A Federated Learning-Based Approach for Classification of Histopathology Images
Year: 2024
Type: conference-paper
Abstract: Nowadays, deep learning and machine learning methods are widely used in computer-aided diagnosis. In healthcare studies, they provide reliable and effective solutions for diagnosis and detection. However, important problems such as ensuring the privacy of patient data arise in these studies. In this study, the HAM10000 dataset was used, and the classification of histopathological images was conducted using the Federated Learning (FL) approach and deep learning methods to ensure data privacy and security. As a result of the tests performed, the classification accuracy rate of the proposed method was observed to be 82.04%.
Authors: Musa Yenilmez, Ilhan Aydin
Institution: Fırat University
Language: English
Topic: AI in cancer detection
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4403447374