AIMC Topic:
ROC Curve

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Deep Learning Ensemble Method for Classifying Glaucoma Stages Using Fundus Photographs and Convolutional Neural Networks.

Current eye research Apr 6, 2021
: This study developed and evaluated a deep learning ensemble method to automatically grade the stages of glaucoma depending on its severity.: After cross-validation of three glaucoma specialists, the final dataset comprised of 3,460 fundus photograp...
Retrospective Studies Reproducibility of Results Severity of Illness Index Deep Learning Humans Neural Networks, Computer Glaucoma Visual Field Tests Diagnostic Techniques, Ophthalmological Photography ROC Curve Area Under Curve Fundus Oculi Visual Fields
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Understanding risk factors for postoperative mortality in neonates based on explainable machine learning technology.

Journal of pediatric surgery Apr 5, 2021
PURPOSE: We aimed to introduce an explainable machine learning technology to help clinicians understand the risk factors for neonatal postoperative mortality at different levels.
Machine Learning Technology Infant, Newborn Risk Factors Child ROC Curve Postoperative Period Humans
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Machine Learning-Based Multiparametric Magnetic Resonance Imaging Radiomics for Prediction of H3K27M Mutation in Midline Gliomas.

World neurosurgery Apr 2, 2021
OBJECTIVE: H3K27M mutation in gliomas has prognostic implications. Previous magnetic resonance imaging (MRI) studies have reported variable rates of tumoral enhancement, necrotic changes, and peritumoral edema in H3K27M-mutant gliomas, with no distin...
Humans Area Under Curve Mutation Histones Glioma Magnetic Resonance Imaging Predictive Value of Tests Brain Neoplasms Male Middle Aged Adolescent Machine Learning Algorithms Cohort Studies Reproducibility of Results Female Child Young Adult ROC Curve Adult Image Processing, Computer-Assisted Sensitivity and Specificity
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Prediction of eating disorder treatment response trajectories via machine learning does not improve performance versus a simpler regression approach.

The International journal of eating disorders Apr 2, 2021
OBJECTIVE: Patterns of response to eating disorder (ED) treatment are heterogeneous. Advance knowledge of a patient's expected course may inform precision medicine for ED treatment. This study explored the feasibility of applying machine learning to ...
Humans Adolescent ROC Curve Machine Learning Logistic Models Female Feeding and Eating Disorders Hospitalization Adult
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Development and Validation of a Machine Learning Model to Estimate Bacterial Sepsis Among Immunocompromised Recipients of Stem Cell Transplant.

JAMA network open Apr 1, 2021
IMPORTANCE: Sepsis disproportionately affects recipients of allogeneic hematopoietic cell transplant (allo-HCT), and timely detection is crucial. However, the atypical presentation of sepsis within this population makes detection challenging, and exi...
Hematopoietic Stem Cell Transplantation Random Allocation Immunocompetence Humans Risk Assessment Sepsis Machine Learning Female ROC Curve Decision Support Techniques Adult Retrospective Studies Male Middle Aged
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A machine learning-based pulmonary venous obstruction prediction model using clinical data and CT image.

International journal of computer assisted radiology and surgery Mar 31, 2021
PURPOSE: In this study, we try to consider the most common type of total anomalous pulmonary venous connection and established a machine learning-based prediction model for postoperative pulmonary venous obstruction by using clinical data and CT imag...
Predictive Value of Tests Area Under Curve Vascular Diseases Pulmonary Veins Lung ROC Curve Logistic Models Humans Neural Networks, Computer Machine Learning Tomography, X-Ray Computed
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A deep learning classifier for digital breast tomosynthesis.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Mar 31, 2021
PURPOSE: To develop a computerized detection system for the automatic classification of the presence/absence of mass lesions in digital breast tomosynthesis (DBT) annotated exams, based on a deep convolutional neural network (DCNN).
Humans Neural Networks, Computer Female Breast Neoplasms Deep Learning ROC Curve Mammography Area Under Curve
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Prediction of risk of acquiring urinary tract infection during hospital stay based on machine-learning: A retrospective cohort study.

PloS one Mar 31, 2021
BACKGROUND: Healthcare associated infections (HAI) are a major burden for the healthcare system and associated with prolonged hospital stay, increased morbidity, mortality and costs. Healthcare associated urinary tract infections (HA-UTI) accounts fo...
Urinary Tract Infections Cross Infection Young Adult Middle Aged Patient Admission Electronic Health Records Adult Length of Stay Humans Female Male ROC Curve Machine Learning Risk Factors Denmark Retrospective Studies Aged
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Development and evaluation of a deep learning model for the detection of multiple fundus diseases based on colour fundus photography.

The British journal of ophthalmology Mar 30, 2021
AIM: To explore and evaluate an appropriate deep learning system (DLS) for the detection of 12 major fundus diseases using colour fundus photography.
Humans Diabetic Retinopathy Sensitivity and Specificity Deep Learning ROC Curve Color Fundus Oculi Optic Nerve Diseases Photography
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Exploring the predictive value of additional peritumoral regions based on deep learning and radiomics: A multicenter study.

Medical physics Mar 30, 2021
PURPOSE: The present study assessed the predictive value of peritumoral regions on three tumor tasks, and further explored the influence of peritumors with different sizes.
Artificial Intelligence Retrospective Studies Deep Learning ROC Curve Humans
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