Time-to-event is a powerful statistical approach increasingly used in sports science and medicine to examine time-to-event outcomes such as time to sports injury occurrence, career duration and ...

Introduction In 2002, hepatitis B vaccines were incorporated into China’s National Immunisation Programme (NIP). In 2009, the ...

Abstract: One advancing machine-learning-based analysis approach for multivariate time-series data is representing data as a third-order tensor and then applying dimensionality reduction (DR) methods.

Forecasting a company's sales is a crucial process that enables businesses to make informed decisions, allocate resources effectively, and plan for future growth. A sales forecast is essentially an ...

In the age of big data, surveillance systems capture vast amounts of information, but the bottleneck lies in interpretation for timely public health action. Heatstroke is a textbook example of ...

Cosmic rays are high-energy particles that constantly bombard Earth from space and are influenced by the sun's magnetic ...

Background Gender disparities in vision impairment (VI) among Chinese children and adolescents persist over time. Assessment ...

We show that, compared with surgeon predictions and existing risk-prediction tools, our machine-learning model can enhance the accuracy of the prediction of progression to death in DCD donors and ...

The predictive analytics market within the banking sector has been witnessing substantial growth in recent years, fueled by the increasing adoption of data-driven decision-making processes and the ...

Bitcoin returns and volatility are falling, leading researchers to say “values above $1 million will probably take 15 years.” ...

IIT Delhi’s 6-month programme offers faculty-led, hands-on training in Data Science, ML, Deep Learning and Generative AI, ending with a valuable certificate.

Introduction: Despite its endemic status and socioeconomic impacts, the spatial-temporal variation in rabies risk and its underlying determinants in Kazakhstan animal populations remain poorly ...