AIMC Topic: Sensitivity and Specificity

Clear Filters Showing 1401 to 1410 of 2880 articles

Development and Validation of a Machine Learning Model to Aid Discharge Processes for Inpatient Surgical Care.

JAMA network open Dec 2, 2019
IMPORTANCE: Inpatient overcrowding is associated with delays in care, including the deferral of surgical care until beds are available to accommodate postoperative patients. Timely patient discharge is critical to address inpatient overcrowding and r...
Prognosis Female Aged Aged, 80 and over Young Adult Humans Neural Networks, Computer Machine Learning Prospective Studies Adolescent Time Factors Models, Theoretical Postoperative Care Patient Discharge Adult Sensitivity and Specificity Male Middle Aged
View on PubMed DOI

Detection and localisation of hip fractures on anteroposterior radiographs with artificial intelligence: proof of concept.

Clinical radiology Nov 29, 2019
AIM: To investigate the feasibility of applying a deep convolutional neural network (CNN) for detection/localisation of acute proximal femoral fractures (APFFs) on hip radiographs.
Male Middle Aged Adolescent Feasibility Studies Hip Fractures Proof of Concept Study Female Aged Aged, 80 and over Humans Adult Artificial Intelligence Sensitivity and Specificity Retrospective Studies
View on PubMed DOI

Diagnosis of Thyroid Nodules: Performance of a Deep Learning Convolutional Neural Network Model vs. Radiologists.

Scientific reports Nov 28, 2019
Computer-aided diagnosis (CAD) systems hold potential to improve the diagnostic accuracy of thyroid ultrasound (US). We aimed to develop a deep learning-based US CAD system (dCAD) for the diagnosis of thyroid nodules and compare its performance with ...
Image Interpretation, Computer-Assisted Humans Middle Aged Female Deep Learning Aged Ultrasonography Aged, 80 and over Thyroid Nodule Adult Support Vector Machine Sensitivity and Specificity Male
View on PubMed DOI

An interpretation algorithm for molecular diagnosis of bacterial vaginosis in a maternity hospital using machine learning: proof-of-concept study.

Diagnostic microbiology and infectious disease Nov 27, 2019
Allplex Bacterial vaginosis assay (Seegene, South Korea) is a molecular test for bacterial vaginosis (BV). A machine learning algorithm was devised on 200 samples (BV = 23, non-BV = 177) converting 7 identified bacterial strains polymerase chain reac...
Humans Machine Learning Molecular Diagnostic Techniques Vaginosis, Bacterial Hospitals, Maternity Algorithms Cross Infection Female Polymerase Chain Reaction Reproducibility of Results Proof of Concept Study Sensitivity and Specificity
View on PubMed DOI

Fully-automated deep learning-powered system for DCE-MRI analysis of brain tumors.

Artificial intelligence in medicine Nov 27, 2019
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays an important role in diagnosis and grading of brain tumors. Although manual DCE biomarker extraction algorithms boost the diagnostic yield of DCE-MRI by providing quantitative infor...
Contrast Media Reproducibility of Results Humans Pharmacokinetics Magnetic Resonance Imaging Sensitivity and Specificity Phantoms, Imaging Regional Blood Flow Brain Neoplasms Automation Deep Learning Algorithms Databases, Factual Prognosis
View on PubMed DOI

Limited One-time Sampling Irregularity Map (LOTS-IM) for Automatic Unsupervised Assessment of White Matter Hyperintensities and Multiple Sclerosis Lesions in Structural Brain Magnetic Resonance Images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Nov 27, 2019
We present the application of limited one-time sampling irregularity map (LOTS-IM): a fully automatic unsupervised approach to extract brain tissue irregularities in magnetic resonance images (MRI), for quantitatively assessing white matter hyperinte...
Multiple Sclerosis Image Interpretation, Computer-Assisted Humans Image Processing, Computer-Assisted Sensitivity and Specificity Magnetic Resonance Imaging Disease Progression White Matter Unsupervised Machine Learning Brain Mapping
View on PubMed DOI

A manifold learning regularization approach to enhance 3D CT image-based lung nodule classification.

International journal of computer assisted radiology and surgery Nov 25, 2019
PURPOSE: Diagnosis of lung cancer requires radiologists to review every lung nodule in CT images. Such a process can be very time-consuming, and the accuracy is affected by many factors, such as experience of radiologists and available diagnosis time...
Radiographic Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Tomography, X-Ray Computed Sensitivity and Specificity Deep Learning Imaging, Three-Dimensional Lung Neoplasms Solitary Pulmonary Nodule
View on PubMed DOI

The exploration of feature extraction and machine learning for predicting bone density from simple spine X-ray images in a Korean population.

Skeletal radiology Nov 23, 2019
OBJECTIVE: Osteoporosis is hard to detect before it manifests symptoms and complications. In this study, we evaluated machine learning models for identifying individuals with abnormal bone mineral density (BMD) through an analysis of spine X-ray feat...
Sensitivity and Specificity Male Middle Aged Predictive Value of Tests Radiography Retrospective Studies Radiographic Image Interpretation, Computer-Assisted Osteoporosis Spine Republic of Korea Absorptiometry, Photon Female Humans Machine Learning Bone Density
View on PubMed DOI

Machine Learning Interpretation of Extended Human Papillomavirus Genotyping by Onclarity in an Asian Cervical Cancer Screening Population.

Journal of clinical microbiology Nov 22, 2019
This study aimed (i) to compare the performance of the BD Onclarity human papillomavirus (HPV) assay with the Cobas HPV test in identifying cervical intraepithelial neoplasia 2/3 or above (CIN2/3+) in an Asian screening population and (ii) to explore...
Aged, 80 and over Middle Aged Adolescent Young Adult Genotype Adult Papillomavirus Infections Humans Sensitivity and Specificity Early Detection of Cancer Machine Learning Uterine Cervical Neoplasms Asian People Female Genotyping Techniques Aged Uterine Cervical Dysplasia Papillomaviridae
View on PubMed DOI

Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance.

Scientific reports Nov 22, 2019
Identification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to class...
Cognition Unsupervised Machine Learning Brain Mapping Electroencephalography Epilepsy Algorithms Brain Retrospective Studies Sensitivity and Specificity Verbal Behavior Electrocorticography Biomedical Engineering Electrodes, Implanted Electrophysiological Phenomena Memory, Short-Term Datasets as Topic Task Performance and Analysis Evoked Potentials Humans
View on PubMed DOI
Popular Topics
Recent Journals