AIMC Topic: ROC Curve

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Virtual genetic diagnosis for familial hypercholesterolemia powered by machine learning.

European journal of preventive cardiology Feb 4, 2020
AIMS: Familial hypercholesterolemia (FH) is the most common genetic disorder of lipid metabolism. The gold standard for FH diagnosis is genetic testing, available, however, only in selected university hospitals. Clinical scores - for example, the Dut...
DNA Mutation Genetic Testing Hyperlipoproteinemia Type II DNA Mutational Analysis Male Virtual Reality ROC Curve Lipids Heterozygote Humans Machine Learning Female Risk Factors
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Multiparametric radiomics methods for breast cancer tissue characterization using radiological imaging.

Breast cancer research and treatment Feb 4, 2020
BACKGROUND AND PURPOSE: Multiparametric radiological imaging is vital for detection, characterization, and diagnosis of many different diseases. Radiomics provide quantitative metrics from radiological imaging that may infer potential biological mean...
Machine Learning Retrospective Studies Female Aged Aged, 80 and over Humans ROC Curve Young Adult Radiology Adult Breast Breast Neoplasms Image Interpretation, Computer-Assisted Middle Aged Multiparametric Magnetic Resonance Imaging
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Using artificial intelligence (AI) to predict postoperative surgical site infection: A retrospective cohort of 4046 posterior spinal fusions.

Clinical neurology and neurosurgery Feb 3, 2020
OBJECTIVES: Machine Learning and Artificial Intelligence (AI) are rapidly growing in capability and increasingly applied to model outcomes and complications within medicine. In spinal surgery, post-operative surgical site infections (SSIs) are a rare...
Machine Learning Retrospective Studies Female Male Middle Aged Humans Neural Networks, Computer Artificial Intelligence Area Under Curve Comorbidity Spinal Fusion Deep Learning Surgical Wound Infection Cohort Studies Clinical Decision Rules ROC Curve
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Application of a machine learning algorithm to predict malignancy in thyroid cytopathology.

Cancer cytopathology Feb 3, 2020
BACKGROUND: The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) comprises 6 categories used for the diagnosis of thyroid fine-needle aspiration biopsy (FNAB). Each category has an associated risk of malignancy, which is important in the ...
Humans Cytodiagnosis Thyroid Gland Machine Learning Biopsy, Fine-Needle Thyroid Neoplasms Algorithms Adenocarcinoma, Follicular Thyroid Nodule Reproducibility of Results ROC Curve Pathologists
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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.
Area Under Curve Radiologists Humans Ultrasonography, Mammary Ultrasonography, Doppler, Color Adult Neural Networks, Computer Sensitivity and Specificity Retrospective Studies Breast Neoplasms Female Middle Aged Aged ROC Curve
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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...
Aged, 80 and over Adult Male Middle Aged Risk Assessment ROC Curve Adenocarcinoma Area Under Curve Neoplasm Recurrence, Local Humans Machine Learning Female Aged Esophagectomy Esophageal Neoplasms Clinical Decision Rules
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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...
Extraction, Obstetrical Trial of Labor Uterine Rupture Vaginal Birth after Cesarean Gestational Age Delivery, Obstetric Apgar Score Fetal Weight Risk Factors Female Organ Size Humans Adult Infant, Newborn Area Under Curve Machine Learning Risk Assessment Cesarean Section Tertiary Care Centers ROC Curve Retrospective Studies Parity Feasibility Studies Pregnancy Head
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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, ...
ROC Curve Tomography, Optical Coherence Optic Disk Optic Nerve Diseases Neural Networks, Computer Retinal Ganglion Cells Diagnostic Techniques, Ophthalmological Glaucoma Humans Retrospective Studies Intraocular Pressure Deep Learning
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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...
Stargardt Disease Deep Learning Humans ROC Curve Female Image Processing, Computer-Assisted Adult Male Tomography, Optical Coherence Middle Aged Severity of Illness Index Case-Control Studies
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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...
Neural Networks, Computer Artificial Intelligence ROC Curve Cephalometry
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