Διαχείριση ηλεκτρονικών φακέλων υγείας διαβητικών και Covid-19 ασθενών με την χρήση υπηρεσιών μηχανικής μάθησης και διαλειτουργικότητας δεδομένων

Ζαφειρόπουλος, Νικόλαος

Management of electronic health records of dabetic and Covid-19 patients using machine learning and data interoperability services

Master Thesis

Author

Ζαφειρόπουλος, Νικόλαος

Date

2023-02

Abstract

In our time, it is a fact that the health sector, and more specifically the healthcare sector, lags behind in terms of developing smart applications with Machine Learning (ML) and Data Interoperability (DI) mechanisms. In the everyday life of a citizen, the use and application of Information Technology (IT) in health care provides a number of benefits with significant importance. These cannot be as better and more immediate for patients, as the facilitation of medical and nursing staff in collaboration with health policy makers. However, following the emergence of the new virus in late 2019 (SARS-CoV-2), many perceptions have changed. One of them is related to the application and adaptation of new technologies in the field of health. Thus, it was realized that there has been a significant movement in the research and development areas of the sector in question. Therefore, the subject of this work is the examination of the Electronic Health Record (EHR) of a patient based on his medical history. The system that supports this report and which was developed in the context of the thesis is the "up-health" information system. With this particular system, medical staff can instantly and quickly see a patient's EHR information. Both the modeling of the NHS and the development of the models are done through the mechanisms of Artificial Intelligence (AI) to predict either based on the first scenario which is the most suitable treatment for diabetes or with the second scenario which is the condition of a patient, regarding whether or not to be admitted to the Intensive Care Unit (ICU), due to respiratory problems (Covid-19). Also, the information that differs within the system but also with external entities of other systems, will be modeled and follow the HL7 FHIR (Health Level Seven Fast Healthcare Interoperability Resources) standard. The aforementioned services, as well as the User Interface, are user-friendly through the use of new technologies to provide appropriate management of the EHR. Also, through the "up-health" system, the doctor can immediately make an appointment for his patient, register a patient, and see aggregate data. He can also see, both the analysis of the important features that you keep in his file, and all the features that make up the EHR. Additionally, before the analysis of the "up-health" information system, a study is made of the international literature concerning the field of Machine Learning and then of the second field to be studied, that of Data Interoperability with a detailed report, for the EHR. Therefore, through this specific system, solutions will be able to be offered in the field of health. They will act as procedures for the digitization and electronic registration of a patient's details. Through the aforementioned report, both the time and the cost required to maintain a computerized file are reduced, as well as the frequent phenomenon of delay, regarding the diagnosis of a disease, but also the immediate setting of an appointment to avoid, any confusion at appointments on the part of the medical staff, but also of citizens to avoid unnecessary travel.

Postgraduate Studies Programme

Προηγμένα Συστήματα Πληροφορικής

Department

Σχολή Τεχνολογιών Πληροφορικής και Επικοινωνιών. Τμήμα Ψηφιακών Συστημάτων

Number of pages

107

Language

Greek

URI

https://dione.lib.unipi.gr/xmlui/handle/unipi/15221
http://dx.doi.org/10.26267/unipi_dione/2643

Collections

Τμήμα Ψηφιακών Συστημάτων

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Except where otherwise noted, this item's license is described as
Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα