Researchers successfully developed a machine learning-based method for predicting symptom deterioration in patients with cancer.

Please provide your email address to receive an email when new articles are posted on . An AI model correctly identified 22 of 31 adults as having acromegaly strictly based on voice recordings. The ...

A tool combining CV risk score (CVRS) and coronary artery calcium score (CACS) facilitates stratification of patients with COPD at risk for MACE.

The CT-based whole-lung radiomic nomogram accurately identifies AECOPD and offers a robust tool for clinical diagnosis and treatment planning.

The models were developed using linear and nonlinear algorithms, predicting survival, nonlocal failure, radiation-induced liver disease, and lymphopenia from baseline patient and treatment parameters.

Development of an Electronic Health Record–Based Algorithm for Predicting Lung Cancer Screening Eligibility in the Population-Based Research to Optimize the Screening Process Lung Research Consortium ...