AIMC Topic: Sensitivity and Specificity

Clear Filters Showing 1211 to 1220 of 2878 articles

Deep Learning Using Chest Radiographs to Identify High-Risk Smokers for Lung Cancer Screening Computed Tomography: Development and Validation of a Prediction Model.

Annals of internal medicine Sep 1, 2020
BACKGROUND: Lung cancer screening with chest computed tomography (CT) reduces lung cancer death. Centers for Medicare & Medicaid Services (CMS) eligibility criteria for lung cancer screening with CT require detailed smoking information and miss many ...
Tomography, X-Ray Computed Female Risk Factors Aged Humans Decision Support Techniques Lung Deep Learning Lung Neoplasms Early Detection of Cancer Smoking Sensitivity and Specificity Male Middle Aged Risk Assessment
View on PubMed DOI

Validation of a Deep Learning Algorithm for the Detection of Malignant Pulmonary Nodules in Chest Radiographs.

JAMA network open Sep 1, 2020
IMPORTANCE: The improvement of pulmonary nodule detection, which is a challenging task when using chest radiographs, may help to elevate the role of chest radiographs for the diagnosis of lung cancer.
Tumor Burden Radiography, Thoracic Radiographic Image Enhancement Middle Aged Lung Deep Learning Lung Neoplasms Solitary Pulmonary Nodule Early Detection of Cancer Reproducibility of Results Predictive Value of Tests Aged Radiologists Sensitivity and Specificity Humans Male Artificial Intelligence Algorithms Female
View on PubMed DOI

Validation of a Machine Learning Model to Predict Childhood Lead Poisoning.

JAMA network open Sep 1, 2020
IMPORTANCE: Childhood lead poisoning causes irreversible neurobehavioral deficits, but current practice is secondary prevention.
Machine Learning Female Sensitivity and Specificity Male Humans Health Care Rationing Preventive Health Services Lead Poisoning Resource Allocation Risk Assessment Child, Preschool Logistic Models United States
View on PubMed DOI

Artificial Intelligence-Assisted Loop Mediated Isothermal Amplification (AI-LAMP) for Rapid Detection of SARS-CoV-2.

Viruses Sep 1, 2020
Until vaccines and effective therapeutics become available, the practical solution to transit safely out of the current coronavirus disease 19 (CoVID-19) lockdown may include the implementation of an effective testing, tracing and tracking system. Ho...
Humans Betacoronavirus Pneumonia, Viral Nucleic Acid Amplification Techniques Sensitivity and Specificity Chlorocebus aethiops RNA, Viral Coronavirus Infections Animals COVID-19 Testing Vero Cells Real-Time Polymerase Chain Reaction Dogs Clinical Laboratory Techniques Molecular Diagnostic Techniques Madin Darby Canine Kidney Cells Artificial Intelligence Pandemics COVID-19 SARS-CoV-2
View on PubMed DOI

Comparison of Convolutional Neural Network Models for Determination of Vocal Fold Normality in Laryngoscopic Images.

Journal of voice : official journal of the Voice Foundation Aug 30, 2020
OBJECTIVES: Deep learning using convolutional neural networks (CNNs) is widely used in medical imaging research. This study was performed to investigate if vocal fold normality in laryngoscopic images can be determined by CNN-based deep learning and ...
Sensitivity and Specificity Deep Learning Vocal Cords Laryngoscopy Humans Neural Networks, Computer
View on PubMed DOI

Application of artificial intelligence using a novel EUS-based convolutional neural network model to identify and distinguish benign and malignant hepatic masses.

Gastrointestinal endoscopy Aug 28, 2020
BACKGROUND AND AIMS: Detection and characterization of focal liver lesions (FLLs) is key for optimizing treatment for patients who may have a primary hepatic cancer or metastatic disease to the liver. This is the first study to develop an EUS-based c...
Sensitivity and Specificity Humans Liver Neoplasms Neural Networks, Computer Artificial Intelligence Prospective Studies
View on PubMed DOI

Deep learning-based automated detection algorithm for active pulmonary tuberculosis on chest radiographs: diagnostic performance in systematic screening of asymptomatic individuals.

European radiology Aug 28, 2020
OBJECTIVES: Performance of deep learning-based automated detection (DLAD) algorithms in systematic screening for active pulmonary tuberculosis is unknown. We aimed to validate DLAD algorithm for detection of active pulmonary tuberculosis and any radi...
Tuberculosis, Pulmonary Radiography, Thoracic Adult Sensitivity and Specificity Deep Learning Radiography Humans Algorithms Young Adult
View on PubMed DOI

Deep Learning Based Software to Identify Large Vessel Occlusion on Noncontrast Computed Tomography.

Stroke Aug 26, 2020
BACKGROUND AND PURPOSE: Reliable recognition of large vessel occlusion (LVO) on noncontrast computed tomography (NCCT) may accelerate identification of endovascular treatment candidates. We aim to validate a machine learning algorithm (MethinksLVO) t...
Databases, Factual Tomography, X-Ray Computed Sensitivity and Specificity Deep Learning Brain Ischemia Middle Cerebral Artery Computed Tomography Angiography Stroke Infarction, Middle Cerebral Artery Humans Software
View on PubMed DOI

Computer-Aided System for the Detection of Multicategory Pulmonary Tuberculosis in Radiographs.

Journal of healthcare engineering Aug 24, 2020
The early screening and diagnosis of tuberculosis plays an important role in the control and treatment of tuberculosis infections. In this paper, an integrated computer-aided system based on deep learning is proposed for the detection of multiple cat...
Computer Systems Thorax Reproducibility of Results Radiographic Image Interpretation, Computer-Assisted Humans Sensitivity and Specificity X-Rays ROC Curve Tuberculosis, Pulmonary Diagnosis, Computer-Assisted Neural Networks, Computer False Positive Reactions Area Under Curve Deep Learning Algorithms Radiography, Thoracic Equipment Design Databases, Factual
View on PubMed DOI

Automated detection of early-stage ROP using a deep convolutional neural network.

The British journal of ophthalmology Aug 23, 2020
BACKGROUND/AIM: To automatically detect and classify the early stages of retinopathy of prematurity (ROP) using a deep convolutional neural network (CNN).
Male Diagnosis, Computer-Assisted ROC Curve Image Processing, Computer-Assisted Humans Female Infant, Low Birth Weight Birth Weight Neural Networks, Computer Infant, Newborn Infant, Premature Gestational Age Algorithms Sensitivity and Specificity Retinopathy of Prematurity Retrospective Studies Cross-Sectional Studies
View on PubMed DOI
Popular Topics
Recent Journals