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 ...
ascopubs.org

Prediction of Patients With High-Risk Osteosarcoma on the Basis of XGBoost Algorithm Using Transcriptome and Methylation Data From SGH-OS Cohort

Benefits of Combining Circulating Tumor DNA With Tissue and Longitudinal Circulating Tumor DNA Genotyping in Advanced Solid Tumors: SCRUM-Japan MONSTAR-SCREEN-1 Study Osteosarcoma (OS) is the most ...
Psychology Today

New AI Tool Detects Autism Early in Toddlers

Scientists have developed a new artificial intelligence (AI) diagnostic tool that can help identify autism risk in toddlers. A new study shows how AI machine learning can predict Autism Spectrum ...
syncedreview

Tree Boosting With XGBoost – Why Does XGBoost Win “Every” Machine Learning Competition?

Tree boosting has empirically proven to be efficient for predictive mining for both classification and regression. For many years, MART (multiple additive regression trees) has been the tree boosting ...