The Lancet

When to and when not to use machine learning in risk prediction models

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...
Scientific Research Publishing

A Wind Speed Prediction Model Based on Machine Learning in Guyuan Area ()

1 School of Atmospheric Sciences, Chengdu University of Information and Technology, Chengdu, China. 2 Guyuan Meteorological Bureau, Guyuan, China. 3 Jilin Provincial Institute of Meteorological ...
Frontiers

NeoTImmuML: a machine learning-based prediction model for human tumor neoantigen immunogenicity

Tumor neoantigens possess high specificity and immunogenicity, making them crucial targets for personalized cancer immunotherapies such as mRNA vaccines and T-cell therapies. However, experimental ...
IEEE

Machine Learning Techniques to Improve the Cognitive Workload Classification Using Multimodal Sensors’ Data

Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...
BMJ

Predicting cardiovascular events from routine mammograms using machine learning

10 The George Institute for Global Health, School of Public Health, Imperial College London, London, UK Background Cardiovascular risk is underassessed in women. Many women undergo screening ...
Frontiers

VAE deep learning model with domain adaptation, transfer learning and harmonization for diagnostic classification from multi-site neuroimaging data

The acquisition sites include: CALTECH, California Institute of Technology; CMU, Carnegie Mellon University; KKI, Kennedy Krieger Institute; LEUVEN, University of Leuven; MAX, Ludwig Maximilians ...
GitHub

dinraj910/Iris-Flower-Classification

The Iris Flower Classification project is an interactive web application that predicts the species of Iris flowers based on their physical characteristics. This project demonstrates the complete ...
IEEE

Intelligent Human Gait Phase Classification Using Machine Learning Models

Abstract: Advancements in machine learning (ML) have facilitated the prediction of key aspects of human locomotion, particularly in identifying subject gait trajectories essential for recognizing ...