Dimitris Gatsios, Greece

University of Ioannina Neurology

Dimitris Gatsios (Male) is Capemed cofounder and COO. Dimitris graduated from the Department of Computer Science of the University of Ioannina in 2004. He has more than 15 years of experience in the acquisition and management of publicly funded projects (medical technology, life sciences, IT). He has been working for Greek Universities and Institutes, at first as a researcher, and then as technical and project manager in EU funded projects (RIGHT, METABO, VPH2, Telecardiology, MICRO, PD_manager, HOLOBALANCE, PD_Pal) since 2006. He has a solid background and very good knowledge of the state of the art in the fields of knowledge management, wearable technology, data mining, medical informatics, m-health and health ecosystems. On top, Dimitris is also seeking his PhD in the Neurology Department, Faculty of Medicine, University of Ioannina.

Presenter of 2 Presentations

Conference Calendar

DESIGNING A CLINICAL DECISION SUPPORT SYSTEM (CDSS) FOR PERSONALISED MEDICINE IN PARKINSON’S DISEASE

Session Name

DIGITAL END-POINTS AND ARTIFICIAL INTELLIGENCE

Session Type

SYMPOSIUM

Date

14.03.2021, Sunday

Session Time

12:00 - 13:45

Room

On Demand Symposia B

Lecture Time

12:30 - 12:45

Presenter

Dimitris Gatsios, Greece

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Abstract

Abstract

Aims

To design an EHR-agnostic, CDSS for personalized medicine approaches in the management of Parkinson's disease (PD) that complements symptomatic treatment by adopting a holistic strategy, as well as passive (with IoT devices) and active (with diaries) patient monitoring.

Methods

The design is based on the recent literature on CDSS, the findings of previous studies evaluating mhealth for the management of Parkinson’s and the analysis of user needs that defined shared decision making, flexibility that accounts for variation among clinicians and monitoring of information integration from multiple sources as the main design principles.

Results

PRIME is a traditional CDSS in the sense that it is comprised of interoperable, FHIR compliant, software designed to be a direct aid to clinical-decision making; the characteristics of an individual patient derived from EHRs, IoT devices such as Apple iWatch and diary data, and processed with machine learning methods, are matched to a computerized clinical knowledge base (derived from Clinical Guidelines, drug and gene interaction DBs and the PD ontology) and patient-specific assessments or recommendations are then presented to the clinician for a decision through a dedicated, user interface.

Conclusions

PRIME which is co‐financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH – CREATE – INNOVATE (project code:Τ2EDK- 05199) will be an evidenced-based CDSS capable of leveraging data and observations otherwise unobtainable or uninterpretable by humans and produce appropriate alerts.

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