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 ...

The model had an area under the receiver-operating-curve (AUC) of 0.96, with 82% sensitivity and 90% specificity, reported Gadi Miron, MD, of Charité-Universitätsmedizin Berlin in Germany, at the ...

Delirium, commonly observed in critically ill patients following intracerebral hemorrhage (ICH), is an acute neuropsychiatric disorder characterized ...

Background and objectives Delirium, commonly observed in critically ill patients following intracerebral hemorrhage (ICH), is ...