Using domain knowledge to improve intelligent decision support in intensive medicine - a study of bacteriological infections

Nowadays antibiotic prescription is object of study in many countries. The rate of prescription varies from country to country, without being found the reasons that justify those variations. In intensive care units the number of new infections rising each day is caused by multiple factors like inpatient length of stay, low defences of the body, chirurgical infections, among others. In order to complement the support of the decision process about which should be the most efficient antibiotic it was developed a heuristic based in domain knowledge extracted from biomedical experts. This algorithm is implemented by intelligent agents. When an alert appear on the presence of a new infection, an agent collects the microbiological results for cultures, it permits to identify the bacteria, then using the rules it searches for a role of antibiotics that can be administered to the patient, based on past results. At the end the agent presents to physicians the top-five sets and the success percentage of each antibiotic. This paper presents the approach proposed and a test with a particular bacterium using real data provided by an Intensive Care Unit.This work has been supported by FCT – Fundação para a Ciência e Tecnologia in the scope of the project: Pest-OE/EEI/UI0319/2014 and PEst-OE/EEI/UI0752/2014. The authors would like to thank FCT (Foundation of Science and Technology, Portugal) for the financial support through the contract PTDC/EEI-SII/1302/2012 (INTCare II)

Pervasive intelligent models to predict the outcome of COVID-19 patients

Nowadays, there is an increasing need to understand the behavior of COVID-19. After the Directorate-General of Health of Portugal made available the infected patient’s data, it became possible to analyze it and gather some conclusions, obtaining a better understanding of the matter. In this context, the project developed—ioCOVID19—Intelligent Decision Support Platform aims to identify patterns and develop intelligent models to predict and support clinical decisions. This article explores which typologies are associated with different outcomes to help clinicians fight the virus with a decision support system. So, to achieve this purpose, classification algorithms were used, and one target was studied—Patients outcome, that is, to predict if the patient will die or recover. Regarding the obtained results, the model that stood out is composed of scenario s4 (composed of all comorbidities, symptoms, and age), the decision tree algorithm, and the oversampling sampling method. The obtained results by the studied metrics were (in order of importance): Sensitivity of 95.20%, Accuracy of 90.67%, and Specificity of 86.08%. The models were deployed as a service, and they are part of a clinical decision support system that is available for authorized users anywhere and anytime.This research was funded by Portugal 2020 program through NORTE-01-02B7-FEDER-048344

XIII International Congress in Animal Hygiene, June 17-21, 2007, Tartu, Estonia "Animal health, animal welfare and biosecurity" : proceedings. Volume 1

KonverentsikogumikOn behalf of both the Organising Committee and the Scientific Committee, I am pleased to welcome you in Tartu, Estonia, to participate at the XIII International Congress of the International Society for Animal Hygiene (ISAH). The ISAH (www.isah-soc.org) was founded in 1970 and has today members from 48 countries throughout the world. ISAH can be considered as a group of scientists contributing to efficient, sustainable animal farming with healthy animals, providing wholesome food in a sound environment. Veterinarians and non-veterinary academic scientists (animal science, agricultural economics, engineers, microbiologists, public health professionals, epidemiologists etc., etc) and respective professionals in animal husbandry, who work and/or do research and education in the field of animal hygiene, can apply for a membership of ISAH, and are most welcome to attend ISAH congresses. The first ISAH congress was held in Budapest in 1973. The last ISAH main congress took place in Warsaw, Poland in 2005 and the last in-between symposium in Saint-Malo, France in 2004. Starting from Warsaw congress in 2005, the ISAH, considering the need for a more flexible and frequent exchange of scientific and practical knowledge, organizes its congresses every second year. The present, XIII ISAH congress in Tartu, Estonia, in June 17–21, 2007 is organised under the device "Animal health, animal welfare and biosecurity”. The scientific programme, trying to follow the scope of the ISAH and receive the feedback from modern animal husbandry and food production, concentrates with more profoundness on the following subjects: interaction between the environment and health and welfare of individual animal and herds; managing animal health in large dairy units; ensuring animal welfare during transportation and slaughter; economical implications considering animals’ health; possibilities of precision livestock farming in maintaining good health and welfare of animals; measures for prevention the development and spread of diseases and pathogens in animals including those posing risk to human health (zoonoses); food safety relevant infections and contaminations such as residues in food derived from animals; influence of the animal production on the environment and public health. The Proceedings from the XIII ISAH Congress are herewith presented. The papers on lectures from invited speakers, oral and poster presentations from 11 parallel sessions are included in this excellent compilation. In general, the printed contribution to the ISAH-2007 congress illustrates clearly the broad scientific field of the ISAH and related to it activities. I hereby would like to express my most sincere gratitude in the address of ISAH-2007 organising and scientific committees. Special thanks go to Frens Conference Services for their excellent organizational and technical contribution and to AS Triip for their outstanding printing job of these proceedings. We also appreciate different companies and organisations for their considerable financial support which gave us the opportunity to keep the registration fees affordable. Finally, we thank all participants, contributors, chairpersons, organisational and technical assistants for your considerable efforts – you made the ISAH-2007 in Tartu real success. We wish you all interesting and pleasant congress and enjoyable stay in Tartu. A. Aland Editor Chairman of the ISAH-2007 Organising Committe

11th International Conference on Business, Technology and Innovation 2022

Welcome to IC – UBT 2022 UBT Annual International Conference is the 11th international interdisciplinary peer reviewed conference which publishes works of the scientists as well as practitioners in the area where UBT is active in Education, Research and Development. The UBT aims to implement an integrated strategy to establish itself as an internationally competitive, research-intensive university, committed to the transfer of knowledge and the provision of a world-class education to the most talented students from all background. The main perspective of the conference is to connect the scientists and practitioners from different disciplines in the same place and make them be aware of the recent advancements in different research fields, and provide them with a unique forum to share their experiences. It is also the place to support the new academic staff for doing research and publish their work in international standard level. This conference consists of sub conferences in different fields like: Security Studies Sport, Health and Society Psychology Political Science Pharmaceutical and Natural Sciences Mechatronics, System Engineering and Robotics Medicine and Nursing Modern Music, Digital Production and Management Management, Business and Economics Language and Culture Law Journalism, Media and Communication Information Systems and Security Integrated Design Energy Efficiency Engineering Education and Development Dental Sciences Computer Science and Communication Engineering Civil Engineering, Infrastructure and Environment Architecture and Spatial Planning Agriculture, Food Science and Technology Art and Digital Media This conference is the major scientific event of the UBT. It is organizing annually and always in cooperation with the partner universities from the region and Europe. We have to thank all Authors, partners, sponsors and also the conference organizing team making this event a real international scientific event. Edmond Hajrizi, President of UBT UBT – Higher Education Institutio

On the Edge of Sustainability: Perspectives on Peri-urban Dynamics

This paper examines some of the many ways in which the peri-urban has been theorised, considering, in particular, the implications for a normative research agenda towards improved environmental and social justice. The paper discusses the value of different notions of sustainability in the context of the peri-urban, challenging the view that ‘sustainability’ is not an appropriate goal in relation to cities which are seen, by some urban theorists, as inherently ‘unsustainable’. Drawing on examples, largely from south Asia, in health service provision, water management and agriculture and food systems, the particular challenges posed by the peri-urban situation in relation to environmental integrity and social justice are reviewed (in line with the STEPS definition of Sustainability which emphases that the objects being sustained are increasing levels of social justice and enhancing environmental integrity). The contribution of both peri-urban theoretical conceptualisations and empirical research to date in the context of Sustainability goals are reviewed, offering suggestions for complementary approaches and progression. Drawing on a notion of pathways (as self reinforcing trajectories of change – both existing and potential), alternative perspectives in planning and management of the peri-urban are considered through examples from policy and practice across sectors; initiatives to increase participation in urban planning processes; citizen action to mobilise access to key resources for the poor, and the engagement of poor and marginalised groups.ESR

Therapeutic Gastrointestinal Endoscopy

Endoscopy has had a big role in the development of modern gastroenterology. Modern endoscopy will certainly be more therapeutic. It started with endoscopic hemostasis and polipectomy, than beginning of the 1970's with the advent of endoscopic sphincterotomy extended to biliopancreatic pathology and has a huge impact in this difficult pathology. Plastic stents made the first steps in endoscopic palliation of neoplastic jaundice, metallic stents, covered or uncovered are better for biliary palliation and can be used also for palliation neoplastic obstruction at different levels of the digestive tube. Resection of digestive tumors has evolved now to sub-mucosal resection, looking to have one-piece complete resection. Interventional endoscopy is now very complex and takes a lot of time for endoscopists to learn properly these techniques. This book is a very good up-to-date overview of new techniques of interventional endoscopy for those who want to learn or develop their knowledges in this field

Machine learning approaches to optimise the management of patients with sepsis

The goal of this PhD was to generate novel tools to improve the management of patients with sepsis, by applying machine learning techniques on routinely collected electronic health records. Machine learning is an application of artificial intelligence (AI), where a machine analyses data and becomes able to execute complex tasks without being explicitly programmed. Sepsis is the third leading cause of death worldwide and the main cause of mortality in hospitals, but the best treatment strategy remains uncertain. In particular, evidence suggests that current practices in the administration of intravenous fluids and vasopressors are suboptimal and likely induce harm in a proportion of patients. This represents a key clinical challenge and a top research priority. The main contribution of the research has been the development of a reinforcement learning framework and algorithms, in order to tackle this sequential decision-making problem. The model was built and then validated on three large non-overlapping intensive care databases, containing data collected from adult patients in the U.S.A and the U.K. Our agent extracted implicit knowledge from an amount of patient data that exceeds many-fold the life-time experience of human clinicians and learned optimal treatment by having analysed myriads of (mostly sub-optimal) treatment decisions. We used state-of-the-art evaluation techniques (called high confidence off-policy evaluation) and demonstrated that the value of the treatment strategy of the AI agent was on average reliably higher than the human clinicians. In two large validation cohorts independent from the training data, mortality was the lowest in patients where clinicians’ actual doses matched the AI policy. We also gained insight into the model representations and confirmed that the AI agent relied on clinically and biologically meaningful parameters when making its suggestions. We conducted extensive testing and exploration of the behaviour of the AI agent down to the level of individual patient trajectories, identified potential sources of inappropriate behaviour and offered suggestions for future model refinements. If validated, our model could provide individualized and clinically interpretable treatment decisions for sepsis that may improve patient outcomes.Open Acces