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ROC Curve

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4S-DT: Self-Supervised Super Sample Decomposition for Transfer Learning With Application to COVID-19 Detection.

IEEE transactions on neural networks and learning systems Jul 6, 2021
Due to the high availability of large-scale annotated image datasets, knowledge transfer from pretrained models showed outstanding performance in medical image classification. However, building a robust image classification model for datasets with da...
Neural Networks, Computer Artificial Intelligence Machine Learning COVID-19 Humans Knowledge Bases Image Interpretation, Computer-Assisted Thorax X-Rays Algorithms Reproducibility of Results Deep Learning ROC Curve
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Development and Validation of a Magnetic Resonance Imaging-Based Machine Learning Model for TMJ Pathologies.

BioMed research international Jul 5, 2021
The purpose of this study was to propose a machine learning model and assess its ability to classify TMJ pathologies on magnetic resonance (MR) images. This retrospective cohort study included 214 TMJs from 107 patients with TMJ signs and symptoms. A...
Male Temporomandibular Joint Disorders Humans Female Middle Aged Machine Learning Aged ROC Curve Algorithms Young Adult Magnetic Resonance Imaging Adult
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Review of Statistical Methods for Evaluating the Performance of Survival or Other Time-to-Event Prediction Models (from Conventional to Deep Learning Approaches).

Korean journal of radiology Jul 1, 2021
The recent introduction of various high-dimensional modeling methods, such as radiomics and deep learning, has created a much greater diversity in modeling approaches for survival prediction (or, more generally, time-to-event prediction). The newness...
ROC Curve Humans Deep Learning
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Effect of a comprehensive deep-learning model on the accuracy of chest x-ray interpretation by radiologists: a retrospective, multireader multicase study.

The Lancet. Digital health Jul 1, 2021
BACKGROUND: Chest x-rays are widely used in clinical practice; however, interpretation can be hindered by human error and a lack of experienced thoracic radiologists. Deep learning has the potential to improve the accuracy of chest x-ray interpretati...
Aged Aged, 80 and over Young Adult Adult Artificial Intelligence Thoracic Injuries Retrospective Studies Female ROC Curve Thoracic Neoplasms Mass Screening Area Under Curve Male Middle Aged Deep Learning Adolescent Humans Infections X-Rays Radiologists Radiographic Image Interpretation, Computer-Assisted Models, Biological Radiography, Thoracic
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In silico prediction of chemical-induced hematotoxicity with machine learning and deep learning methods.

Molecular diversity Jul 1, 2021
Chemical-induced hematotoxicity is an important concern in the drug discovery, since it can often be fatal when it happens. It is quite useful for us to give special attention to chemicals which can cause hematotoxicity. In the present study, we focu...
Blood Cells Quantitative Structure-Activity Relationship Cheminformatics Algorithms ROC Curve Humans Reproducibility of Results Models, Molecular Machine Learning Drug Discovery Drug-Related Side Effects and Adverse Reactions Deep Learning Databases, Chemical
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Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Identify and Estimate Survival in a Longitudinal Cohort of Patients With Lung Cancer.

JAMA network open Jul 1, 2021
IMPORTANCE: Electronic health records (EHRs) provide a low-cost means of accessing detailed longitudinal clinical data for large populations. A lung cancer cohort assembled from EHR data would be a powerful platform for clinical outcome studies.
Cohort Studies ROC Curve Lung Neoplasms Area Under Curve Survival Analysis Survivors Boston Prognosis Electronic Health Records Female Male Humans Machine Learning Algorithms
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Multi-institutional development and external validation of machine learning-based models to predict relapse risk of pancreatic ductal adenocarcinoma after radical resection.

Journal of translational medicine Jun 30, 2021
BACKGROUND: Surgical resection is the only potentially curative treatment for pancreatic ductal adenocarcinoma (PDAC) and the survival of patients after radical resection is closely related to relapse. We aimed to develop models to predict the risk o...
Adenocarcinoma Support Vector Machine Humans Recurrence Machine Learning ROC Curve
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Prediction of preterm birth in nulliparous women using logistic regression and machine learning.

PloS one Jun 30, 2021
OBJECTIVE: To predict preterm birth in nulliparous women using logistic regression and machine learning.
Young Adult Logistic Models Adult Humans Pregnancy ROC Curve Area Under Curve Machine Learning Female Ontario Pregnancy Trimester, First Retrospective Studies Premature Birth Pregnancy Trimester, Second Parity
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Assessing the utility of deep neural networks in predicting postoperative surgical complications: a retrospective study.

The Lancet. Digital health Jun 29, 2021
BACKGROUND: Early detection of postoperative complications, including organ failure, is pivotal in the initiation of targeted treatment strategies aimed at attenuating organ damage. In an era of increasing health-care costs and limited financial reso...
Risk Assessment Postoperative Complications Adolescent ROC Curve Data Management Area Under Curve Humans Aged Models, Biological Neural Networks, Computer Databases, Factual Adult Postoperative Period Biomedical Technology Data Analysis Male Forecasting Retrospective Studies Middle Aged Female Risk Factors
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Non-invasive thyroid detection based on electroglottogram signal using machine learning classifiers.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine Jun 27, 2021
Thyroid is a butterfly shaped gland located in the neck region. Hormones are secreted by the thyroid gland that is responsible for various functions that maintain metabolism of the body. The variance in secretion of the hormones causes disorders such...
Machine Learning Algorithms Thyroid Gland ROC Curve Support Vector Machine Humans Bayes Theorem
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