Models using established cardiovascular disease risk factors had satisfactory predictive performance for 5-year CVD risk in ...
Abhijeet Sudhakar develops efficient Mamba model training for machine learning, improving sequence modelling and ...
Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...
Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global ...
A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.
Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
Assessment of Circulating Tumor DNA Burden in Patients With Metastatic Gastric Cancer Using Real-World Data Endometrial cancer (EC) is the most common gynecologic cancer in the United States with ...
This study presents a transfer learning–based method for predicting train-induced environmental vibration. The method applies ...
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Mistaken correlations: Why it's critical to move beyond overly aggregated machine-learning metrics
MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...
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