AIMC Topic:
ROC Curve

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A combined ultrasonic B-mode and color Doppler system for the classification of breast masses using neural network.

European radiology Jan 31, 2020
OBJECTIVES: To develop a dual-modal neural network model to characterize ultrasound (US) images of breast masses.
Humans Neural Networks, Computer Retrospective Studies Female Sensitivity and Specificity Breast Neoplasms Middle Aged Aged Adult ROC Curve Ultrasonography, Doppler, Color Area Under Curve Radiologists Ultrasonography, Mammary
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Machine learning to predict early recurrence after oesophageal cancer surgery.

The British journal of surgery Jan 30, 2020
BACKGROUND: Early cancer recurrence after oesophagectomy is a common problem, with an incidence of 20-30 per cent despite the widespread use of neoadjuvant treatment. Quantification of this risk is difficult and existing models perform poorly. This s...
Esophagectomy Aged, 80 and over Adult Humans Male Esophageal Neoplasms Middle Aged Machine Learning Clinical Decision Rules Adenocarcinoma Female Area Under Curve Aged Neoplasm Recurrence, Local Risk Assessment ROC Curve
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Prediction of vaginal birth after cesarean deliveries using machine learning.

American journal of obstetrics and gynecology Jan 30, 2020
BACKGROUND: Efforts to reduce cesarean delivery rates to 12-15% have been undertaken worldwide. Special focus has been directed towards parturients who undergo a trial of labor after cesarean delivery to reduce the burden of repeated cesarean deliver...
Female Extraction, Obstetrical Infant, Newborn Cesarean Section Trial of Labor Parity Uterine Rupture Gestational Age Humans Vaginal Birth after Cesarean Delivery, Obstetric Machine Learning Apgar Score Organ Size Retrospective Studies Fetal Weight Area Under Curve Pregnancy Risk Factors Tertiary Care Centers Adult Feasibility Studies Risk Assessment Head ROC Curve
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Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie Jan 27, 2020
PURPOSE: To develop a deep learning approach based on deep residual neural network (ResNet101) for the automated detection of glaucomatous optic neuropathy (GON) using color fundus images, understand the process by which the model makes predictions, ...
Deep Learning ROC Curve Tomography, Optical Coherence Optic Disk Diagnostic Techniques, Ophthalmological Retinal Ganglion Cells Neural Networks, Computer Optic Nerve Diseases Glaucoma Humans Retrospective Studies Intraocular Pressure
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Automated classification of normal and Stargardt disease optical coherence tomography images using deep learning.

Acta ophthalmologica Jan 24, 2020
PURPOSE: Recent advances in deep learning have seen an increase in its application to automated image analysis in ophthalmology for conditions with a high prevalence. We wanted to identify whether deep learning could be used for the automated classif...
Case-Control Studies Deep Learning ROC Curve Image Processing, Computer-Assisted Tomography, Optical Coherence Adult Male Middle Aged Severity of Illness Index Stargardt Disease Humans Female
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Automated Skeletal Classification with Lateral Cephalometry Based on Artificial Intelligence.

Journal of dental research Jan 24, 2020
Lateral cephalometry has been widely used for skeletal classification in orthodontic diagnosis and treatment planning. However, this conventional system, requiring manual tracing of individual landmarks, contains possible errors of inter- and intrava...
Cephalometry Neural Networks, Computer Artificial Intelligence ROC Curve
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Improvement of classification performance of Parkinson's disease using shape features for machine learning on dopamine transporter single photon emission computed tomography.

PloS one Jan 24, 2020
OBJECTIVE: To assess the classification performance between Parkinson's disease (PD) and normal control (NC) when semi-quantitative indicators and shape features obtained on dopamine transporter (DAT) single photon emission computed tomography (SPECT...
Case-Control Studies ROC Curve Parkinson Disease Area Under Curve Corpus Striatum Humans Machine Learning Databases, Factual Tomography, Emission-Computed, Single-Photon
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A six‑gene support vector machine classifier contributes to the diagnosis of pediatric septic shock.

Molecular medicine reports Jan 23, 2020
Septic shock is induced by an uncontrolled inflammatory immune response to pathogens and the survival rate of patients with pediatric septic shock (PSS) is particularly low, with a mortality rate of 25‑50%. The present study explored the mechanisms o...
ROC Curve Gene Regulatory Networks Databases, Genetic Computational Biology Gene Expression Profiling Shock, Septic Gene Expression Regulation, Neoplastic Age Factors Adolescent Support Vector Machine Humans Gene Ontology Child, Preschool Child Biomarkers Reproducibility of Results Infant
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Transfer learning radiomics based on multimodal ultrasound imaging for staging liver fibrosis.

European radiology Jan 21, 2020
OBJECTIVES: To propose a transfer learning (TL) radiomics model that efficiently combines the information from gray scale and elastogram ultrasound images for accurate liver fibrosis grading.
Data Accuracy Elasticity Imaging Techniques Liver Cirrhosis Liver Area Under Curve Hepatitis B, Chronic Algorithms Humans Male Aged Biomarkers Neural Networks, Computer Middle Aged Machine Learning Retrospective Studies Adult ROC Curve Female
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Validating the validation: reanalyzing a large-scale comparison of deep learning and machine learning models for bioactivity prediction.

Journal of computer-aided molecular design Jan 20, 2020
Machine learning methods may have the potential to significantly accelerate drug discovery. However, the increasing rate of new methodological approaches being published in the literature raises the fundamental question of how models should be benchm...
Humans Machine Learning Algorithms ROC Curve Support Vector Machine Computer Simulation Area Under Curve Drug Discovery Benchmarking Deep Learning Drug Evaluation, Preclinical User-Computer Interface
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