The process of matching patients with suitable clinical trials is essential for advancing
medical research and providing optimal care. However, current approaches face challenges …

Explainable machine learning significantly improves the transparency of deep neural
networks~(DNN). However, existing work is constrained to explaining the behavior of …

Detailed phenotype information is fundamental to accurate diagnosis and risk estimation of
diseases. As a rich source of phenotype information, electronic health records (EHRs) …

Organ transplant is the essential treatment method for some end-stage diseases, such as
liver failure. Analyzing the post-transplant cause of death (CoD) after organ transplant …

Parkinson's disease (PD), a neurodegenerative disorder, often manifests as speech and
voice dysfunction. While utilizing voice data for PD detection has great potential in clinical …

Background Retinal imaging, including fundus autofluorescence (FAF), strongly depends on
the clearness of the optical media. Lens status is crucial since the ageing lens has both light …

Identifying patient cohorts is fundamental to numerous healthcare tasks, including clinical
trial recruitment and retrospective studies. Current cohort retrieval methods in healthcare …

Explainable machine learning significantly improves the transparency of deep neural
networks. However, existing work is constrained to explaining the behavior of individual …

Deep learning on graphs has garnered considerable attention across various machine
learning applications, encompassing social science, transportation services, and biomedical …

Clinical trials play a crucial role in the development of new treatments, yet they often
encounter significant challenges in patient recruitment and retention, impeding the …