AI Medical Compendium

Prediction of Retinopathy of Prematurity and Treatment in Very Low Birth Weight Infants Using Machine Learning on Nationwide Non-Imaging Clinical Data.

Neonatology Jan 19, 2026

INTRODUCTION: Retinopathy of prematurity (ROP) remains a leading cause of preventable blindness in preterm infants. This study aimed to develop machine learning (ML) models using non-imaging clinical data to predict ROP, severe ROP (sROP), and treate... read more

Integrative Image Processing Framework for Enhanced Detection of Leprosy-Associated Chronic Wounds.

The international journal of lower extremity wounds Jan 19, 2026

Automated leprosy chronic wound analysis from smartphone-acquired images remains hindered by uneven illumination, indistinct lesion margins, and poor spatial-textural integration. The CO-WinF framework introduces three specialized modules: AINCE, whi... read more

Morphometric analysis and its application in lupus nephritis: a systematic review.

Journal of histotechnology Jan 19, 2026

Lupus nephritis (LN) is a severe manifestation of systemic lupus erythematosus (SLE), characterized by marked histological heterogeneity and high interobserver variability in the evaluation of renal biopsies. Digital morphometry has emerged as an obj... read more

Developing a Quality Evaluation Index System for Health Conversational Artificial Intelligence: Mixed Methods Study.

Journal of medical Internet research Jan 19, 2026

BACKGROUND: Effective communication is fundamental to health care; however, demographic transitions and a widening global health workforce gap are intensifying the imbalance between service demand and resource supply. Health conversational artificial... read more

Humans Artificial Intelligence Delphi Technique

Model uncertainty estimates for deep learning mammographic density prediction using ordinal and classification approaches.

Biomedical physics & engineering express Jan 19, 2026

Mammographic density is associated with the risk of developing breast cancer and can be predicted using deep learning methods. Model uncertainty estimates are not produced by standard regression approaches but would be valuable for clinical and resea... read more

Machine Learning Prediction Models for Preeclampsia: Systematic Review and Meta-Analysis.

Journal of medical Internet research Jan 19, 2026

BACKGROUND: Preeclampsia is a severe hypertensive disorder with rising global prevalence. While machine learning (ML) models for predicting preeclampsia are increasingly published, existing evidence shows high heterogeneity, and the distinction betwe... read more

Humans Machine Learning Pregnancy Female Pre-Eclampsia

OCT-Derived Virtual Fractional Flow Reserve Associated With 1-Year Outcomes After PCI in ACS Patients.

Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions Jan 19, 2026

BACKGROUND: Despite PCI, many acute coronary syndrome (ACS) patients experience major adverse cardiovascular events (MACE). Angiography is limited, and fractional flow reserve (FFR) is restricted by cost and specialized resource requirements. Optical... read more

Machine Learning for Predicting Malignant Transformation in Actinic Cheilitis: A Prognostic Support System Based on Demographic and Clinical Descriptors.

Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology Jan 19, 2026

OBJECTIVE: This study aimed to develop and evaluate Machine Learning models to predict the malignant transformation (MT) in patients with actinic cheilitis (AC). METHODS: Three hundred forty patients diagnosed with AC (322 in the no MT group, and 18 ... read more

Model-agnostic linear-memory online learning in spiking neural networks.

Nature communications Jan 19, 2026

Spiking neural networks (SNNs) offer a promising paradigm for modeling brain dynamics and developing neuromorphic intelligence, yet an online learning system capable of training rich spiking dynamics over long horizons with low memory footprints has ... read more

Predictive design of stretchable electrodes with strain-insensitive performance via robotics- and machine learning-integrated workflow.