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

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

Machine learning models can predict the risk for developing moderate-to-severe persistent asthma and allergic rhinitis in ...

Ionospheric delay remains a significant error source in GNSS positioning, particularly for single-frequency users and during periods of enhanced space weather ...

This study develops an ML-assisted approach for accelerating the discovery of HER electrocatalysts in multi-principal element alloys. With ultralow material costs and record-breaking electrocatalytic ...

Spatially distributed prediction of streamflow and nitrogen (N) export dynamics is essential for precision management of agricultural watersheds. To address this need, a team of researchers led by the ...

Discover how explainable AI enhances Parkinson’s disease prediction with improved accuracy and clinical interpretability.

Innovative machine learning models using routine clinical data offer superior stroke risk prediction in atrial fibrillation, ...

Multimodal Artificial Intelligence Model From Baseline Histopathology Adds Prognostic Information for Distant Recurrence Assessment in Hormone Receptor–Positive/Human Epidermal Growth Factor Receptor ...

Using Python, web scraping, and advanced algorithms, the solution aggregates real-time data from marketplaces to deliver ...