Vilmos Bilicki

assistant professor

University of Szeged

Hungary

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Vilmos Bilicki is an assistant professor at the University of Szeged. His research interests encompass deep learning integration with transcriptomics, machine learning applications in analyzing electroencephalogram signals, and the development of telemedicine tools. He has contributed to advancing methodologies in collaboration and productivity analysis, as well as the assessment of heart rate variability as a biomarker for stress. His recent articles reflect a strong focus on interdisciplinary approaches in health and technology.

Articles (20)

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2025

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2023

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2023

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2023

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2023

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2023

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2022

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2022

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2022

Collaborators (6)

Dombi József

professor

University of Szeged

HUNGARY

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András Lovas

head of department, specialist in anaesthesiology and intensive therapy

HUNGARY

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Gergely Vadai

Assistant lecturer

University of Szeged

HUNGARY

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Szilvia Kusza

University of Debrecen

HUNGARY

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Róbert Péter

Associate Professor

HUNGARY

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Gábor Berend

assistant professor

University of Szeged

HUNGARY

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Vilmos Bilicki

Research Interests

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About

Articles (20)

Integrating Deep Learning and Transcriptomics to Assess Livestock Aggression: A Scoping Review

Repository structures: Impact on collaboration and productivity

Challenges in Generating Accurate Text in Images: A Benchmark for Text-to-Image Models on Specialized Content

A Machine-Learning-Based Analysis of Resting State Electroencephalogram Signals to Identify Latent Schizotypal and Bipolar Development in Healthy University Students

Quantifying Stress and Relaxation: A New Measure of Heart Rate Variability as a Reliable Biomarker

Multilingual Analysis and Visualization of Bibliographic Metadata and Texts With the AVOBMAT Research Tool

Factors of Weight Loss for Telemedically Supported Metabolic Syndrome Patients in a Controlled Trial

Patient Flow Analysis with a Custom Simulation Engine

Standardized Telemedicine Software Development Kit with Hybrid Cloud Support

The Influence of the Nonfunctional Requirements on the Data Model

The Actigraphy-Based Identification of Premorbid Latent Liability of Schizophrenia and Bipolar Disorder

The Actigraphy-Based Identification of Premorbid Latent Liability of Schizophrenia and Bipolar Disorder

Rule-Based Architectural Design Pattern Recognition with GPT Models

The Impact of the Web Data Access Object (WebDAO) Design Pattern on Productivity

A Data Quality Measurement Framework Using Distribution-Based Modeling and Simulation in Real-Time Telemedicine Systems

Photoplethysmograph Based Biofeedback for Stress Reduction under Real-Life Conditions in Healthcare Frontline

Photoplethysmograph Based Biofeedback for Stress Reduction under Real-Life Conditions in Healthcare Frontline

Comparison between mono and multi repository structures

An application for identification and stratification psychological crisis among pandemic frontline healthcare workers

COVID-MENTA: an integrated mental health protection system for pandemic frontline healthcare workers

Collaborators (6)

Dombi József

András Lovas

Gergely Vadai

Szilvia Kusza

Róbert Péter

Gábor Berend

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