Improved Architecture and the Synthesis Algorithm for Bithreshold Neural Network Classifier DOI
Vladyslav Kotsovsky, Anatoliy Batyuk

Опубликована: Окт. 19, 2023

The model of the 3-layer feed-forward neural network is introduced whose first hidden layer consists bithreshold neurons and other layers—of single-threshold ones. proposed capable to recognize compact finite set patterns using a union hyperrectangular decision regions in n-dimensional space. We design multiclass classifier on base such network, propose synthesis algorithm for it estimate networks size as well time computations. simulation results demonstrate that application additional improves accuracy classification.

Язык: Английский

Automated biomedical measurements analysis: Innovative models based on machine learning for predicting laboratory results in nephrology DOI
Dawid Pawuś, Tomasz Porażko, Szczepan Paszkiel

и другие.

Expert Systems with Applications, Год журнала: 2025, Номер unknown, С. 126568 - 126568

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Automation and Decision Support in Nephrology: An Expert System Based on AI and ML for the Assessment, Treatment, and Management of Focal Segmental Glomerulosclerosis DOI Creative Commons
Dawid Pawuś, Tomasz Porażko, Szczepan Paszkiel

и другие.

Applied Sciences, Год журнала: 2025, Номер 15(3), С. 1044 - 1044

Опубликована: Янв. 21, 2025

Focal segmental glomerulosclerosis (FSGS) presents significant challenges in diagnosis, treatment, and management due to its complex etiology clinical variability. Traditional approaches often rely on clinician judgment are prone inconsistencies. This study introduces an advanced expert system integrating Artificial Intelligence (AI) with Machine Learning (ML) support nephrologists assessing, treating, managing FSGS. The proposed features a modular design comprising diagnostic workflows, risk stratification, treatment guidance, outcome monitoring modules. By leveraging ML algorithms data, the offers personalized, data-driven recommendations, enhancing decision-making patient care. evaluation demonstrates system’s efficacy reducing errors optimizing pathways. These findings underscore potential of AI-driven tools transforming nephrology practice improving outcomes for FSGS patients.

Язык: Английский

Процитировано

0

Novel Systems Based on Artificial Intelligence and Numerical Algorithms for Predicting Laboratory Results: A Comparative Study of Original Automatic Prediction Model with Advances in the Field DOI
Dawid Pawuś, Tomasz Porażko, Szczepan Paszkiel

и другие.

Lecture notes in networks and systems, Год журнала: 2025, Номер unknown, С. 113 - 131

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Multithreshold Neural Units for Multiclass Classification DOI
Vladyslav Kotsovsky,

Tetiana Lisovska,

Volodymyr Sabadosh

и другие.

Опубликована: Май 15, 2024

Язык: Английский

Процитировано

0

Investigation of Elderly Patient Actimetries for Night Sleep/Wake Phases Prediction DOI

Radjia Zard,

Jaouher Ben Ali,

Nacira Laamiri

и другие.

2022 8th International Conference on Control, Decision and Information Technologies (CoDIT), Год журнала: 2024, Номер 15, С. 2633 - 2638

Опубликована: Июль 1, 2024

Язык: Английский

Процитировано

0

Improved Architecture and the Synthesis Algorithm for Bithreshold Neural Network Classifier DOI
Vladyslav Kotsovsky, Anatoliy Batyuk

Опубликована: Окт. 19, 2023

The model of the 3-layer feed-forward neural network is introduced whose first hidden layer consists bithreshold neurons and other layers—of single-threshold ones. proposed capable to recognize compact finite set patterns using a union hyperrectangular decision regions in n-dimensional space. We design multiclass classifier on base such network, propose synthesis algorithm for it estimate networks size as well time computations. simulation results demonstrate that application additional improves accuracy classification.

Язык: Английский

Процитировано

0