Dimitris Kalles

Professor

Hellenic Open University

Greece

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Dimitris Kalles is a Professor at the Hellenic Open University in Greece. His research areas encompass large language models, machine learning applications in healthcare, and algorithmic generation of realistic graphics. Recent publications have explored topics such as technical debt in AI/ML platforms, trust models for multi-agent systems, and data-driven approaches in antimicrobial resistance.

Articles (20)

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2025

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2021

Collaborators (3)

Vassilios Verykios

Professor

Hellenic Open University

GREECE

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Athanasios Anastasiou

National Technical University of Athens

GREECE

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Paraskevi Peristera

Researcher, Associate Professor

Stockholm University

SWEDEN

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Dimitris Kalles

Research Interests

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About

Articles (20)

GDPR and Large Language Models: Technical and Legal Obstacles

From Divergence to Alignment: Evaluating the Role of Large Language Models in Facilitating Agreement Through Adaptive Strategies

A Scoping Review and Assessment Framework for Technical Debt in the Development and Operation of AI/ML Competition Platforms

A Biologically Inspired Trust Model for Open Multi-Agent Systems That Is Resilient to Rapid Performance Fluctuations

From Preliminary Urinalysis to Decision Support: Machine Learning for UTI Prediction in Real-World Laboratory Data

Algorithmic Generation of Realistic 3D Graphics for Liquid Surfaces Within Arbitrary-Form Vessels in a Virtual Laboratory and Application in Flow Simulation

Deep Learning for Melanoma Detection: A Deep Learning Approach to Differentiating Malignant Melanoma from Benign Melanocytic Nevi

Data-Driven Approaches in Antimicrobial Resistance: Machine Learning Solutions

The Synergy of Machine Learning and Epidemiology in Addressing Carbapenem Resistance: A Comprehensive Review

Using Machine Learning to Calibrate Automated Performance Assessment in a Virtual Laboratory: Exploring the Trade-Off between Accuracy and Explainability

Analysis, Evaluation and Reusability of Virtual Laboratory Software Based on Conceptual Modeling and Conformance Checking

Using Machine Learning to Predict Antimicrobial Resistance―A Literature Review

An experimental comparison of single-agent and multi-agent learning-and-playing algorithms in a gaming ecosystem

Using machine learning techniques to predict antimicrobial resistance in stone disease patients

The use and applicability of machine learning algorithms in predicting the surgical outcome for patients with benign prostatic enlargement. Which model to use?

Machine Learning for Antibiotic Resistance Prediction: A Prototype Using Off-the-Shelf Techniques and Entry-Level Data to Guide Empiric Antimicrobial Therapy

Machine learning for antibiotic resistance prediction: A prototype using off-the-shelf techniques and entry-level data to guide empiric antimicrobial therapy

An IRT-based approach to assess the learning gain of a virtual reality lab students' experience

Analyzing Sequence Data with Markov Chain Models in Scientific Experiments

Ultra-short-term trading system using a neural network-based ensemble of financial technical indicators

Collaborators (3)

Vassilios Verykios

Athanasios Anastasiou

Paraskevi Peristera

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