Scientific Research Publishing

A Multimodal Machine-Learning Framework for Predicting Lithium-Associated Renal Dysfunction from Synthetic Biomarker Trajectories ()

Long-term lithium therapy remains the most effective maintenance treatment for bipolar disorder, yet it poses a significant risk of progressive renal impairment in a subset of patients. Early ...

Deep learning model predicts how individual cells influence disease outcomes

A computational method called scSurv, developed by researchers at Institute of Science Tokyo, links individual cells to patient outcomes using widely available bulk RNA sequencing data. The approach ...
The Lancet

A predictive atlas of disease onset from retinal fundus photographs: a modelling study using data from population-based cohorts

We present one of the first comprehensive evaluations of predictive information derived from retinal fundus photographs, illustrating the potential and limitations of readily accessible and low-cost ...
Frontiers

Trustworthy AI for Medical Imaging: Advanced Modeling and Clinical Prediction

Medical imaging is a process of visualizing the tissues, organs and structure of the human body to diagnose, monitor, and treat medical conditions. It plays ...
Scientific Research Publishing

A Lightweight Self-Supervised Representation Learning Framework for Depression Risk Profiling from Synthetic Daily Behavioural Trajectories ()

Detecting behavioural signatures of depression from everyday digital traces is a central challenge in computational psychiatry. Real-world datasets from smartphones and wearables often suffer from ...