AI Medical Compendium Topic:
ROC Curve

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Glaucoma diagnosis using multi-feature analysis and a deep learning technique.

Scientific reports
In this study, we aimed to facilitate the current diagnostic assessment of glaucoma by analyzing multiple features and introducing a new cross-sectional optic nerve head (ONH) feature from optical coherence tomography (OCT) images. The data (n = 100 ...

Automated detection of acute appendicular skeletal fractures in pediatric patients using deep learning.

Skeletal radiology
OBJECTIVE: We aimed to perform an external validation of an existing commercial AI software program (BoneView™) for the detection of acute appendicular fractures in pediatric patients.

Prediction models for early diagnosis of actinomycotic osteomyelitis of the jaw using machine learning techniques: a preliminary study.

BMC oral health
BACKGROUND: This study aimed to develop and validate five machine learning models designed to predict actinomycotic osteomyelitis of the jaw. Furthermore, this study determined the relative importance of the predictive variables for actinomycotic ost...

Dynamic Mortality Risk Predictions for Children in ICUs: Development and Validation of Machine Learning Models.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies
OBJECTIVES: Assess a machine learning method of serially updated mortality risk.

Optimizing discharge after major surgery using an artificial intelligence-based decision support tool (DESIRE): An external validation study.

Surgery
BACKGROUND: In the DESIRE study (Discharge aftEr Surgery usIng aRtificial intElligence), we have previously developed and validated a machine learning concept in 1,677 gastrointestinal and oncology surgery patients that can predict safe hospital disc...

Monitoring Approaches for a Pediatric Chronic Kidney Disease Machine Learning Model.

Applied clinical informatics
OBJECTIVE: The purpose of this study is to evaluate the ability of three metrics to monitor for a reduction in performance of a chronic kidney disease (CKD) model deployed at a pediatric hospital.

Leveraging machine learning tools and algorithms for analysis of fruit fly morphometrics.

Scientific reports
Analysis of landmark-based morphometric measurements taken on body parts of insects have been a useful taxonomic approach alongside DNA barcoding in insect identification. Statistical analysis of morphometrics have largely been dominated by tradition...

Development and Validation of an Explainable Machine Learning Model for Major Complications After Cytoreductive Surgery.

JAMA network open
IMPORTANCE: Cytoreductive surgery (CRS) is one of the most complex operations in surgical oncology with significant morbidity, and improved risk prediction tools are critically needed. Machine learning models can potentially overcome the limitations ...

A Hybrid Approach for Approximating the Ideal Observer for Joint Signal Detection and Estimation Tasks by Use of Supervised Learning and Markov-Chain Monte Carlo Methods.

IEEE transactions on medical imaging
The ideal observer (IO) sets an upper performance limit among all observers and has been advocated for assessing and optimizing imaging systems. For general joint detection and estimation (detection-estimation) tasks, estimation ROC (EROC) analysis h...

Understanding land degradation induced by gully erosion from the perspective of different geoenvironmental factors.

Journal of environmental management
Complex interrelationships between landscape-level geoenvironmental factors and natural phenomena have rendered land degradation control measures ineffective. For control to be effective, this study argues that the interactions between different geoe...