A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

NOTE. These are the baseline variables determined at treatment completion and included in the analysis. Abbreviations: CIN, cervical intraepithelial neoplasia; COPD, chronic obstructive pulmonary ...

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

Among patients with chronic noncancer pain, a novel machine learning model effectively predicts opioid use disorder risk.

Data is fundamental to hydrological modeling and water resource management; however, it remains a major challenge in many ...

Musculoskeletal (MSK) conditions drive a large share of global pain, disability, and lost productivity. Rehabilitation can be effective, but outcomes vary ...

Recent study reveals machine learning's potential in predicting the strength of carbonated recycled concrete, paving the way ...

A new technical paper titled “Estimating Voltage Drop: Models, Features and Data Representation Towards a Neural Surrogate” was published by researchers at KTH Royal Institute of Technology and ...

Performance evaluation of an AI-powered system for clinical trial eligibility using mCODE data standards. ATheNa-Breast: A real-world pilot of an artificial intelligence (AI) chatbot using therapy ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...