AIMC Topic: ROC Curve

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Classifying non-small cell lung cancer types and transcriptomic subtypes using convolutional neural networks.

Journal of the American Medical Informatics Association : JAMIA May 1, 2020
OBJECTIVE: Non-small cell lung cancer is a leading cause of cancer death worldwide, and histopathological evaluation plays the primary role in its diagnosis. However, the morphological patterns associated with the molecular subtypes have not been sys...
Humans ROC Curve Lung Neoplasms Carcinoma, Non-Small-Cell Lung Adenocarcinoma of Lung Neural Networks, Computer Machine Learning Carcinoma, Squamous Cell Transcriptome
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Screening Candidates for Refractive Surgery With Corneal Tomographic-Based Deep Learning.

JAMA ophthalmology May 1, 2020
IMPORTANCE: Evaluating corneal morphologic characteristics with corneal tomographic scans before refractive surgery is necessary to exclude patients with at-risk corneas and keratoconus. In previous studies, researchers performed screening with machi...
Young Adult Humans Deep Learning Adult Artificial Intelligence Keratoconus China Cross-Sectional Studies Machine Learning Corneal Topography ROC Curve Male Algorithms Refractive Surgical Procedures Models, Theoretical Female Tomography
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A new risk stratification score for patients with suspected cardiac chest pain in emergency departments, based on machine learning.

Chinese medical journal Apr 5, 2020
Machine Learning Retrospective Studies Emergency Service, Hospital ROC Curve Chest Pain Humans Logistic Models Chi-Square Distribution Angina Pectoris
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Detecting Patient Deterioration Using Artificial Intelligence in a Rapid Response System.

Critical care medicine Apr 1, 2020
OBJECTIVES: As the performance of a conventional track and trigger system in a rapid response system has been unsatisfactory, we developed and implemented an artificial intelligence for predicting in-hospital cardiac arrest, denoted the deep learning...
Middle Aged Risk Assessment ROC Curve Vital Signs Heart Arrest Critical Illness Humans Clinical Deterioration Female Artificial Intelligence Hospital Rapid Response Team Adult Algorithms Male Retrospective Studies
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Radiomics and Deep Learning: Hepatic Applications.

Korean journal of radiology Apr 1, 2020
Radiomics and deep learning have recently gained attention in the imaging assessment of various liver diseases. Recent research has demonstrated the potential utility of radiomics and deep learning in staging liver fibroses, detecting portal hyperten...
Area Under Curve Liver Diseases Humans Hypertension, Portal ROC Curve Databases, Factual Deep Learning Liver Neoplasms Image Processing, Computer-Assisted Liver Cirrhosis
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A customizable deep learning model for nosocomial risk prediction from critical care notes with indirect supervision.

Journal of the American Medical Informatics Association : JAMIA Apr 1, 2020
OBJECTIVE: Reliable longitudinal risk prediction for hospitalized patients is needed to provide quality care. Our goal is to develop a generalizable model capable of leveraging clinical notes to predict healthcare-associated diseases 24-96 hours in a...
Anemia Pressure Ulcer Iatrogenic Disease Support Vector Machine Natural Language Processing Area Under Curve Critical Care Risk Assessment Deep Learning ROC Curve Humans Retrospective Studies Acute Kidney Injury Electronic Health Records
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Diagnosing Glaucoma With Spectral-Domain Optical Coherence Tomography Using Deep Learning Classifier.

Journal of glaucoma Apr 1, 2020
UNLABELLED: PRéCIS:: A spectral-domain optical coherence tomography (SD-OCT) based deep learning system detected glaucomatous structural change with high sensitivity and specificity. It outperformed the clinical diagnostic parameters in discriminatin...
Humans Glaucoma Female Aged Adult Nerve Fibers Deep Learning Optic Disk ROC Curve Retinal Ganglion Cells Sensitivity and Specificity Area Under Curve Visual Fields Intraocular Pressure Tomography, Optical Coherence Male Middle Aged
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Assessment of a Segmentation-Free Deep Learning Algorithm for Diagnosing Glaucoma From Optical Coherence Tomography Scans.

JAMA ophthalmology Apr 1, 2020
IMPORTANCE: Conventional segmentation of the retinal nerve fiber layer (RNFL) is prone to errors that may affect the accuracy of spectral-domain optical coherence tomography (SD-OCT) scans in detecting glaucomatous damage.
Slit Lamp Microscopy ROC Curve Tomography, Optical Coherence Nerve Fibers Retinal Ganglion Cells Visual Fields Visual Field Tests Glaucoma, Open-Angle Gonioscopy Intraocular Pressure Male Humans Middle Aged Aged, 80 and over Algorithms Deep Learning Adult Female Cross-Sectional Studies Aged
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Performance of a Deep Neural Network Algorithm Based on a Small Medical Image Dataset: Incremental Impact of 3D-to-2D Reformation Combined with Novel Data Augmentation, Photometric Conversion, or Transfer Learning.

Journal of digital imaging Apr 1, 2020
Collecting and curating large medical-image datasets for deep neural network (DNN) algorithm development is typically difficult and resource-intensive. While transfer learning (TL) decreases reliance on large data collections, current TL implementati...
Algorithms ROC Curve Computed Tomography Angiography Humans Neural Networks, Computer Machine Learning
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Epileptic seizure detection: a comparative study between deep and traditional machine learning techniques.

Journal of integrative neuroscience Mar 30, 2020
Electroencephalography is the recording of brain electrical activities that can be used to diagnose brain seizure disorders. By identifying brain activity patterns and their correspondence between symptoms and diseases, it is possible to give an accu...
Signal Processing, Computer-Assisted ROC Curve Humans Electroencephalography Machine Learning Epilepsy Brain Seizures
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