1. A group of five machine learning algorithms identified whether a patient was a suitable candidate for corneal refractive surgery with 93.4 percent accuracy, a level equal to that of expert ...
Optimizing hospital patient safety: Machine learning model enhances early warning system performance
In a recent article published in eClinicalMedicine, researchers propose a novel predictive model based on machine learning (ML) for the early prediction of adverse events (AEs), such as cardiac arrest ...
Patients undergoing radiotherapy (RT) or chemoradiotherapy (CRT) may require emergency department evaluation or hospitalization. Early identification may direct preventative supportive care, improving ...
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