AIMC Topic: ROC Curve

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Macular Ganglion Cell-Inner Plexiform Layer Thickness Prediction from Red-free Fundus Photography using Hybrid Deep Learning Model.

Scientific reports Feb 24, 2020
We developed a hybrid deep learning model (HDLM) algorithm that quantitatively predicts macular ganglion cell-inner plexiform layer (mGCIPL) thickness from red-free retinal nerve fiber layer photographs (RNFLPs). A total of 789 pairs of RNFLPs and sp...
Optic Nerve Tomography, Optical Coherence Fundus Oculi Translational Research, Biomedical Retinal Ganglion Cells Aged, 80 and over Glaucoma Diagnostic Techniques, Ophthalmological Deep Learning Young Adult Algorithms ROC Curve Adult Refractometry Support Vector Machine Retrospective Studies Sensitivity and Specificity Regression Analysis Intraocular Pressure Female Humans Male Aged Middle Aged Case-Control Studies Diagnosis, Computer-Assisted
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A comprehensive study on the multi-class cervical cancer diagnostic prediction on pap smear images using a fusion-based decision from ensemble deep convolutional neural network.

Tissue & cell Feb 20, 2020
The diagnosis of cervical dysplasia, carcinoma in situ and confirmed carcinoma cases is more easily perceived by commercially available and current research-based decision support systems when the scenario of pathologists to patient ratio is small. T...
Area Under Curve Models, Biological Databases as Topic Humans Uterine Cervical Neoplasms Neural Networks, Computer Algorithms Deep Learning Female ROC Curve Papanicolaou Test Image Processing, Computer-Assisted
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Same same but different: A Web-based deep learning application revealed classifying features for the histopathologic distinction of cortical malformations.

Epilepsia Feb 20, 2020
OBJECTIVE: The microscopic review of hematoxylin-eosin-stained images of focal cortical dysplasia type IIb and cortical tuber of tuberous sclerosis complex remains challenging. Both entities are distinct subtypes of human malformations of cortical de...
Malformations of Cortical Development, Group I Neuropathology Tuberous Sclerosis Internet Neurons Cerebral Cortex Proof of Concept Study Diagnosis, Computer-Assisted Deep Learning ROC Curve Area Under Curve Humans Epilepsy Neural Networks, Computer Algorithms Reproducibility of Results
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A Machine-learning Approach to Forecast Aggravation Risk in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease with Clinical Indicators.

Scientific reports Feb 20, 2020
Patients with chronic obstructive pulmonary disease (COPD) repeat acute exacerbations (AE). Global Initiative for Chronic Obstructive Lung Disease (GOLD) is only available for patients in stable phase. Currently, there is a lack of assessment and pre...
Algorithms Prognosis Female Reproducibility of Results Hospitalization Aged Aged, 80 and over Adult Pulmonary Disease, Chronic Obstructive Humans Machine Learning False Positive Reactions Risk ROC Curve Male Decision Support Systems, Clinical Middle Aged Inflammation Disease Progression Models, Statistical Comorbidity Decision Trees
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Automatic detection and classification of protruding lesions in wireless capsule endoscopy images based on a deep convolutional neural network.

Gastrointestinal endoscopy Feb 19, 2020
BACKGROUND AND AIMS: Protruding lesions of the small bowel vary in wireless capsule endoscopy (WCE) images, and their automatic detection may be difficult. We aimed to develop and test a deep learning-based system to automatically detect protruding l...
Neural Networks, Computer Deep Learning ROC Curve Capsule Endoscopy Humans Intestine, Small
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Monitoring stance towards vaccination in twitter messages.

BMC medical informatics and decision making Feb 18, 2020
BACKGROUND: We developed a system to automatically classify stance towards vaccination in Twitter messages, with a focus on messages with a negative stance. Such a system makes it possible to monitor the ongoing stream of messages on social media, of...
Vaccination Support Vector Machine Social Media Data Collection Humans Netherlands Machine Learning ROC Curve
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Detecting Congestive Heart Failure by Extracting Multimodal Features and Employing Machine Learning Techniques.

BioMed research international Feb 18, 2020
The adaptability of heart to external and internal stimuli is reflected by the heart rate variability (HRV). Reduced HRV can be a predictor of negative cardiovascular outcomes. Based on the nonlinear, nonstationary, and highly complex dynamics of the...
ROC Curve Humans Machine Learning Support Vector Machine Algorithms Models, Statistical Sensitivity and Specificity Heart Failure Heart Rate
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Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT: external validation and clinical utility for resident training.

European radiology Feb 17, 2020
PURPOSE: This study aimed to validate a deep learning model's diagnostic performance in using computed tomography (CT) to diagnose cervical lymph node metastasis (LNM) from thyroid cancer in a large clinical cohort and to evaluate the model's clinica...
Radiology Education, Medical, Graduate ROC Curve Multidetector Computed Tomography Humans Internship and Residency Lymph Nodes Artificial Intelligence Neck Algorithms Lymphatic Metastasis Diagnosis, Computer-Assisted Deep Learning Cohort Studies Thyroid Neoplasms
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Prediction of bone mineral density from computed tomography: application of deep learning with a convolutional neural network.

European radiology Feb 14, 2020
OBJECTIVES: To investigate whether a deep learning model can predict the bone mineral density (BMD) of lumbar vertebrae from unenhanced abdominal computed tomography (CT) images.
Area Under Curve Lumbar Vertebrae Absorptiometry, Photon Middle Aged Deep Learning ROC Curve Abdomen Bone Density Retrospective Studies Osteoporosis Tomography, X-Ray Computed Female Reproducibility of Results Aged Adult Male Humans
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CT-based deep learning model to differentiate invasive pulmonary adenocarcinomas appearing as subsolid nodules among surgical candidates: comparison of the diagnostic performance with a size-based logistic model and radiologists.

European radiology Feb 13, 2020
OBJECTIVES: To evaluate the deep learning models for differentiating invasive pulmonary adenocarcinomas (IACs) among subsolid nodules (SSNs) considered for resection in a retrospective diagnostic cohort in comparison with a size-based logistic model ...
Humans Retrospective Studies Middle Aged Deep Learning ROC Curve Lung Neoplasms Logistic Models Tomography, X-Ray Computed Female Aged Male Radiologists Radiography, Thoracic Adenocarcinoma of Lung
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