AIMC Topic: Area Under Curve

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Evaluation of a Deep Learning System For Identifying Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.

Journal of glaucoma Dec 1, 2019
PRECIS: Pegasus outperformed 5 of the 6 ophthalmologists in terms of diagnostic performance, and there was no statistically significant difference between the deep learning system and the "best case" consensus between the ophthalmologists. The agreem...
Humans Retrospective Studies Female Aged Observer Variation Optic Disk Optic Nerve Diseases Diagnostic Techniques, Ophthalmological Photography Ophthalmologists Glaucoma, Open-Angle Middle Aged Diagnosis, Computer-Assisted Deep Learning ROC Curve Area Under Curve Adult Sensitivity and Specificity Intraocular Pressure Male
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OPTICAL COHERENCE TOMOGRAPHY BIOMARKERS TO DISTINGUISH DIABETIC MACULAR EDEMA FROM PSEUDOPHAKIC CYSTOID MACULAR EDEMA USING MACHINE LEARNING ALGORITHMS.

Retina (Philadelphia, Pa.) Dec 1, 2019
PURPOSE: In diabetic patients presenting with macular edema (ME) shortly after cataract surgery, identifying the underlying pathology can be challenging and influence management. Our aim was to develop a simple clinical classifier able to confirm a d...
Reproducibility of Results Aged Sensitivity and Specificity Male Humans Middle Aged Diabetic Retinopathy Machine Learning Tomography, Optical Coherence Biomarkers Diagnosis, Computer-Assisted Macular Edema Retrospective Studies Visual Acuity Female Fluorescein Angiography Predictive Value of Tests Subretinal Fluid Area Under Curve Pseudophakia
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Using a machine learning algorithm to predict acute graft-versus-host disease following allogeneic transplantation.

Blood advances Nov 26, 2019
Acute graft-versus-host disease (aGVHD) is 1 of the critical complications that often occurs following allogeneic hematopoietic stem cell transplantation (HSCT). Thus far, various types of prediction scores have been created using statistical calcula...
Area Under Curve Graft vs Host Disease Hematopoietic Stem Cell Transplantation Transplantation, Homologous Female Hematologic Diseases Humans Reproducibility of Results Machine Learning Male Algorithms Models, Theoretical Prognosis
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High-throughput multimodal automated phenotyping (MAP) with application to PheWAS.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2019
OBJECTIVE: Electronic health records linked with biorepositories are a powerful platform for translational studies. A major bottleneck exists in the ability to phenotype patients accurately and efficiently. The objective of this study was to develop ...
Humans Algorithms Phenotype Electronic Health Records Polymorphism, Single Nucleotide Natural Language Processing Area Under Curve International Classification of Diseases Unified Medical Language System
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Development and Validation of a Machine Learning Algorithm for Predicting Response to Anticholinergic Medications for Overactive Bladder Syndrome.

Obstetrics and gynecology Nov 1, 2019
OBJECTIVE: To develop and externally validate a prediction model for anticholinergic response in patients with overactive bladder (OAB).
Female Reproducibility of Results Aged Adult Middle Aged Humans Machine Learning Algorithms Prognosis Cholinergic Antagonists Predictive Value of Tests Area Under Curve Urinary Bladder, Overactive Urinary Incontinence
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Machine Learning Algorithm Identifies Patients at High Risk for Early Complications After Intracranial Tumor Surgery: Registry-Based Cohort Study.

Neurosurgery Oct 1, 2019
INTRODUCTION: Reliable preoperative identification of patients at high risk for early postoperative complications occurring within 24 h (EPC) of intracranial tumor surgery can improve patient safety and postoperative management. Statistical analysis ...
Machine Learning Algorithms Prospective Studies Female Aged Adult Brain Neoplasms Male Middle Aged Humans Postoperative Complications Cohort Studies Area Under Curve Registries
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Learning to detect and understand drug discontinuation events from clinical narratives.

Journal of the American Medical Informatics Association : JAMIA Oct 1, 2019
OBJECTIVE: Identifying drug discontinuation (DDC) events and understanding their reasons are important for medication management and drug safety surveillance. Structured data resources are often incomplete and lack reason information. In this article...
Humans Natural Language Processing Machine Learning Drug Therapy Electronic Health Records Area Under Curve Support Vector Machine Narration Pharmacovigilance Product Surveillance, Postmarketing
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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 ...
Proto-Oncogene Proteins c-met Carcinoma, Non-Small-Cell Lung DNA Copy Number Variations Area Under Curve Sensitivity and Specificity In Situ Hybridization, Fluorescence Humans High-Throughput Nucleotide Sequencing Deep Learning Receptor, ErbB-2 Algorithms Genome-Wide Association Study Genome, Human Databases, Factual ROC Curve False Positive Reactions Reproducibility of Results Lung Neoplasms Exons
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[Clinical image identification of basal cell carcinoma and pigmented nevi based on convolutional neural network].

Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences Sep 28, 2019
To construct an intelligent assistant diagnosis model based on the clinical images of basal cell carcinoma (BCC) and pigmented nevi in Chinese by using the advanced convolutional neural network (CNN).
 Methods: Based on the Xiangya Medical Big Data P...
Carcinoma, Basal Cell Area Under Curve Nevus, Pigmented Humans Neural Networks, Computer Skin Neoplasms
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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.
Area Under Curve Mutation Magnetic Resonance Angiography Isocitrate Dehydrogenase Genotype Glioma Contrast Media Humans Magnetic Resonance Imaging Male Neural Networks, Computer Middle Aged Female Deep Learning ROC Curve Aged Image Processing, Computer-Assisted Adult Brain Neoplasms
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