Innovative machine learning models using routine clinical data offer superior stroke risk prediction in atrial fibrillation, ...
This predictive model built on readily acquired clinical data provides encouraging results for the detection of residual disease. External validation and prospective studies implementing the model in ...
Final random-forest-based models outperformed all publicly available risk scores on internal and external test sets.
A novel staging system for cancer cachexia. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not include a full text component.
Mount Sinai researchers have created an analytic tool using machine learning that can predict cardiovascular disease risk in patients with obstructive sleep apnea ...
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How do different data preprocessing techniques affect performance of machine learning models on prediction tasks?
Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...
Using a comprehensive sample of 2585 bankruptcies from 1990 to 2019, we benchmark the performance of various machine learning models in predicting the financial distress of publicly traded US firms ...
Infinite dilution activity coefficient is a key thermodynamic parameter in solvent design for chemical processes. Although ...
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