Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

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

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 ...

IPDsim: An interpretable model to assess individual clinical antagonism in combination therapies for cancers. Model performance across development and validation cohorts.

Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.

The authors analyze the interest rate risk in the banking book regulations, arguing that financial institutions must develop robust models for forecasting ...

The severity of symptoms in posttraumatic stress disorder (PTSD) varies greatly across individuals in the first year after trauma and it remains difficult to predict whether someone might worsen, ...

A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications after stem cell and bone marrow transplants, according to new research ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 ...