AIMC Topic: ROC Curve

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Histopathological Diagnosis System for Gastritis Using Deep Learning Algorithm.

Chinese medical sciences journal = Chung-kuo i hsueh k'o hsueh tsa chih Sep 30, 2021
Objective To develope a deep learning algorithm for pathological classification of chronic gastritis and assess its performance using whole-slide images (WSIs). Methods We retrospectively collected 1,250 gastric biopsy specimens (1,128 gastritis, 122...
Deep Learning ROC Curve Gastritis Humans Algorithms Retrospective Studies
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Machine learning for initial insulin estimation in hospitalized patients.

Journal of the American Medical Informatics Association : JAMIA Sep 18, 2021
OBJECTIVE: The study sought to determine whether machine learning can predict initial inpatient total daily dose (TDD) of insulin from electronic health records more accurately than existing guideline-based dosing recommendations.
Machine Learning Electronic Health Records Insulin ROC Curve Inpatients Humans
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Identification of active molecules against Mycobacterium tuberculosis through machine learning.

Briefings in bioinformatics Sep 2, 2021
Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (Mtb) and it has been one of the top 10 causes of death globally. Drug-resistant tuberculosis (XDR-TB), extensively resistant to the commonly used first-line drugs, has e...
ROC Curve Support Vector Machine Area Under Curve Antitubercular Agents Humans Neural Networks, Computer Reproducibility of Results Drug Discovery Data Accuracy Tuberculosis, Multidrug-Resistant Models, Biological Mycobacterium tuberculosis
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DeepCNV: a deep learning approach for authenticating copy number variations.

Briefings in bioinformatics Sep 2, 2021
Copy number variations (CNVs) are an important class of variations contributing to the pathogenesis of many disease phenotypes. Detecting CNVs from genomic data remains difficult, and the most currently applied methods suffer from an unacceptably hig...
DNA Copy Number Variations Humans Area Under Curve Benchmarking Deep Learning Genome, Human ROC Curve Datasets as Topic False Positive Reactions Disease
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GAERF: predicting lncRNA-disease associations by graph auto-encoder and random forest.

Briefings in bioinformatics Sep 2, 2021
Predicting disease-related long non-coding RNAs (lncRNAs) is beneficial to finding of new biomarkers for prevention, diagnosis and treatment of complex human diseases. In this paper, we proposed a machine learning techniques-based classification appr...
Stomach Neoplasms RNA, Long Noncoding Humans Biomarkers, Tumor Decision Trees Male Lung Neoplasms Prostatic Neoplasms Neural Networks, Computer ROC Curve Computer Graphics Computational Biology Machine Learning Gene Expression Regulation, Neoplastic Risk Factors MicroRNAs
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Tuberculosis detection from chest x-rays for triaging in a high tuberculosis-burden setting: an evaluation of five artificial intelligence algorithms.

The Lancet. Digital health Sep 1, 2021
BACKGROUND: Artificial intelligence (AI) algorithms can be trained to recognise tuberculosis-related abnormalities on chest radiographs. Various AI algorithms are available commercially, yet there is little impartial evidence on how their performance...
Humans Artificial Intelligence Algorithms Retrospective Studies ROC Curve Triage Radiography Sensitivity and Specificity Radiologists Radiographic Image Interpretation, Computer-Assisted Male Female Tuberculosis, Pulmonary Middle Aged Young Adult Bangladesh Adolescent Adult
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Detection of Optic Disc Abnormalities in Color Fundus Photographs Using Deep Learning.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society Sep 1, 2021
BACKGROUND: To date, deep learning-based detection of optic disc abnormalities in color fundus photographs has mostly been limited to the field of glaucoma. However, many life-threatening systemic and neurological conditions can manifest as optic dis...
Optic Disk Optic Nerve Diseases Diagnostic Techniques, Ophthalmological Algorithms Deep Learning ROC Curve Humans
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Deep Learning-based Diagnosis of Glaucoma Using Wide-field Optical Coherence Tomography Images.

Journal of glaucoma Sep 1, 2021
PURPOSE: (1) To evaluate the performance of deep learning (DL) classifier in detecting glaucoma, based on wide-field swept-source optical coherence tomography (SS-OCT) images. (2) To assess the performance of DL-based fusion methods in diagnosing gla...
ROC Curve Tomography, Optical Coherence Nerve Fibers Retinal Ganglion Cells Cross-Sectional Studies Intraocular Pressure Deep Learning Humans Glaucoma
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Machine Learning for Early Lung Cancer Identification Using Routine Clinical and Laboratory Data.

American journal of respiratory and critical care medicine Aug 15, 2021
Most lung cancers are diagnosed at an advanced stage. Presymptomatic identification of high-risk individuals can prompt earlier intervention and improve long-term outcomes. To develop a model to predict a future diagnosis of lung cancer on the basi...
Clinical Decision Rules Carcinoma, Non-Small-Cell Lung Humans Early Detection of Cancer Machine Learning Odds Ratio Retrospective Studies Female Middle Aged Aged Case-Control Studies Aged, 80 and over ROC Curve Sensitivity and Specificity Lung Neoplasms Male
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Application of Comprehensive Artificial intelligence Retinal Expert (CARE) system: a national real-world evidence study.

The Lancet. Digital health Aug 1, 2021
BACKGROUND: Medical artificial intelligence (AI) has entered the clinical implementation phase, although real-world performance of deep-learning systems (DLSs) for screening fundus disease remains unsatisfactory. Our study aimed to train a clinically...
Mass Screening Biomedical Technology Deep Learning Photography Humans Area Under Curve Models, Biological China Ophthalmologists Diabetic Retinopathy Fundus Oculi ROC Curve Retina Artificial Intelligence Image Processing, Computer-Assisted Expert Systems Retinal Diseases
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