BIOENGINEER

Predicting the incidence of type 2 diabetes using FINDRISC and machine learning approaches: evidence from a population-based cohort

In a population-based cohort of 8,859 adults followed for six years, component-level machine learning models showed higher ...

Machine learning isn't just about making predictions: 5 steps learned from housing price prediction [Practical Summary]

"Which products will sell, and how many, next month?""How many hours will this task take?""Can we identify conditions prone ...
BIOENGINEER

Machine Learning Framework Delivers Reliable Agronomic Predictions for Precision Farming

Researchers in India have developed an optimized machine learning framework combining preprocessing, feature selection and ...
Nature

Machine learning articles from across Nature Portfolio

Researchers developed NiCLIP, an AI model that decodes cognitive tasks, concepts, and domains from brain activation patterns. Trained on over 23,000 papers, NiCLIP excels at group-level decoding, ...
Eos

Using Machine Learning Techniques for Polar Vortex Predictions

A new model accurately reproduces aspects of polar vortex behavior, extracting indicators of imminent vortex collapse and accompanying frigid weather in North America and Europe.

[#16] How to show it to machine learning: Feature engineering for stock price prediction

In this note, with the theme of can we beat a '99-point' index investment? I, a company employee who has dabbled a bit in ...
Neurology Advisor

Sex-Specific Machine Learning Models Predict 10-Year Dementia Risk

Machine learning models utilizing cardiovascular and lifestyle factors can accurately predict the 10-year risk of dementia in both men and women.
Notebookcheck

AI improves weather forecasting: Researchers double reliability for forecasts 2 to 6 weeks ahead

Weather forecasting is difficult, and predictions often become less accurate the further into the future they reach. Using a ...
Nature

Machine Learning Techniques for Streamflow Forecasting articles from across Nature Portfolio

A precise streamflow forecast is crucial in hydrology for flood alerts, water quantity and quality management, and disaster preparedness. Machine learning (ML) techniques are commonly employed for ...