A machine learning model slightly outperforms a conventional regression model at predicting which children hospitalized for asthma will be readmitted within 180 days.

Machine learning can predict the risk for developing asthma and allergic rhinitis in children diagnosed with early-life atopic dermatitis.

A predictive model for psoriasis relapse risk demonstrates moderate performance, according to a study published online April ...

Whether estimating the probability that a disease is present or forecasting risk of deterioration,1 readmission,2 or death,3 most contemporary clinical artificial intelligence (AI) systems are ...

Discover how machine learning asthma prediction can identify high-risk children early and support personalised care ...

This study highlights the potential for using deep learning methods on longitudinal health data from both primary and ...

A new update from the American Gastroenterological Association (AGA) urges stronger prevention efforts and better ...

The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

Somewhere on Kaggle, the open data platform where anyone can upload a spreadsheet and call it a dataset, two files labeled as ...

Dubious data sets are being used to train artificial-intelligence models that are designed to predict people’s risk of stroke and diabetes, researchers report in a preprint 1 on medRxiv. Some of the ...

Omalizumab effectively improves quality of life in patients with moderate-to-severe perennial allergic rhinitis (PAR) uncontrolled by conventional medications. However, the duration of its efficacy ...

Mount Sinai researchers have created an analytic tool using machine learning that can predict cardiovascular disease risk in patients with obstructive sleep apnea ...