AIMC Topic:
ROC Curve

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Preoperative prediction of postoperative urinary retention in lumbar surgery: a comparison of regression to multilayer neural network.

Journal of neurosurgery. Spine Sep 10, 2021
OBJECTIVE: Postoperative urinary retention (POUR) is a common complication after spine surgery and is associated with prolongation of hospital stay, increased hospital cost, increased rate of urinary tract infection, bladder overdistention, and auton...
Spinal Diseases Neural Networks, Computer Machine Learning Predictive Value of Tests Retrospective Studies Lumbar Vertebrae Urinary Retention Humans Postoperative Complications ROC Curve Regression Analysis Aged Female Adult Reproducibility of Results Male Risk Factors Middle Aged
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Geometric and biomechanical modeling aided by machine learning improves the prediction of growth and rupture of small abdominal aortic aneurysms.

Scientific reports Sep 10, 2021
It remains difficult to predict when which patients with abdominal aortic aneurysm (AAA) will require surgery. The aim was to study the accuracy of geometric and biomechanical analysis of small AAAs to predict reaching the threshold for surgery, diam...
Models, Cardiovascular Prognosis Aortic Rupture Biomechanical Phenomena Humans ROC Curve Tomography, X-Ray Computed Area Under Curve Machine Learning Aortic Aneurysm, Abdominal Clinical Decision-Making Disease Management Algorithms Aorta, Abdominal Computed Tomography Angiography
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Glomerular disease classification and lesion identification by machine learning.

Biomedical journal Sep 8, 2021
BACKGROUND: Classification of glomerular diseases and identification of glomerular lesions require careful morphological examination by experienced nephropathologists, which is labor-intensive, time-consuming, and prone to interobserver variability. ...
Humans Neural Networks, Computer ROC Curve Image Processing, Computer-Assisted Machine Learning Deep Learning
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Machine learning guided postnatal gestational age assessment using new-born screening metabolomic data in South Asia and sub-Saharan Africa.

BMC pregnancy and childbirth Sep 7, 2021
BACKGROUND: Babies born early and/or small for gestational age in Low and Middle-income countries (LMICs) contribute substantially to global neonatal and infant mortality. Tracking this metric is critical at a population level for informed policy, ad...
Asia Africa South of the Sahara Neonatal Screening Gestational Age Premature Birth Prospective Studies Metabolomics Cohort Studies Male Pregnancy Developing Countries Ultrasonography, Prenatal ROC Curve Female Humans Machine Learning Algorithms Infant, Newborn
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Stratifying the Risk of Cardiovascular Disease in Obstructive Sleep Apnea Using Machine Learning.

The Laryngoscope Sep 6, 2021
OBJECTIVES/HYPOTHESIS: Obstructive sleep apnea (OSA) is associated with higher risk of morbidity and mortality related to cardiovascular disease (CVD). Due to overlapping clinical risk factors, identifying high-risk patients with OSA who are likely t...
Aged Aged, 80 and over Sensitivity and Specificity Male Retrospective Studies Female Risk Factors ROC Curve Sleep Apnea, Obstructive Cardiovascular Diseases Middle Aged Risk Assessment Machine Learning Algorithms Humans
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Deep learning model for diagnosing gastric mucosal lesions using endoscopic images: development, validation, and method comparison.

Gastrointestinal endoscopy Sep 4, 2021
BACKGROUND AND AIMS: Endoscopic differential diagnoses of gastric mucosal lesions (benign gastric ulcer, early gastric cancer [EGC], and advanced gastric cancer) remain challenging. We aimed to develop and validate convolutional neural network-based ...
Artificial Intelligence Deep Learning ROC Curve Area Under Curve Humans Neural Networks, Computer
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Ophthalmic Disease Detection via Deep Learning With a Novel Mixture Loss Function.

IEEE journal of biomedical and health informatics Sep 3, 2021
With the popularization of computer-aided diagnosis (CAD) technologies, more and more deep learning methods are developed to facilitate the detection of ophthalmic diseases. In this article, the deep learning-based detections for some common eye dise...
Algorithms Deep Learning ROC Curve Fundus Oculi Humans Neural Networks, Computer Glaucoma
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Accurate and Feasible Deep Learning Based Semi-Automatic Segmentation in CT for Radiomics Analysis in Pancreatic Neuroendocrine Neoplasms.

IEEE journal of biomedical and health informatics Sep 3, 2021
Current clinical practice or radiomics studies of pancreatic neuroendocrine neoplasms (pNENs) require manual delineation of the lesions in computed tomography (CT) images, which is time-consuming and subjective. We used a semi-automatic deep learning...
Neoplasms Deep Learning ROC Curve Area Under Curve Humans Retrospective Studies Tomography, X-Ray Computed
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Detecting hip osteoarthritis on clinical CT: a deep learning application based on 2-D summation images derived from CT.

Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA Sep 2, 2021
UNLABELLED: We developed and compared deep learning models to detect hip osteoarthritis on clinical CT. The CT-based summation images, CT-AP, that resemble X-ray radiographs can detect radiographic hip osteoarthritis and in the absence of large train...
Humans Retrospective Studies Radiography Osteoarthritis, Hip Tomography, X-Ray Computed Deep Learning ROC Curve
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Revisiting performance metrics for prediction with rare outcomes.

Statistical methods in medical research Sep 1, 2021
Machine learning algorithms are increasingly used in the clinical literature, claiming advantages over logistic regression. However, they are generally designed to maximize the area under the receiver operating characteristic curve. While area under ...
Machine Learning Humans Algorithms Postoperative Complications ROC Curve Benchmarking Predictive Value of Tests False Positive Reactions
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