AIMC Topic: ROC Curve

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Predicting weaning difficulty for planned extubation patients with an artificial neural network.

Medicine Oct 1, 2019
This study aims to construct a neural network to predict weaning difficulty among planned extubation patients in intensive care units.This observational cohort study was conducted in eight adult ICUs in a medical center about adult patients experienc...
Humans Neural Networks, Computer Algorithms Retrospective Studies Intensive Care Units Middle Aged ROC Curve APACHE Airway Extubation Ventilator Weaning Female Aged Aged, 80 and over Male
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DL-CNV: A deep learning method for identifying copy number variations based on next generation target sequencing.

Mathematical biosciences and engineering : MBE Sep 30, 2019
Copy number variations (CNVs) play an important role in many types of cancer. With the rapid development of next generation sequencing (NGS) techniques, many methods for detecting CNVs of a single sample have emerged: (i) require genome-wide data of ...
Reproducibility of Results Sensitivity and Specificity Deep Learning Genome-Wide Association Study ROC Curve Lung Neoplasms Carcinoma, Non-Small-Cell Lung DNA Copy Number Variations Area Under Curve Humans Algorithms Databases, Factual False Positive Reactions High-Throughput Nucleotide Sequencing Exons In Situ Hybridization, Fluorescence Proto-Oncogene Proteins c-met Receptor, ErbB-2 Genome, Human
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Prediction of IDH genotype in gliomas with dynamic susceptibility contrast perfusion MR imaging using an explainable recurrent neural network.

Neuro-oncology Sep 6, 2019
BACKGROUND: The aim of this study was to predict isocitrate dehydrogenase (IDH) genotypes of gliomas using an interpretable deep learning application for dynamic susceptibility contrast (DSC) perfusion MRI.
Adult Brain Neoplasms Male Middle Aged Deep Learning Humans Neural Networks, Computer Female Aged Isocitrate Dehydrogenase ROC Curve Image Processing, Computer-Assisted Contrast Media Genotype Magnetic Resonance Imaging Glioma Area Under Curve Mutation Magnetic Resonance Angiography
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Using Machine Learning and Natural Language Processing to Review and Classify the Medical Literature on Cancer Susceptibility Genes.

JCO clinical cancer informatics Sep 1, 2019
PURPOSE: The medical literature relevant to germline genetics is growing exponentially. Clinicians need tools that help to monitor and prioritize the literature to understand the clinical implications of pathogenic genetic variants. We developed and ...
Reproducibility of Results Neoplasms Prevalence Oncogenes ROC Curve Medicine in Literature Genetic Predisposition to Disease Support Vector Machine Natural Language Processing Polymorphism, Genetic Humans Knowledge Discovery Machine Learning
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Artificial Intelligence in Imaging: The Radiologist's Role.

Journal of the American College of Radiology : JACR Sep 1, 2019
Rapid technological advancements in artificial intelligence (AI) methods have fueled explosive growth in decision tools being marketed by a rapidly growing number of companies. AI developments are being driven largely by computer scientists, informat...
Radiology Radiologists Role Practice Patterns, Physicians' Algorithms Sensitivity and Specificity Deep Learning ROC Curve Image Processing, Computer-Assisted Humans Artificial Intelligence
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Radiomics MRI Phenotyping with Machine Learning to Predict the Grade of Lower-Grade Gliomas: A Study Focused on Nonenhancing Tumors.

Korean journal of radiology Sep 1, 2019
OBJECTIVE: To assess whether radiomics features derived from multiparametric MRI can predict the tumor grade of lower-grade gliomas (LGGs; World Health Organization grade II and grade III) and the nonenhancing LGG subgroup.
Image Processing, Computer-Assisted Glioma Magnetic Resonance Imaging Area Under Curve Neoplasm Grading Brain Neoplasms Male Middle Aged ROC Curve Humans Machine Learning Retrospective Studies Female Adult
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Stand-Alone Artificial Intelligence for Breast Cancer Detection in Mammography: Comparison With 101 Radiologists.

Journal of the National Cancer Institute Sep 1, 2019
BACKGROUND: Artificial intelligence (AI) systems performing at radiologist-like levels in the evaluation of digital mammography (DM) would improve breast cancer screening accuracy and efficiency. We aimed to compare the stand-alone performance of an ...
Early Detection of Cancer Mammography Area Under Curve Radiologists Humans Female Artificial Intelligence Reproducibility of Results Algorithms Breast Neoplasms ROC Curve Image Processing, Computer-Assisted
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Development and Validation of a Deep Learning-based Automatic Detection Algorithm for Active Pulmonary Tuberculosis on Chest Radiographs.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America Aug 16, 2019
BACKGROUND: Detection of active pulmonary tuberculosis on chest radiographs (CRs) is critical for the diagnosis and screening of tuberculosis. An automated system may help streamline the tuberculosis screening process and improve diagnostic performan...
Automation Thorax Deep Learning ROC Curve Aged Radiography Humans Adult Tuberculosis, Pulmonary Sensitivity and Specificity Algorithms Male Female Middle Aged
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Open Source Infrastructure for Health Care Data Integration and Machine Learning Analyses.

JCO clinical cancer informatics Aug 1, 2019
PURPOSE: We have created a cloud-based machine learning system (CLOBNET) that is an open-source, lean infrastructure for electronic health record (EHR) data integration and is capable of extract, transform, and load (ETL) processing. CLOBNET enables ...
Electronic Health Records Humans ROC Curve Genital Neoplasms, Female Female Machine Learning Decision Support Systems, Clinical Aged Software Cloud Computing Data Management Aged, 80 and over Databases, Factual Medical Informatics Middle Aged
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Machine learning applications for the prediction of surgical site infection in neurological operations.

Neurosurgical focus Aug 1, 2019
OBJECTIVE: Surgical site infection (SSI) following a neurosurgical operation is a complication that impacts morbidity, mortality, and economics. Currently, machine learning (ML) algorithms are used for outcome prediction in various neurosurgical aspe...
Male Middle Aged ROC Curve Neurosurgical Procedures Humans Female Neurosurgery Surgical Wound Infection Risk Factors Machine Learning Aged Retrospective Studies Adult
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