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 ...
GitHub

EEG Functional Connectivity Analysis Using Machine Learning and Graph Neural Networks

This repository presents an end-to-end computational neuroscience project focused on the analysis of EEG functional connectivity using both classical Machine Learning (ML) and Graph Neural Networks ...
GitHub

DFU — Diabetic Foot Ulcer Wagner Grading

Ordinal regression for diabetic foot ulcer severity grading (Wagner 0–5) using ConvNeXt-Tiny with CORN (Conditional Ordinal Regression for Neural networks), two-stage inference, and unsupervised ...
The Lancet

Real-time risk prediction model for sepsis in patients with acute gastrointestinal bleeding: development and multicenter validation of a dynamic monitoring tool

bEmergency Department, Qilu Hospital of Shandong University (Qingdao), Qingdao, China cEmergency Department, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China ...
The Lancet

Prediction of hypertension and restenosis under guideline-directed management in aortic coarctation: development and validation of machine-learning models

aInstitute of Computer-Assisted Cardiovascular Medicine, Deutsches Herzzentrum der Charité Augustenburger Platz 1, 13353 Berlin, Germany bDepartment of Congenital Heart Disease – Pediatric Cardiology, ...