Learn more about me
Welcome to my professional space!
I am Dimitris Dimopoulos, a passionate researcher at the intersection of economics, information systems, and artificial intelligence. With a robust academic background comprising a bachelor's degree in economics, a master's degree in information and communication systems, and ongoing PhD studies, I am committed to creating solutions that enhance peoples life.
Vision and Purpose
My journey is driven by the vision to harness the power of technology to make significant improvements in healthcare. As a PhD candidate specializing in bioinformatics, my research leverages artificial intelligence to develop predictive models that support medical decision-making. By analyzing clinical and medical data, I aim to provide tools that assist healthcare professionals in making more accurate and timely decisions, ultimately improving patient outcomes.
Research and Publications
My research focuses on developing machine learning models for predictive analysis in healthcare. I have presented my research at prominent conferences, including the 12th and 13th Conference on Artificial Intelligence in 2022 and 2024, and published in respected journals like ACM and Thrombosis and Haemostasis.
Future Goals
Looking ahead, my goal is to continue pushing the boundaries of AI in healthcare, developing advanced models that can further assist medical professionals and improve patient care. I aspire to contribute to a future where technology and medicine work hand in hand to save lives and enhance the quality of healthcare globally.
Check My Resume
University of the Aegean, Samos, Greece
PhD research on the application of both Machine (ML) and Deep Learning (DL) to medical - clinical data.
University of the Aegean, Samos, Greece
Master degree in the field of Information Technology by the "Department of Information and Communication Systems Engineering".
Technological Educational Institute, Chalkida, Greece
Degree in Finance with specialization in Accounting.
Proceedings of the 13th Hellenic Conference on AI
Length of Stay & Mortality Prediction for Patients Suffering from Stroke in ICU: A Multimodal Approach
Hellenic Institute of Advanced Studies
Machine learning-based predictive models for patients with venous thromboembolism: A Systematic Review.
Proceedings of the 12th Hellenic Conference on AI
Mortality Prediction in ICU Patients Suffering from Stroke
