AIMC Topic: ROC Curve

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Machine learning-assisted prediction of trabeculectomy outcomes among patients of juvenile glaucoma by using 5-year follow-up data.

Indian journal of ophthalmology
OBJECTIVE: To develop machine learning (ML) models, using pre and intraoperative surgical parameters, for predicting trabeculectomy outcomes in the eyes of patients with juvenile-onset primary open-angle glaucoma (JOAG) undergoing primary surgery.

An Improved Clinical and Genetics-Based Prediction Model for Diabetic Foot Ulcer Healing.

Advances in wound care
The goal of this investigation was to use comprehensive prediction modeling tools and available genetic information to try to improve upon the performance of simple clinical models in predicting whether a diabetic foot ulcer (DFU) will heal. We uti...

Development and validation of an electrocardiographic artificial intelligence model for detection of peripartum cardiomyopathy.

American journal of obstetrics & gynecology MFM
BACKGROUND: This study used electrocardiogram data in conjunction with artificial intelligence methods as a noninvasive tool for detecting peripartum cardiomyopathy.

Deep learning-based prediction of post-pancreaticoduodenectomy pancreatic fistula.

Scientific reports
Postoperative pancreatic fistula is a life-threatening complication with an unmet need for accurate prediction. This study was aimed to develop preoperative artificial intelligence-based prediction models. Patients who underwent pancreaticoduodenecto...

Automated Machine Learning versus Expert-Designed Models in Ocular Toxoplasmosis: Detection and Lesion Localization Using Fundus Images.

Ocular immunology and inflammation
PURPOSE: Automated machine learning (AutoML) allows clinicians without coding experience to build their own deep learning (DL) models. This study assesses the performance of AutoML in detecting and localizing ocular toxoplasmosis (OT) lesions in fund...

Development of a deep learning model that predicts critical events of pediatric patients admitted to general wards.

Scientific reports
Early detection of deteriorating patients is important to prevent life-threatening events and improve clinical outcomes. Efforts have been made to detect or prevent major events such as cardiopulmonary resuscitation, but previously developed tools ar...

An advanced machine learning method for simultaneous breast cancer risk prediction and risk ranking in Chinese population: A prospective cohort and modeling study.

Chinese medical journal
BACKGROUND: Breast cancer (BC) risk-stratification tools for Asian women that are highly accurate and can provide improved interpretation ability are lacking. We aimed to develop risk-stratification models to predict long- and short-term BC risk amon...

Deep Learning based Retinal Vessel Caliber Measurement and the Association with Hypertension.

Current eye research
PURPOSE: To develop a highly efficient and fully automated method that measures retinal vessel caliber using digital retinal photographs and evaluate the association between retinal vessel caliber and hypertension.

Predicting extremely low body weight from 12-lead electrocardiograms using a deep neural network.

Scientific reports
Previous studies have successfully predicted overweight status by applying deep learning to 12-lead electrocardiogram (ECG); however, models for predicting underweight status remain unexplored. Here, we assessed the feasibility of deep learning in pr...