AI Researcher Mahfuz Islam Khan Jabed Advances Ethical, Explainable AI for Workforce and Healthcare Applications

This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...

Machine learning algorithm fully reconstructs LHC particle collisions

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle collisions at the LHC. This new approach can reconstruct collisions more quickly ...
Nature

Machine Learning Approaches for Thyroid Disease Diagnosis and Prediction

Recent advances in machine learning have significantly enhanced the diagnosis and prediction of thyroid diseases. By integrating diverse algorithms including ensemble methods, neural networks, and ...
BMJ

Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...
Chromatography Online

AI/ML in Practice: Boudewijn Hollebrands on Deep Learning Models to Predict Food Peptide Retention Times

LCGC International’s interview series on the evolving role of artificial intelligence (AI)/machine learning (ML) in separation science continues with Boudewijn Hollebrands from Unilever Foods R&D, ...
Morningstar

Machine Learning Can Forecast Which Stock Factors Will Outperform

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...
Science Daily

Exploring factors affecting workers' acquisition of exercise habits using machine learning approaches

Researchers analyzed data from middle-aged workers who had received Specific Health Guidance -- a revolutionary system implemented by the Japanese Ministry of Health, Labor, and Welfare to improve ...
American Institute of Physics

Peering inside the machine learning black box for fusion experiments

Statistical insights into machine learning analysis can help researchers evaluate model performance and may even provide new physical understanding.
Semiconductor Engineering

Machine Learning-Based IR Drop Prediction Approach

A new technical paper titled “Estimating Voltage Drop: Models, Features and Data Representation Towards a Neural Surrogate” was published by researchers at KTH Royal Institute of Technology and ...
ascopubs.org

Machine learning–driven approaches for predicting T-cell–mediated immunity and beyond.

Effect of KROS 101, a small molecule GITR ligand agonist, on T effector cells, T reg cells and intratumoral CD8 T cell cytotoxicity. Phase 1 study of DK210 (EGFR), a tumor-targeted IL2 x IL10 dual ...

Quantum reservoir computing peaks at the edge of many-body chaos, study suggests

Reservoir computing is a promising machine learning-based approach for the analysis of data that changes over time, such as weather patterns, recorded speech or stock market trends. Classical ...