AIMC Topic: Sensitivity and Specificity

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Deep-learned placental vessel segmentation for intraoperative video enhancement in fetoscopic surgery.

International journal of computer assisted radiology and surgery Nov 27, 2018
INTRODUCTION: Twin-to-twin transfusion syndrome (TTTS) is a potentially lethal condition that affects pregnancies in which twins share a single placenta. The definitive treatment for TTTS is fetoscopic laser photocoagulation, a procedure in which pla...
Fetofetal Transfusion Pregnancy Fetoscopy Humans Laser Coagulation Female Deep Learning Sensitivity and Specificity Image Processing, Computer-Assisted Placenta Vascular Surgical Procedures
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A reliable method for colorectal cancer prediction based on feature selection and support vector machine.

Medical & biological engineering & computing Nov 26, 2018
Colorectal cancer (CRC) is a common cancer responsible for approximately 600,000 deaths per year worldwide. Thus, it is very important to find the related factors and detect the cancer accurately. However, timely and accurate prediction of the diseas...
Humans Logistic Models Body Mass Index Reproducibility of Results Support Vector Machine Sensitivity and Specificity Area Under Curve Colorectal Neoplasms Models, Biological ROC Curve
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DeepSeeNet: A Deep Learning Model for Automated Classification of Patient-based Age-related Macular Degeneration Severity from Color Fundus Photographs.

Ophthalmology Nov 22, 2018
PURPOSE: In assessing the severity of age-related macular degeneration (AMD), the Age-Related Eye Disease Study (AREDS) Simplified Severity Scale predicts the risk of progression to late AMD. However, its manual use requires the time-consuming partic...
Humans Prospective Studies Female Aged Aged, 80 and over Diagnostic Techniques, Ophthalmological Sensitivity and Specificity Photography Reproducibility of Results Retinal Drusen Risk Factors Geographic Atrophy Diagnosis, Computer-Assisted Male Deep Learning Middle Aged Models, Theoretical Disease Progression Area Under Curve Severity of Illness Index
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Machine Learning Methods as a Tool for Predicting Risk of Illness Applying Next-Generation Sequencing Data.

Risk analysis : an official publication of the Society for Risk Analysis Nov 21, 2018
Next-generation sequencing (NGS) data present an untapped potential to improve microbial risk assessment (MRA) through increased specificity and redefinition of the hazard. Most of the MRA models do not account for differences in survivability and vi...
Probability Linear Models Food Listeriosis Listeria monocytogenes Virulence Genetic Variation High-Throughput Nucleotide Sequencing Risk Assessment Databases, Genetic Food Microbiology Foodborne Diseases Algorithms Humans Phenotype Machine Learning Sensitivity and Specificity
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Automated classification of benign and malignant lesions in F-NaF PET/CT images using machine learning.

Physics in medicine and biology Nov 20, 2018
PURPOSE: F-NaF PET/CT imaging of bone metastases is confounded by tracer uptake in benign diseases, such as osteoarthritis. The goal of this work was to develop an automated bone lesion classification algorithm to classify lesions in NaF PET/CT image...
Prostatic Neoplasms, Castration-Resistant Fluorine Radioisotopes Sodium Fluoride Image Processing, Computer-Assisted Bone Neoplasms Positron Emission Tomography Computed Tomography Automation Algorithms Sensitivity and Specificity Male Humans Machine Learning
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Automated detection of imaging features of disproportionately enlarged subarachnoid space hydrocephalus using machine learning methods.

NeuroImage. Clinical Nov 19, 2018
OBJECTIVE: Create an automated classifier for imaging characteristics of disproportionately enlarged subarachnoid space hydrocephalus (DESH), a neuroimaging phenotype of idiopathic normal pressure hydrocephalus (iNPH).
ROC Curve Aged Humans Support Vector Machine Subarachnoid Space Machine Learning Aged, 80 and over Magnetic Resonance Imaging Brain Sensitivity and Specificity Hydrocephalus, Normal Pressure Female Male
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Application of convolutional neural network in the diagnosis of the invasion depth of gastric cancer based on conventional endoscopy.

Gastrointestinal endoscopy Nov 16, 2018
BACKGROUND AND AIMS: According to guidelines, endoscopic resection should only be performed for patients whose early gastric cancer invasion depth is within the mucosa or submucosa of the stomach regardless of lymph node involvement. The accurate pre...
Humans Sensitivity and Specificity Male Diagnosis, Computer-Assisted ROC Curve Image Processing, Computer-Assisted Neural Networks, Computer Artificial Intelligence Female Stomach Neoplasms Gastric Mucosa Neoplasm Invasiveness Endoscopic Mucosal Resection Carcinoma Serous Membrane Gastrectomy Gastroscopy
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Identifying probable post-traumatic stress disorder: applying supervised machine learning to data from a UK military cohort.

Journal of mental health (Abingdon, England) Nov 16, 2018
BACKGROUND: Early identification of probable post-traumatic stress disorder (PTSD) can lead to early intervention and treatment.
Military Personnel United Kingdom Female Cohort Studies Humans Male Young Adult Stress Disorders, Post-Traumatic Middle Aged Supervised Machine Learning Adult Sensitivity and Specificity
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A deep neural network learning algorithm outperforms a conventional algorithm for emergency department electrocardiogram interpretation.

Journal of electrocardiology Nov 16, 2018
BACKGROUND: Cardiologs® has developed the first electrocardiogram (ECG) algorithm that uses a deep neural network (DNN) for full 12‑lead ECG analysis, including rhythm, QRS and ST-T-U waves. We compared the accuracy of the first version of Cardiologs...
Arrhythmias, Cardiac Sensitivity and Specificity Electrocardiography Predictive Value of Tests Emergency Service, Hospital Humans Neural Networks, Computer Algorithms Retrospective Studies
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Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging.

European radiology Nov 15, 2018
OBJECTIVES: Preoperative, noninvasive prediction of the meningioma grade is important because it influences the treatment strategy. The purpose of this study was to evaluate the role of radiomics features of postcontrast T1-weighted images (T1C), app...
Algorithms Retrospective Studies Female Reproducibility of Results Humans Machine Learning Neoplasm Grading Diffusion Tensor Imaging Meningioma Anisotropy Meningeal Neoplasms Aged Sensitivity and Specificity Male Middle Aged
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