| Vol-3609 urn:nbn:de:0074-3609-1 Copyright © 2023 for the individual papers by the papers' authors. Copyright © 2023 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# IDDM 2023
Informatics & Data-Driven Medicine 2023

### Proceedings of the 6th International Conference on Informatics & Data-Driven Medicine

### Bratislava, Slovakia, November 17-19, 2023.

Edited by

### Nataliia Shakhovska *
Michal Kovac **
Ivan Izonin ***
Stephane Chretien ****

* Lviv Polytechnic National University, Institute of Computer Science and Information Technologies, 28a Bandery St., Building 5, Lviv, Ukraine
** Slovak University of Technology in Bratislava, Faculty of Informatics and Information Technologies Ilkovičova 2 SK-842 16 Bratislava 4, Slovac Republic
*** Lviv Polytechnic National University, Institute of Computer Science and Information Technologies, 28a Bandery St., Building 5, Lviv, Ukraine
**** Université Lumiere Lyon 2, Faculty of Anthropology, Sociology and Political Science, 5 avenue Pierre Mendès-France Campus Porte des Alpes - Lyon 69676, France

## Table of Contents

- Preface
  Summary: There were 105 papers submitted for peer-review to this conference. Out of these, 31 papers were accepted for this volume, 22 as regular papers and 9 as short papers.

### Session 1

- Robust R-peak Detection using Deep Learning based on Integrating Domain Knowledge 1-14
  Oleksii Kovalchuk, Pavlo Radiuk, Olexander Barmak, Iurii Krak
- Method and Software Tool for Generating Artificial Databases of Biomedical Images Based on Deep Neural Networks 15-26
  Oleh Berezsky, Petro Liashchynskyi, Oleh Pitsun, Grygoriy Melnyk
- Mobile Cyber-Physical System for Diabetic Patients' Health Status Monitoring 27-36
  Tetiana Hovorushchenko, Maksym Pytlyak, Olha Hovorushchenko, Illya Paionk, Vitaliy Osyadlyi, Artem Boyarchuk
- Open Public Data and Early Factor Analysis in a Developing Public Health Event 37-47
  Serge Dolgikh
- Applying Convolutional Neural Network for Cancer Disease Diagnosis Based on Gene Expression Data 48-61
  Sergii Babichev, Ihor Liakh, Vasyl Morokhovych, Andrii Honcharuk, Anatolii Balanda, Oleksandr Zaitsev
- Two-Stage Approach for Semantic Image Segmentation of Breast Cancer: Deep Learning and Mass Detection in Mammographic Images 62-76
  Faycal Touazi, Djamel Gaceb, Marouane Chirane, Selma Hеrzallah
- Myocardium Segmentation using Two-Step Deep Learning with Smoothed Masks by Gaussian Blur 77-91
  Vitalii Slobodzian, Pavlo Radiuk, Anastasiia Zingailo, Olexander Barmak, Iurii Krak
- A Data-Driven Simulation of Ukrainian Refugee Flows Impact on COVID-19 Dynamics in the UK 92-102
  Dmytro Chumachenko, Vasyl Chomko, Ievgen Meniailov, Serhii Krivtsov, Halyna Padalko
- Health and Fitness Apps: An Analysis of Gamification Elements in Austria 103-114
  Ana D. Domuta, Otilia Libal, Christine Strauss
- FedDDR: A Federated Improved DenseNet for Classification of Diabetic Retinopathy 115-125
  Akansha Singh, Krishna Kant Singh
- Adaptive Metaheuristic Methods Based on the Covid-19 Virus’ Behavior and Measures for Fight It 126-137
  Eugene Fedorov, Olga Nechyporenko, Maryna Leshchenko, Tetyana Utkina, Kostiantyn Rudakov, Nataliia Lada
- Generalizing the Antiviral Immune Response Model to Account for Adsorption Therapy in Conditions of Diffusion Perturbations and the Organism’s Temperature Response 138-144
  Serhii Baranovsky, Andrii Bomba, Oksana Pryshchepa
- IoT Smart Implants: Information Security and the Implementation of Lightweight Cryptography 145-156
  Inna Rozlomii, Andrii Yarmilko, Serhii Naumenko, Pavlo Mykhailovskyi
- Formation of Indicators for Evaluating the Model Based on a Set of Interconnected Data Sets in the Tasks of Communication Technologies in Healthcare 157-166
  Alexander Trunov
- Identification of Personality Based on the Sphenoid Sinus Structure Using Machine Learning 167-173
  Alina Nechyporenko, Marcus Frohme, Vladyslav Omelchenko, Victoriia Alekseeva, Andrii Lupyr, Vitaliy Gargin

### Session 2

- New CNN Stacking Model for Classification of Medical Imaging Modalities and Anatomical Organs on Medical Images 174-188
  Mamar Khaled, Djamel Gaceb, Fayçal Touazi, Chakib Ammar Aouchiche, Youcef Bellouche, Ayoub Titoun
- Parallel Algorithms for Interpolation with Bezier Curves and B-Splines for Medical Data Recovery 189-197
  Lesia Mochurad, Yulianna Mochurad
- Classification of Patients with the Development of Alzheimer's Disease using an Ensemble of Machne Learning Models 198-216
  Mariia Nykoniuk, Nataliia Melnykova, Yurii Patereha, Dariusz Sala, Dariusz Cichoń
- HelpDiabeto: A user-friendly Tool for Diabetes Tracking and Monitoring 217-228
  Houda El Bouhissi, Wissam Aitousekhri, Lahna Asbai
- Uncertain Model for Classification of Children's Neurological Diseases 229-240
  Olga Rybytska, Ivanna Dronyuk, Andriy Pushnyk
- MLOps Approach for Automatic Segmentation of Biomedical Images 241-248
  Oleh Berezsky, Oleh Pitsun, Grygoriy Melnyk, Yuriy Batko, Petro Liashchynskyi, Mykola Berezkyi
- The Peculiarities of Measuring Bone Density in Males and Females Using Uncertainty Calculation 249-254
  Alina Nechyporenko, Viktor Reshetnik, Alla Dzyza, Victoriia Alekseeva, Andrii Lupyr, Vitaliy Gargin
- Indicators of the Course Remote Procedures Correction according to IoMT the Patient State Assessments in Restorative Medicine 255-264
  Aleksander Trunov, Ivanna Dronyuk, Ivan Skopenko
- Enhanced Classification Models for Heart Disease Prediction in Precision Medicine 265-278
  Nataliya Boyko, Iryna Dosiak
- Enhancing the Quality of Medical Services Through the QMS Medical Cloud Platform 279-291
  Igor Pavliv, Volodymyr Pasichnyk
- Design Approaches and Tools for the Implementation of a Medicinal Cocktails Recommendation System 292-302
  Sviatoslav Tyskyi, Solomiia Liaskovska, Andy T. Augousti
- Teaching Assistant Robots in Various Fields: Natural Sciences, Medicine and Specific Non-Deterministic Conditions 303-309
  Roman Hasko, Oleksandra Hasko, Hakan Kutucu
- Genome Compression Using Program Synthesis 310-321
  Denys Maletskyi, Volodymyr Shymanskyi
- A Hybrid Two-ML-based Classifier to Predict the Survival of Kidney Transplants One Month after Transplantation 322-331
  Ivan Izonin, Yaroslav Tolstyak, Veronika Kachmar, Roman Tkachenko, Mariia Rashkevych, Valentyna Chopyak
- Multimodal Medical Data Learning Approaches for Digital Healthcare 332-337
  Oleh Basystiuk, Nataliia Melnykova
- Investigation of PNN Optimization Methods to Improve Classification Performance in Transplantation Medicine 338-345
  Myroslav Havryliuk, Nazarii Hovdysh, Yaroslav Tolstyak, Valentyna Chopyak, Natalya Kustra

2023-11-23: submitted by Ivan Izonin, metadata incl. bibliographic data published under Creative Commons CC0
2024-01-07: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|