IEEE Spectrum on MSN
Machine learning system monitors patient pain during surgery
To create their contactless approach, the researchers created a machine learning algorithm capable of analyzing aspects of ...
Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...
Sharon Hewner, a professor at the University at Buffalo School of Nursing, PhD student Erica Smith, and alumna and UB nursing research associate professor Suzanne Sullivan, who is also an associate ...
Sensor data from wearable devices analyzed over five years reveals walking and posture differences that predict fall risk in Parkinson’s patients. Study: Predicting future fallers in Parkinson’s ...
Using Real-World Data for Machine-Learning Algorithms to Predict the Treatment Response in Advanced Melanoma: A Pilot Study for Personalizing Cancer Care This study aims to investigate the impact of ...
A novel machine learning system effectively stratifies emergency department use and hospitalization risk of older patients with multimorbidity who take multiple medications and provides appropriate ...
Debate continues over the role of artificial intelligence in treating mental health conditions, but new research shows that machine learning models can help predict whether a person might benefit from ...
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