Cooperation through information interchange in StormCast

This paper addresses the cooperation between different expert system modules in a networking environment. StormCast - a distributed artificial intelligence application for severe storm forecasting is used as a case to obtain practical results. Two key aspects is investigated, first the representation of knowledge in this kind of environment is outlined. Then the cooperating nature of a group of expert system modules is discussed

Hvordan bli professor før du er 40? (Alternativt – Hvordan bli professor?)

Dette er en fil som som vil kunne bli oppdatert. I tilfelle oppdatering vil det være viktig at den nyeste versjonen av filen brukes. Den engelske versjonen av artikkelen finnes også i Munin http://hdl.handle.net/10037/4480Med den norske opprykksordningen hvor alle med professorkompetanse gis et personlig professorat, så er det ingen andre enn den vitenskapelig ansatte selv som står i veien for professortittelen. I denne artikkelen gjennomgås 12 suksesskriterier for å oppnå professorkompetanse: (1) Ta imot faglige utfordringer; (2) tenk publisering; (3) barn bør ta tid; (4) begrens forelesningsforberedelser; (5) ha faste veiledningstidspunkt; (6) forelesningsfri = forskningstid; (7) aksepter ditt kompetansenivå; (8) etabler en infrastruktur for forskning; (9) overlat de tyngste tillitsvervene til professorene; (10) hold deg unna Internett og andre tidstyver; (11) vær sta; (12) vær strategisk – ikke kynisk. Følger du disse rådene så er professortittelen i høyeste grad oppnåelig før du fyller førti år

K-CUSUM: Cluster Detection Mechanism in EDMON

Source at https://www.ep.liu.se/ecp/contents.asp?issue=161. The main goal of the EDMON (Electronic Disease Monitoring Network) project is to detect the spread of contagious diseases at the earliest possible moment, and potentially before people know that they have been infected. The results shall be visualized on real-time maps as well as presented in digital communication. In this paper, a hybrid of K-nearness Neighbor (KNN) and cumulative sum (CUSUM), known as K-CUSUM, were explored and implemented with a prototype approach. The KNN algorithm, which was implemented in the K- CUSUM, recorded 99.52% accuracy when it was tested with simulated dataset containing geolocation coordinates among other features and SckitLearn KNN algorithm achieved an accuracy of 93.81% when it was tested with the same dataset. After injection of spikes of known outbreaks in the simulated data, the CUSUM module was totally specific and sensitive by correctly identifying all outbreaks and non-outbreak clusters. Suitable methods for obtaining a balance point of anonymizing geolocation attributes towards obscuring the privacy and confidentiality of diabetes subjects’ trajectories while maintaining the data requirements for public good, in terms of disease surveillance, remains a challenge

Open source software, the future of medical imaging?

Medical imaging and Picture Archiving and Communication Systems (PACS) in particular, have appeared to be one of the promising areas for Open Source Software (OSS). Open source medical imaging solutions do exist, including PACS, but are not widely deployed at hospitals and health care establishments, which prevents them from achieving their full potential. In most cases where medical OSS systems exist (i.e. not necessarily PACS), it is to a very limited degree, and typically out of sight of the common user. Research we have conducted on medical software companies in North Norway and three hospitals in Europe suggests that if open source medical software is to become a useful alternative to proprietary software, that firstly, the initiative must be taken by the public health services and secondly, that it will require a shift from software companies (from sale-value oriented to service oriented). However, it would be naïve to rely on existing proprietary companies to initiate such a change. Interviews revealed that some companies considered the possibilities of developing using an OSS model, but did not deem it to be profitable, whereas others stated that it was simply out of the question. They are not willing to risk their successful business models, because historically (and perhaps at the cost of quality) it pays to keep the inner workings of their software secret. Other reasons revealed for not using OSS were: poor support, prejudices and the unwillingness of proprietary companies to accept a new business model. We suggest that these problems can be overcome with the emergence of competence centers for OSS, and that if open source medical imaging, PACS projects in particular, are to get started, they are more likely to succeed if a hospital is involved. However, our suggestions can only be tested thoroughly if more implementations are done

Including patient-generated health data in electronic health records – a solution for CGM-data

Patients with diabetes and health personnel do not have an optimal way of interacting. Health personnel must use multiple ICT systems, such as third-party companies’ services, to access health-related data from diverse vendors’ CGM platforms and Electronic Health Record (EHR). Furthermore, other health-related data like physical activities, quality of life or well-being is often discussed but rarely stored inside the EHR system. We propose a future-proof architecture for diabetes medical consultation using the HL7 Fast Healthcare Interoperability Resources (FHIR) standard

Using mobile sensors to expand recording of physical activity and increase motivation for prolonged data sharing in a population-based study

Source at http://www.ep.liu.se/ecp/article.asp?issue=145&article=005.Regularly conducted population cohort studies contribute important new knowledge to medical research. A high participation rate is required in these types of studies in order to claim representativeness and validity of study results. Participation rates are declining worldwide, and re-searchers are challenged to develop new data collection strategies and tools to motivate people to participate. The last years of advances in sensor and mobile technology, and the widespread use of activity trackers and smart watches, have made it possible to privately collect physical activity data, in a cheap, easy and prolonged way. The unstructured way of collecting this data can have other applications than just showing users their activity trends. In this paper, we describe our plans for how to use these pervasive sensors as new tools for collecting data on physical activity, in a way that can motivate participants to share more information, for a longer time period and with a renewed motivation to participate in a population study

Measuring Physical Activity Using Triaxial Wrist Worn Polar Activity Trackers: A Systematic Review

International Journal of Exercise Science 13(4): 438-454, 2020. Collecting objective physical activity data from research participants are increasingly done using consumer-based activity trackers. Several validation studies of Polar devices are conducted to date, but no systematic review of the current level of accuracy for these devices exist. The aim of this study is therefore to investigate the accuracy of current wrist-worn Polar devices that equips a triaxial accelerometer to measure physical activity. We conducted a systematic review by searching six databases for validation studies on modern Polar activity trackers. Studies were grouped and examined by tested outcome, i.e. energy expenditure, physical activity intensity, and steps. We summarized and reported relevant metrics from each study. The initial search resulted in 157 studies, out of which fourteen studies were included in the final review. Energy expenditure was reviewed in seven studies, physical activity intensity was reviewed in four studies, and steps was reviewed in 11 studies. There is a large difference in study protocols with conflicting results between the identified studies. However, for energy expenditure there is some indication that Polar devices perform better in free-living, compared to lab-based studies. In addition, step counting seems to have less average error compared to energy expenditure and physical activity intensity. There is large heterogeneity between the identified studies, both in terms of study protocols and results, and the accuracy of Polar devices remains unclear. More studies are needed for more recently developed devices, and future studies should take care to follow guidelines for assessment of wearable sensors designed for physical activity monitoring

A systematic review of cluster detection mechanisms in syndromic surveillance: Towards developing a framework of cluster detection mechanisms for EDMON system

Source at http://www.ep.liu.se/ecp/151/011/ecp18151011.pdf.Time lag in detecting disease outbreaks remains a threat to global health security. Currently, our research team is working towards a system called EDMON, which uses blood glucose level and other supporting parameters from people with type 1 diabetes, as indicator variables for outbreak detection. Therefore, this paper aims to pinpoint the state of the art cluster detection mechanism towards developing an efficient framework to be used in EDMON and other similar syndromic surveillance systems. Various challenges such as user mobility, privacy and confidentiality, geographical location estimation and other factors have been considered. To this end, we conducted a systematic review exploring different online scholarly databases. Considering peer reviewed journals and articles, literatures search was conducted between January and March 2018. Relevant literatures were identified using the title, keywords, and abstracts as a preliminary filter with the inclusion criteria and a full text review were done for literatures that were found to be relevant. A total of 28 articles were included in the study. The result indicates that various clustering and aberration detection algorithms have been developed and tested up to the task. In this regard, privacy preserving policies and high computational power requirement were found challenging since it restrict usage of specific locations for syndromic surveillance

Information and communication technology-based interventions for chronic diseases consultation: Scoping review

Background: Medical consultations are often critical meetings between patients and health personnel to provide treatment, health-management advice, and exchange of information, especially for people living with chronic diseases. The adoption of patient-operated Information and Communication Technologies (ICTs) allows the patients to actively participate in their consultation and treatment. The consultation can be divided into three different phases: before, during, and after the meeting. The difference is identified by the activities in preparation (before), the meeting, conducted either physically or in other forms of non-face-to-face interaction (during), and the follow-up activities after the meeting (after). Consultations can be supported by various ICT-based interventions, often referred to as eHealth, mHealth, telehealth, or telemedicine. Nevertheless, the use of ICTs in healthcare settings is often accompanied by security and privacy challenges due to the sensitive nature of health information and the regulatory requirements associated with storing and processing sensitive information. Objective: This scoping review aims to map the existing knowledge and identify gaps in research about ICT-based interventions for chronic diseases consultations. The review objective is guided by three research questions: (1) which ICTs are used by people with chronic diseases, health personnel, and others before, during, and after consultations; (2) which type of information is managed by these ICTs; and (3) how are security and privacy issues addressed? Methods: We performed a literature search in ACM, IEEE, PubMed, Scopus, and Web of Science and included primary studies published between January 2015 and June 2020 that used ICT before, during, and/or after a consultation for chronic diseases. This review presents and discusses the findings from the included publications structured around the three research questions. Results: Twenty-four studies met the inclusion criteria. Only five studies reported the use of ICTs in all three phases: before, during, and after consultations. The main ICTs identified were smartphone applications, webbased portals, cloud-based infrastructures, and electronic health record systems. Different devices like sensors and wearable devices were used in 23 studies to gather diverse information. Regarding the type of information managed by these ICTs, we identified nine categories: physiological data, treatment information, medical history, consultation media like images or videos, laboratory results, reminders, lifestyle parameters, symptoms, and patient identification. Security issues were addressed in 20 studies, while only eight of the included studies addressed privacy issues. Conclusions: This scoping review highlights the potential for a new model of consultation for patients with chronic diseases. Furthermore, it emphasizes the possibilities for consultations besides physical and remote meetings