A machine learning model using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD than traditional tools. Heart failure is one of the most serious and ...
Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...
A new study published in the Journal of Neurology1 detailed the development of 2 machine learning–based tools that were able ...
Machine learning models can predict the risk for developing moderate-to-severe persistent asthma and allergic rhinitis in ...
This study highlights the potential for using deep learning methods on longitudinal health data from both primary and ...
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 ...
Mount Sinai researchers have created an analytic tool using machine learning that can predict cardiovascular disease risk in patients with obstructive sleep apnea ...
Morning Overview on MSN
Many AI disease-risk models trained on flawed health data
Somewhere on Kaggle, the open data platform where anyone can upload a spreadsheet and call it a dataset, two files labeled as ...
Artificial intelligence (AI) is positioned to make a major impact on almost every industry, including healthcare. A new study suggests that machine learning models can more quickly and affordably ...
Results that may be inaccessible to you are currently showing.
Hide inaccessible results