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 ...
EurekAlert!

Multimodal machine learning framework for cardiovascular risk stratification in adult obesity

Cardiovascular diseases account for approximately 80% of all deaths caused by known medical conditions, making them the leading cause of mortality worldwide. The present study investigates the use of ...
Morning Overview on MSN

LazySlide links pathology images with RNA data using foundation models

LazySlide, a new computational tool designed to connect whole-slide pathology images with RNA sequencing data through foundation models, addresses one of the persistent bottlenecks in cancer research: ...
EurekAlert!

Multimodal machine learning model effective at predicting response to CDK4/6 inhibitors in HR-positive, HER2-negative breast cancer patients

SAN ANTONIO – A machine learning (ML) model incorporating both clinical and genomic factors outperformed models based solely on either clinical or genomic data in predicting which patients with ...
ascopubs.org

Development and real-world validation of a multi-modal machine learning model to predict response to immune checkpoint inhibitors in cancer patients.

Trends in immune-related adverse event reporting among multidisciplinary cancer programs. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not include a full ...
Devdiscourse

Multi-modal artificial intelligence can improve smart city traffic analytics

Smart city initiatives are generating vast amounts of data from sensors, cameras, mobile devices, and digital service ...