We show that, compared with surgeon predictions and existing risk-prediction tools, our machine-learning model can enhance ...
Wearables, Mobile Health (m-Health), Real-Time Monitoring Share and Cite: Alqarni, A. (2025) Analysis of Decision Support ...
Humn Health offers an AI-based healthcare platform that uses smartphone sensors and wearable data to detect pregnancy-related risks and other health symptoms.
For many ILD patients, adherence to treatment and engagement with supportive therapies such as pulmonary rehabilitation can ...
Latus Bio, Inc. (Latus), a biotechnology company pioneering advances in adeno-associated virus (AAV) gene therapy, today announced a major expansion of its artificial intelligence and machine learning ...
Machine learning predicted ASD using sex-specific prenatal/perinatal factors: pregestational BMI, socioeconomic status, maternal age, and more.
The convergence of technology and healthcare is changing the way we approach chronic conditions like diabetes. Artificial Intelligence (AI) is ...
Background: Cardiovascular disease (CVD) is the leading cause of mortality in patients with metabolic dysfunction-associated steatotic liver disease (MASLD), yet traditional risk predictors remain ...
1 School of Nursing, Nanjing University of Chinese Medicine, Nanjing, China 2 Jiangsu Province Hospital of Chinese Medicine, Nanjing, China The final, formatted version of the article will be ...
Abstract: This paper presents a comprehensive study on the application of Explainable Artificial Intelligence (XAI) for diabetes risk assessment, focusing on the interpretability of machine learning ...
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