AIMC Topic: ROC Curve

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Improving sensitivity and connectivity of retinal vessel segmentation via error discrimination network.

Medical physics May 20, 2022
PURPOSE: Automated retinal vessel segmentation is crucial to the early diagnosis and treatment of ophthalmological diseases. Many deep-learning-based methods have shown exceptional success in this task. However, current approaches are still inadequat...
Image Processing, Computer-Assisted Neural Networks, Computer Retinal Vessels Algorithms ROC Curve
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Pressure Injury Prediction Model Using Advanced Analytics for At-Risk Hospitalized Patients.

Journal of patient safety May 19, 2022
OBJECTIVE: Analyzing pressure injury (PI) risk factors is complex because of multiplicity of associated factors and the multidimensional nature of this injury. The main objective of this study was to identify patients at risk of developing PI.
ROC Curve Pressure Ulcer Risk Factors Cohort Studies Humans Machine Learning
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Prediction of serious outcomes based on continuous vital sign monitoring of high-risk patients.

Computers in biology and medicine May 18, 2022
Continuous monitoring of high-risk patients and early prediction of severe outcomes is crucial to prevent avoidable deaths. Current clinical monitoring is primarily based on intermittent observation of vital signs and the early warning scores (EWS). ...
Vital Signs Oximetry ROC Curve Humans Area Under Curve Machine Learning
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Prediction of future healthcare expenses of patients from chest radiographs using deep learning: a pilot study.

Scientific reports May 18, 2022
Our objective was to develop deep learning models with chest radiograph data to predict healthcare costs and classify top-50% spenders. 21,872 frontal chest radiographs were retrospectively collected from 19,524 patients with at least 1-year spending...
Radiography Retrospective Studies Pilot Projects Deep Learning ROC Curve Humans Delivery of Health Care
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Development and validation of a meta-learner for combining statistical and machine learning prediction models in individuals with depression.

BMC psychiatry May 16, 2022
BACKGROUND: The debate of whether machine learning models offer advantages over standard statistical methods when making predictions is ongoing. We discuss the use of a meta-learner model combining both approaches as an alternative.
Neural Networks, Computer Machine Learning Depression ROC Curve Humans
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Glaucoma diagnosis using multi-feature analysis and a deep learning technique.

Scientific reports May 16, 2022
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 ...
Pilot Projects ROC Curve Retinal Ganglion Cells Tomography, Optical Coherence Cross-Sectional Studies Humans Deep Learning Glaucoma
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Automated detection of acute appendicular skeletal fractures in pediatric patients using deep learning.

Skeletal radiology May 6, 2022
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.
Retrospective Studies Female Sensitivity and Specificity Humans Algorithms Fractures, Bone Child ROC Curve Male Deep Learning
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Prediction models for early diagnosis of actinomycotic osteomyelitis of the jaw using machine learning techniques: a preliminary study.

BMC oral health May 6, 2022
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...
Early Diagnosis Osteomyelitis ROC Curve Logistic Models Humans Machine Learning
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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 May 5, 2022
OBJECTIVES: Assess a machine learning method of serially updated mortality risk.
Retrospective Studies Intensive Care Units Hospital Mortality ROC Curve Humans Child Machine Learning
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Optimizing discharge after major surgery using an artificial intelligence-based decision support tool (DESIRE): An external validation study.

Surgery May 4, 2022
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...
ROC Curve Patient Discharge Retrospective Studies Hospitalization Artificial Intelligence Machine Learning Humans
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