British Journal of Ophthalmology

Identifying patients with poor visual outcomes after primary rhegmatogenous retinal detachment surgery using machine learning

Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...

Data Scientist Ke Zhang’s Research Explores Homomorphic Encryption for Privacy-Preserving Marketing

A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...

Machine Learning Is Enabling A New Era For Precision Medicine And Pharmacogenomics

Medicine is rapidly evolving from statistical, evidence-based approaches to predictive, genotype-directed care, driven by ...

Wastewater management reverses widespread freshwater deoxygenation in China

Freshwater ecosystems worldwide have been suffering from declining oxygen levels—a trend known as deoxygenation—that ...

New algorithm identifies disease-linked changes in cells without prior training

A new algorithm could drive breakthroughs in understanding cancer, Alzheimer's disease and other potentially fatal conditions ...
STAT

Your sepsis algorithm shouldn’t require a time machine

You’re reading the web edition of STAT’s AI Prognosis newsletter, our subscriber-exclusive guide to artificial intelligence in health care and medicine. Sign up to get it delivered in your inbox every ...
IEEE

Exploration of Stacking Ensemble Learner (SEL) Modeling with XGBoost and SVM algorithms on Predicting Stock Price

Abstract: The fluctuating characteristics of stock prices indicate high stock market volatility. Therefore, a method is needed that can overcome these problems by providing more accurate predictions ...
IEEE

Machine Learning based Hybrid Technique for Cyber Attack Prediction in VANET

Abstract: This paper introduces a hybrid machine learning-based framework that combines the Random Forest and the XGBoost machine learning algorithms for effective prediction of cyber-attacks in ...