AIMC Topic: ROC Curve
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Implementing machine learning in bipolar diagnosis in China.
Translational psychiatry
Nov 18, 2019
Bipolar disorder (BPD) is often confused with major depression, and current diagnostic questionnaires are subjective and time intensive. The aim of this study was to develop a new Bipolar Diagnosis Checklist in Chinese (BDCC) by using machine learnin...
TAP: A static analysis model for PHP vulnerabilities based on token and deep learning technology.
PloS one
Nov 18, 2019
With the widespread usage of Web applications, the security issues of source code are increasing. The exposed vulnerabilities seriously endanger the interests of service providers and customers. There are some models for solving this problem. However...
AOCT-NET: a convolutional network automated classification of multiclass retinal diseases using spectral-domain optical coherence tomography images.
Medical & biological engineering & computing
Nov 14, 2019
Since introducing optical coherence tomography (OCT) technology for 2D eye imaging, it has become one of the most important and widely used imaging modalities for the noninvasive assessment of retinal eye diseases. Age-related macular degeneration (A...
CT-based radiomics for prediction of histologic subtype and metastatic disease in primary malignant lung neoplasms.
International journal of computer assisted radiology and surgery
Nov 13, 2019
PURPOSE: As some of the most important factors for treatment decision of lung cancer (which is the deadliest neoplasm) are staging and histology, this work aimed to associate quantitative contrast-enhanced computed tomography (CT) features from malig...
Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs.
American journal of ophthalmology
Nov 12, 2019
PURPOSE: To compare the diagnostic performance of human gradings vs predictions provided by a machine-to-machine (M2M) deep learning (DL) algorithm trained to quantify retinal nerve fiber layer (RNFL) damage on fundus photographs.
Retrospective Studies
Optic Nerve Diseases
Female
Photography
Aged
Physical Examination
Cross-Sectional Studies
Glaucoma, Open-Angle
Humans
Middle Aged
Algorithms
Deep Learning
Gonioscopy
Nerve Fibers
ROC Curve
Vision Disorders
Intraocular Pressure
Retinal Ganglion Cells
Area Under Curve
Male
Visual Fields
Tomography, Optical Coherence
Visual Field Tests
Fundus Oculi
Using machine learning approaches to predict high-cost chronic obstructive pulmonary disease patients in China.
Health informatics journal
Nov 11, 2019
The accurate identification and prediction of high-cost Chronic obstructive pulmonary disease (COPD) patients is important for addressing the economic burden of COPD. The objectives of this study were to use machine learning approaches to identify an...
Detection of mesial temporal lobe epileptiform discharges on intracranial electrodes using deep learning.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Nov 11, 2019
OBJECTIVE: Develop a high-performing algorithm to detect mesial temporal lobe (mTL) epileptiform discharges on intracranial electrode recordings.
Early symptoms and sensations as predictors of lung cancer: a machine learning multivariate model.
Scientific reports
Nov 11, 2019
The aim of this study was to identify a combination of early predictive symptoms/sensations attributable to primary lung cancer (LC). An interactive e-questionnaire comprised of pre-diagnostic descriptors of first symptoms/sensations was administered...
A machine learning method correlating pulse pressure wave data with pregnancy.
International journal for numerical methods in biomedical engineering
Nov 10, 2019
Pulse feeling , representing the tactile arterial palpation of the heartbeat, has been widely used in traditional Chinese medicine (TCM) to diagnose various diseases. The quantitative relationship between the pulse wave and health conditions however ...
Predictive Utility of a Machine Learning Algorithm in Estimating Mortality Risk in Cardiac Surgery.
The Annals of thoracic surgery
Nov 7, 2019
BACKGROUND: This study evaluated the predictive utility of a machine learning algorithm in estimating operative mortality risk in cardiac surgery.
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