39 citations · 75 across the 10 of their papers we have counts for
10 papers
From Large Language Models to Knowledge Graphs for Biomarker Discovery in Cancer
Md. Rezaul Karim, Lina Molinas Comet, Md Shajalal +3
Domain experts often rely on most recent knowledge for apprehending and disseminating specific biological processes that help them design strategies for developing prevention and t…
Privacy-Preserving Linkage of Distributed Datasets using the Personal Health Train
Maximilian Jugl, Sascha Welten, Yongli Mou +4
With the generation of personal and medical data at several locations, medical data science faces unique challenges when working on distributed datasets. Growing data protection re…
A Biomedical Knowledge Graph for Biomarker Discovery in Cancer
Md. Rezaul Karim, Lina Molinas Comet, Oya Beyan +2
Structured and unstructured data and facts about drugs, genes, protein, viruses, and their mechanism are spread across a huge number of scientific articles. These articles are a la…
Explainable AI for Bioinformatics: Methods, Tools, and Applications
Md. Rezaul Karim, Tanhim Islam, Oya Beyan +4
Artificial intelligence (AI) systems utilizing deep neural networks (DNNs) and machine learning (ML) algorithms are widely used for solving important problems in bioinformatics, bi…
Towards General Deep Leakage in Federated Learning
Jiahui Geng, Yongli Mou, Feifei Li +4
Unlike traditional central training, federated learning (FL) improves the performance of the global model by sharing and aggregating local models rather than local data to protect…
Distributed Learning for Melanoma Classification using Personal Health Train
Yongli Mou, Sascha Welten, Yeliz Ucer Yediel +2
Skin cancer is the most common cancer type. Usually, patients with suspicion of cancer are treated by doctors without any aided visual inspection. At this point, dermoscopy has bec…