This project demonstrates medical time series analysis using deep learning for heart rate prediction. It provides a comprehensive framework for: medical-time-series-analysis/ ├── src/ # Source code │ ...

Methods: This retrospective longitudinal time-series study used a big data-driven interpretable machine learning approach to analyze global multifaceted data across 38 countries from pandemic onset ...

For the 29 teams who do not win the World Series, the offseason typically begins with an assessment of how they fell short. The champions, naturally, have more to say about what it takes to win a ...

How will this year's World Series play out? Using the Dynasty League Baseball online simulation, USA TODAY Sports' Steve Gardner and DLB designer Mike Cieslinski will pre-play each game to provide ...

What a start to the 2025 World Series for the Toronto Blue Jays. The Blue Jays came out swinging in Game 1, riding a nine-run sixth inning to an 11-4 victory over the Los Angeles Dodgers in front of a ...

Abstract: Traditional machine learning approaches for biomedical time series analysis face fundamental limitations when integrating the heterogeneous data types essential for comprehensive clinical ...

A significant development is set to transform AI in healthcare. Researchers at Stanford University, in collaboration with ETH Zurich and tech leaders including Google Research and Amazon, have ...

Objectives To evaluate temporal trends in the epidemiology of hip osteoarthritis (OA) in the USA from 1990 to 2019, with stratification by sex and geographic region. Design Cross-sectional time-series ...

A Deep Learning Framework for Using Search Engine Data to Predict Influenza-Like Illness and Distinguish Epidemic and Nonepidemic Seasons: Multifeature Time Series Analysis ...

Time-series data—measurements collected at regular intervals, like stock prices or traffic flows—has become a key driver of intelligent decision-making systems across industries. From medical ...