Prediction of future clinical events (eg, disease diagnoses) is an important machine learning
task in healthcare informatics research. In this work, we propose a deep learning approach …

Advances in systems immunology, such as new biomarkers, offer the potential for highly
personalized immunosuppression regimens that could improve patient outcomes. In the …

Chronic kidney disease (CKD) is a global health issue, affecting more than 10% of the
worldwide population. The current approach for formal diagnosis and prognostication of …

Kidney diseases form part of the major health burdens experienced all over the world.
Kidney diseases are linked to high economic burden, deaths, and morbidity rates. The great …

One of the main problems that affect patients in dialysis therapy who are on the waiting list to
receive a kidney transplant is predicting their survival time if they do not receive a transplant …

Background Censorship is the primary challenge in survival modeling, especially in human
health studies. The classical methods have been limited by applications like Kaplan–Meier …

Background The currently available prediction models, such as the Cox model, were too
simplistic to correctly predict the outcome of gastric adenocarcinoma patients. This study …

Facial palsy evaluation (FPE) aims to assess facial palsy severity of patients, which plays a
vital role in facial functional treatment and rehabilitation. The traditional manners of FPE are …

Due to the shortage of available organs compared to the number of patients on waitlists, the
organ allocation process has always been challenging and calls for an equitable and …

In the field of medicine, decision-making has traditionally been carried out based on the best
available scientific information and the experience of specialists using data found in analog …