Proceedings of the 12th International Conference on e-Health (EH2020)最新文献

{"title":"AUDAPRET: TOWARDS A CLOUD ARCHITECTURE SUPPORTING MULTI-DEVICE RESEARCH STUDIES","authors":"Nadine von Frankenberg, Felix Matschilles, Stephan M. Jonas","doi":"10.33965/eh2020_202009c027","DOIUrl":"https://doi.org/10.33965/eh2020_202009c027","url":null,"abstract":"Recent improvements in the functional range and measurement accuracy of commercially available biosignal measurement devices enable cost-effective human trials with large numbers of participants. Biosignals can be tracked outside the research institution, with only minor restrictions in the daily activities of the study participants, compared to stationary measuring devices. However, there is a lack of data acquisition systems supporting the use of several different devices needed, so that the collected data from measurement devices have to be processed manually. Researchers must also abide by strict legal regulations when handling health-related data of study participants, which is often cumbersome and requires additional time-consuming efforts. To address these challenges, this paper proposes the AUtomatic DAta Processing of REsearch Trials (AUDAPRET) architecture, which enables researchers to conduct trials requiring health-related data of participants in a less time-consuming and legally compliant manner. AUDAPRET is designed in such a way that study participants retain full control over their data and the access rights of anyone requesting access.","PeriodicalId":393647,"journal":{"name":"Proceedings of the 12th International Conference on e-Health (EH2020)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115139407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"HOW CAN QUALITY REQUIREMENTS FOR MEDICAL SOFTWARE BE SYSTEMATICALLY FULFILLED BETTER?","authors":"Karin Messer-Misak, J. D. Bruin, S. Hanke","doi":"10.33965/eh2020_202009c026","DOIUrl":"https://doi.org/10.33965/eh2020_202009c026","url":null,"abstract":"Due to a variety of factors, among others medical and legislative requirements, the quality requirements on medical software become increasingly demanding. Several quality standards and guidelines are already in place, e.g., ISO/IEC s9126, 14598 and 25000 (SQaRE). However, there is a debate on whether these standards are not specific enough for medical software. Furthermore, their effective application for requirement gathering, analysis and monitoring can be difficult. In this paper, we propose a workflow for the application of the ISO/IEC 25010:2011 standard for the systematic collection, analysis and evaluation of requirements for various stakeholders in order to systematically better fulfill quality requirements on medical software","PeriodicalId":393647,"journal":{"name":"Proceedings of the 12th International Conference on e-Health (EH2020)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128667466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ANALYSIS OF DATA QUALITY ON ADVERSE DRUG REACTIONS AND OF METHODS FOR ITS IMPROVEMENT","authors":"Mark Tkachenko, N. Dobrenko, D. Butorina, Elvira Bulatova, A. Vatian, Anton Arazashvili","doi":"10.33965/eh2020_202009l011","DOIUrl":"https://doi.org/10.33965/eh2020_202009l011","url":null,"abstract":"This article presents the results of quality analysis of data on adverse drug reactions (ADRs) for groups of drugs, which are most frequently discussed by users of Internet resources. Several Russian-language resources were used as data sources. An open database MedDRA, translated into Russian, was used as a database of ADRs. To collect information about ADRs from Internet resources, a rule-based algorithm has been developed and implemented. Venn diagrams, multigraphs of pairwise as well as interaction scaling analysis were used to compare data on ADRs obtained from different sources. To assess the quality of the data, conditionally objective indicators were used, such as relevance, integrity, compatibility, measurability, and source characteristic. As a result, significant violations of the integrity and measurability of data were identified, and a comparative assessment of the characteristics of data sources was carried out. The ways of improving the quality of data on ADRs have been formulated.","PeriodicalId":393647,"journal":{"name":"Proceedings of the 12th International Conference on e-Health (EH2020)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132659325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"VERIFICATION OF AUTOMATA MODELS FOR CLINICAL DECISION SUPPORT SYSTEMS","authors":"G. Shovkoplias, Ivan Smirnov, Mark Tkachenko, N. Gusarova, A. Vatian, A. Shalyto, R. Niyogi","doi":"10.33965/eh2020_202009l002","DOIUrl":"https://doi.org/10.33965/eh2020_202009l002","url":null,"abstract":"In the treatment of any disease, the doctor must strictly follow the clinical protocol. However, this document cannot be fully considered as a graph diagram of the algorithm of the doctor’s actions, since most of the transition rules in it cannot be implemented without the involvement of the doctor’s knowledge. So, based on the clinical protocol, it is necessary to create a clinical decision support system (CDSS). Existing CDSSs do not allow describing the clinical protocol as a sequence of actions. This drawback can be eliminated by using the automata model as a CDSS inference engine, since the terminology of the treatment process itself leads to a natural thought - to model this process in states, i.e. use an automata approach. At the same time, it is vital to ensure the extensibility of the automata model, which will allow among other things for taking into account when choosing drugs any possible adverse reactions to drugs already prescribed. The article discusses the process of development and verification of an automata model as an inference engine for CDSS. The process, based on the Automata approach and performed offline, uses a sequence of refinements, which allows you to get a more detailed model that reflects the typical options for the doctor. In addition, with each replacement or addition of the drug, online testing of the model is performed, during which compatibility with the already prescribed drugs and the patient's history is checked. The developed process is applied to the construction and verification of CDSS for the management of patients with multiple sclerosis. to automata","PeriodicalId":393647,"journal":{"name":"Proceedings of the 12th International Conference on e-Health (EH2020)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125386297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ONCONET - A DIGITAL SERVICE FOR REMOTE MONITORING AND SUPPORT OF CANCER PATIENTS ON CHEMOTHERAPY","authors":"I. G. Kargalskaja, S. A. Shinkarev, B. Zingerman, I. Fistul, A. Nozik, S. B. Arseniev","doi":"10.33965/eh2020_202009c024","DOIUrl":"https://doi.org/10.33965/eh2020_202009c024","url":null,"abstract":"Background: Cancer patients suffer from many complications caused by both the disease itself and the side effects of anticancer treatment Many symptoms go unnoticed by doctors because of the patient's remote location, significant interruptions between face-to-face visits to the doctor and differences in the individual course of the disease In a pandemic caused by Covid 19, cancer patients are at great risk The practical impossibility of patient's visit to a doctor, conduct clinical trials determines the highest risk for this group of patients Thus the relevance of remote support for these patients in isolation increases many times Objective: The goal was to create and implement in a pilot project a digital service (ONCONET system) for remote monitoring of cancer patients outside the hospital as well as adaptation to COVID 19 pandemic Methods: The developed platform is a cloud service hosted in a data processing center which provides healthcare organizations with a ready-made service The system is based on specialized questionnaires developed by oncologists for remote assessment of the patient's condition The important component of the system are content libraries for patients and doctors, information and reference materials as the collection of video-schools from leading experts of nosology, rules of life, nutrition, rehabilitation and care Results: To evaluate the effectiveness of the ONCONET system, 2 groups of patients were formed: ONCONET group - 206 patients and retrospective control group - 209 patients Statistical analysis revealed significant differences between groups as a whole, as well as between individual factors of complications Conclusion: The study demonstrates the usefulness and high medical efficiency of the ONCONET system for remote monitoring of cancer patients, especially against the background of a pandemic and the necessary self-isolation of cancer patients © Proceedings of the 12th IADIS International Conference e-Health 2020, EH 2020 - Part of the 14th Multi Conference on Computer Science and Information Systems, MCCSIS 2020 All rights reserved","PeriodicalId":393647,"journal":{"name":"Proceedings of the 12th International Conference on e-Health (EH2020)","volume":"113 16","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113940626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ALL YOU NEED IS HIGHER ACCURACY? ON THE QUEST FOR MINIMUM ACCEPTABLE ACCURACY FOR MEDICAL ARTIFICIAL INTELLIGENCE","authors":"F. Cabitza, A. Campagner, F. Zotti, Alice Ravizza, Federico Sternini","doi":"10.33965/eh2020_202009l020","DOIUrl":"https://doi.org/10.33965/eh2020_202009l020","url":null,"abstract":"In this paper we will discuss the concept of the minimum level of accuracy an Artificial Intelligence system must exhibit in medical settings to be fit to its intended use and improve the daily practice of its intended users, the medical doctors. We will consider simple binary classification tasks in both diagnostic and prognostic ambit (like to discriminate between normal/abnormal case, and improvement/no improvement prospects). We will make the point that the common ways to determine this minimum acceptable accuracy are fraught with many conceptual and practical troubles. We will report about a small user study conducted to elicit the discriminative requirements from a sample of medical doctors, stratified both in general practitioners and specialists. Finally, we will present a simple nomogram by which to determine the minimum accuracy of a technological aid, once the human average performance and the desired level of accuracy are known. The nomogram is to be intended as a provocative simple tool to recognize that the technological tool is less important than a sound protocol in which to use it, responsibly and paying due attention to the role of the human decision makers.","PeriodicalId":393647,"journal":{"name":"Proceedings of the 12th International Conference on e-Health (EH2020)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121651824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PRIMARY USE CASE IMPLEMENTATION OF INTERNATIONAL PATIENT SUMMARY ON openEHR PLATFORM","authors":"E. Krastev, Petko Kovatchev, D. Tcharaktchiev, Simeon Abanos","doi":"10.33965/eh2020_202009l021","DOIUrl":"https://doi.org/10.33965/eh2020_202009l021","url":null,"abstract":"The International Patient Summary (IPS) comprises the essential clinical data that must be available in case an European citizen needs unscheduled or urgent health care while abroad. The implementation of cross- border exchange of IPS is among the highest priorities of the European commission. Detailed functional requirements and use cases have been elaborated in addition to a new IPS standard in recent years as part of the efforts for enabling interoperability in information exchange and continuity of care. This paper presents a practicable approach and a solution to the problem of achieving semantic interoperability among the IPS sources in the European union. A novelty approach in this paper is first to design and analyze the business process of the primary use case and after that to propose a solution. It allows to identify several activities that are out of the scope in the existing documents and at the same time require special attention at the stage of software implementation. The proposed solution makes use of the openEHR information model to represent the IPS standard dataset in terms of archetypes. This way we preserve the semantic context in clinical concepts as well as introduce interoperability among data providers. Moreover, it overcomes the severe drawback of the message paradigm, where every two communicating parties must apply transformation of existing data that is specific to their needs. The discussion considers a computer experiment with real data employing a fully functional web application for IPS cross-border exchange. business process model. The computer experiments show that the web application precisely executes the sequence of activities in the BPMN model. Moreover, the application reads and writes electronic health records of a patient’s IPS, whose data structure follows the current EN 17269:2019 standard for this document. The experimental results demonstrate that the electronic health records satisfy both the dual information model of openEHR and the IPS standard EN 17269:2019. We show that the Medication summary section on these records encapsulates detailed semantic context describing each previously prescribed medication.","PeriodicalId":393647,"journal":{"name":"Proceedings of the 12th International Conference on e-Health (EH2020)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114185841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"APPLICATION OF DATA LAKE APPROACH FOR DATA ANALYTICS IN E-HEALTH ISSUES OF ARCHITECTURES AND ORGANIZATION","authors":"B. Molnár, Á. Tarcsi","doi":"10.33965/eh2020_202009r029","DOIUrl":"https://doi.org/10.33965/eh2020_202009r029","url":null,"abstract":"By a case study approach, the paper analyzes a project and information ecosystem of the Clinical Research environment within a Medical School at a University. There are two types of data sources, a medical information system based on a transactional database for recording patients and serving as the basis of nursing and treatments of patients and medical and other medical IoT systems (like ECGs, etc). There exists neither Data Warehouse solutions nor any other data collection solutions dedicated to utilizing Data Science methods and tools. The emerging technologies provide opportunities for synergy between the traditional Data Warehouse and the most recent Data Lake approaches. Therefore, it seems feasible and reasonable to integrate these two architecture approaches to support data analytics on the research of medicine and biomedical areas.","PeriodicalId":393647,"journal":{"name":"Proceedings of the 12th International Conference on e-Health (EH2020)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128414549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"APPLICATION OF AUTOMATON MODEL TO SUPPORT REHABILITATION OF MOTOR SKILLS OF PATIENTS","authors":"G. Shovkoplias, Eduard Glekler, V. Povyshev, Jaafar Hammoud, N. Gusarova, A. Vatian, A. Shalyto","doi":"10.33965/eh2020_202009l005","DOIUrl":"https://doi.org/10.33965/eh2020_202009l005","url":null,"abstract":"Rehabilitation of patients during illnesses associated with the loss of motor skills, such as multiple sclerosis, is an important task of medicine. Effective in these cases are gaming approaches that increase patient motivation, which in the field of e-Health form the direction of “Serious Games”. The essential requirements in the development of Serious Games are the continuity of training, which should be carried out not only in a specialized center, but al-so by the patient himself at home, as well as the accuracy of the movements performed by the patient; otherwise, the outcome of the rehabilitation will be doubtful or even negative. As the basis for satisfying the rigorous requirements for the correctness of the movements performed the automatic simulation of the game process is chosen. Serious Games differ from regular games in a significantly smaller number of possible states, which makes them convenient for applying this approach. At the same time, in contrast to the previously considered applications of au-tomaton models in medical systems, such as, for example, systems for sup-porting hemodialysis, in the case of a game, the parameters of each state can vary over a fairly wide range. In the article, this problem is considered in the example of rehabilitation of pinch movements of hands by performing physical exercises in a specialized video game form using motion capture of fingers on a smartphone. The Ab-stract State Machine method is used to build the automaton model applicable to the Serious Game for pinch movement, which provides opportunities and motivation of the patient to do independent exercises. To build the resulting model, the method of successive refinements is used, on each of which veri-fication is performed, which provides the necessary control over the accuracy of patient movements.","PeriodicalId":393647,"journal":{"name":"Proceedings of the 12th International Conference on e-Health (EH2020)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133487529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EVALUATION OF COST-SAVING MACHINE LEARNING METHODS FOR PATIENT BLOOD MANAGEMENT","authors":"Davide Brinati, Andrea Seveso, P. Perazzo, G. Banfi, F. Cabitza","doi":"10.33965/eh2020_202009l023","DOIUrl":"https://doi.org/10.33965/eh2020_202009l023","url":null,"abstract":"Our objective is the development of cost-saving methods for the patient blood management in Galeazzi Orthopedic Institute, a large Italian hospital. The methods have been developed in relation to the known costs of the hospital, both in terms of unused blood bags and drugs. Observational data about 4593 patients have been retrieved, with anagraphical and pre-operational clinical features. Model’s performances have been compared to an existing baseline in terms of both accuracy measures (F1, recall, AUC) and saved costs per patient. The proposed methods recorded an enhancement of performances for the adopted measures, demonstrating a possible useful application of machine-learning-based methods for the patient blood management task.","PeriodicalId":393647,"journal":{"name":"Proceedings of the 12th International Conference on e-Health (EH2020)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126360290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}