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 ...
Computer WeeklyOpinion

A deep dive into the Dell Pro Max with GB10 and NemoClaw

AI agents such as OpenClaw are turning developer workstations into always-on edge servers. We test whether the Dell Pro Max ...
Rising KashmirOpinion

Artificial Intelligence in GI Endoscopy: Advancing Precision from Detection to Decision-Making

Artificial Intelligence is transforming GI endoscopy by improving detection accuracy, enhancing diagnosis, and supporting ...
RMD Open

Development and assessment of an assisted diagnosis model using machine learning for identifying adult-onset Still’s disease in fever of unknown origin: a retrospective …

Background Adult-onset Still’s disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic ...

Wastewater management reverses widespread freshwater deoxygenation in China

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

Large tabular models excel where LLMs fail

Startup’s foundation model NEXUS tackles spreadsheets, AI’s surprising final frontier ...
IEEE

Dynamic Weighting Multi Factor Stock Selection Strategy Based on XGboost Machine Learning Algorithm

Abstract: Tree boosting is a highly effective and widely used machine learning method. A dynamic weighting multi-factor stock selection strategy based on XGBoost model is constructed. XGboost machine ...
IEEE

Assessing Machine Learning Approaches for Photovoltaic Energy Prediction in Sustainable Energy Systems

Abstract: Precise forecasting of solar power output is crucial for integrating renewable energy into power networks, improving efficiency and dependability. This study assesses the efficacy of several ...