Frontiers

Numerical foundations for scalable statistical and machine learning methods

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...
Nature

ImMLPro platform for accessible machine learning and statistical analysis in digital agriculture and beyond

The integration of machine learning (ML) algorithms with statistical analysis and user-friendly interfaces has become crucial for democratizing advanced analytics across various domains, particularly ...
News Medical

Combining machine learning with statistical methods can provide accurate models for disease risk prediction

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...
Nature

Invasive and non-invasive variables prediction models for cardiovascular disease-specific mortality between machine learning vs. traditional statistics

This study examined the predictive performance of cardiovascular disease (CVD)-specific mortality using traditional statistical and machine learning models with non-invasive indicators, and assessed ...
techtimes

The Role of Assumptions in Statistical Model Selection

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...
Quanta Magazine

What Is Machine Learning?

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...