Ryszard Tadeusiewicz

Professor

AGH University of Science and Technology

Poland

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Ryszard Tadeusiewicz is a Professor at AGH University of Science and Technology in Poland. His research focuses on advanced computational methods in medical imaging and AI-driven applications, including deep learning for medical diagnostics and therapeutic applications. Recent publications include work on chitosan-based scaffolds for cartilage regeneration, automated disease classification using deep learning, and innovative approaches in mental health classification.

Ryszard Tadeusiewicz

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Articles (23)

Advancements in chitosan-based scaffolds for chondrogenic differentiation and knee cartilage regeneration: current trends and future perspectives

An off-policy deep reinforcement learning-based active learning for crime scene investigation image classification

Automated classification of thyroid disease using deep learning with neuroevolution model training

Automatic liver tumor segmentation of CT and MRI volumes using ensemble ResUNet-InceptionV4 model

A pilot study on AI-driven approaches for classification of mental health disorders

Brain MRI detection and classification: Harnessing convolutional neural networks and multi-level thresholding

EO-CNN: Equilibrium Optimization-Based hyperparameter tuning for enhanced pneumonia and COVID-19 detection using AlexNet and DarkNet19

Semi-supervised generative adversarial networks for improved colorectal polyp classification using histopathological images

Significance of physiological signal thresholds in the early diagnosis of simulator sickness

Application of Kronecker convolutions in deep learning technique for automated detection of kidney stones with coronal CT images

A fuzzy interval model for assessing patient status and treatment effectiveness using blood morphology

A new super resolution Faster R-CNN model based detection and classification of urine sediments

Design of a planting module for an automatic device for forest regeneration

ECG-COVID: An end-to-end deep model based on electrocardiogram for COVID-19 detection

SCovNet: a skip connection-based feature union deep learning technique with statistical approach analysis for the detection of COVID-19

AuCFSR: Authentication and Color Face Self-Recovery Using Novel 2D Hyperchaotic System and Deep Learning Models

Constant Q–transform–based deep learning architecture for detection of obstructive sleep apnea

A hybrid approach of a deep learning technique for real–time ECG beat detection

A novel end-to-end deep learning approach for cancer detection based on microscopic medical images

BAED: a secured biometric authentication system using ECG signal based on deep learning techniques

Book review "Process maturity of hospitals and the quality of medical services" by Beata Detyna

Cancelable ECG biometric based on combination of deep transfer learning with DNA and amino acid approaches for human authentication

EEG based alcoholism detection by oscillatory modes decomposition second order difference plots and machine learning

Collaborators (9)

Paweł Pławiak

Shady Mohamed

Antoni Wilinski

Marek Danielak

Ewa Stodolak-Zych

Florian Adamczyk

Jacek Wojciechowski

Mohamed Hammad

Mariam Zomorodi

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