Nature

Development and validation of interpretable machine learning models to predict distant metastasis and prognosis of muscle-invasive bladder cancer patients

Muscle-Invasive Bladder Cancer (MIBC) is a more aggressive disease than non-muscle-invasive bladder cancer (NMIBC), with greater chances of metastasis. We sought to develop machine learning (ML) ...
Nature

Development and validation of a machine learning model for predicting mortality risk in veno-arterial extracorporeal membrane oxygenation patients

This study aims to develop and validate a machine learning-based mortality risk prediction model for V-A ECMO patients to improve the precision of clinical decision-making. This multicenter ...
ascopubs.org

Development of Machine Learning Systems to Predict Cancer-Related Symptoms With Validation Across a Health Care System

Enhancing Readability of Lay Abstracts and Summaries for Urologic Oncology Literature Using Generative Artificial Intelligence: BRIDGE-AI 6 Randomized Controlled Trial We trained and tested ML systems ...
Technology Networks

Predictive Modeling for Compound Prioritization

Explore predictive modeling for compound prioritization, including in silico screening, toxicology models, and lead selection ...
ascopubs.org

Ensuring Reliability of Curated Electronic Health Record–Derived Data: The Validation of Accuracy for Large Language Model–/Machine Learning–Extracted Information and ...

Early-Stage Breast Cancer in Women Younger Than 50 Years: Comparing American Joint Committee on Cancer Anatomic and Prognostic Stages With Partitioning Around Medoids Clusters in SEER Data Large ...