transparent analysis of data, combining analysis techniques with a maintainable record of provenance so that independent third party analysis can be applied to verify any derived conclusions. In order to demonstrate these concepts, a complex real world example involving the near real-time capturing and analysis of neurophysiological data from a neonatal intensive care unit (NICU) was chosen. A system was engineered to gather raw data, analyse that data using different analysis techniques, uncover information, incorporate that information into the system and curate the evolution of the discovered knowledge. The application domain was chosen for three reasons: firstly because it is complex and no comprehensive solution exists; secondly, it requires tight interaction with domain experts, thus requiring the handling of subjective knowledge and inference; and thirdly, given the dearth of neurophysiologists, there is a real world need to provide a solution for this domai

The emergence of a national community health worker programme in South Africa: dimensions of governance & leadership

National community health worker programmes are returning to favour across the globe. While such programmes expand access and deepen community engagement in health, they require considerable resources and support to sustain. This thesis seeks to enhance understanding of the system-wide changes and governance and leadership required to implement community health worker programmes at scale. Empirically, it examines the implementation of a community based delivery strategy, referred to as Primary Health Care Ward Based Outreach Teams (hereafter referred to as outreach teams), adopted in South Africa since 2011. These outreach teams are reconfiguring a community based care and support sector that evolved organically in response to HIV, towards a comprehensive approach, integrated into the primary health care system. Located within the field of health policy and systems research and using multi-method (document reviews, interviews, observations) case study research, the thesis describes the evolution of community-based services in South Africa and analyses the adoption and early implementation of the outreach team strategy in two provinces (Western Cape, North West). These case studies highlight the diverse and context specific ways in which the strategy emerged at sub-national level, as a negotiated product of local histories of community based services and new mandates from the top. Drawing on an additional case study in a third province (Gauteng), a cross case analysis inductively identified the challenges facing, and the strategies adopted, by provincial and district managers in implementing the new strategy. It shows how implementation of community health worker programmes is far from linear, and the complex and distributed nature of governance and leadership required, spanning analytic, managerial, technical and political roles. The thesis concludes by proposing a multi-level governance and leadership framework for community health worker programmes at scale. Through this lens it adds a more general understanding on health system governance and leadership. The thesis is presented as four published papers embedded in a narrative, that includes a literature review and cross-cutting discussion