AI Medical Compendium Topic:
Predictive Value of Tests

Clear Filters Showing 1101 to 1110 of 2129 articles

Radiomic Model for Distinguishing Dissecting Aneurysms from Complicated Saccular Aneurysms on high-Resolution Magnetic Resonance Imaging.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Sep 8, 2020
OBJECTIVE: To build radiomic model in differentiating dissecting aneurysm (DA) from complicated saccular aneurysm (SA) based on high-resolution magnetic resonance imaging (HR-MRI) through machine-learning algorithm.
Predictive Value of Tests Image Interpretation, Computer-Assisted Aortic Dissection Intracranial Aneurysm Machine Learning Retrospective Studies Female Reproducibility of Results Aged Adult Male Middle Aged Magnetic Resonance Imaging Diagnosis, Differential Humans
View on PubMed DOI

Novel and conventional embryo parameters as input data for artificial neural networks: an artificial intelligence model applied for prediction of the implantation potential.

Fertility and sterility Sep 8, 2020
OBJECTIVE: To describe novel embryo features capable of predicting implantation potential as input data for an artificial neural network (ANN) model.
Single Embryo Transfer Oocyte Donation Humans Neural Networks, Computer Blastocyst Pregnancy Rate Retrospective Studies Fertility Fertilization in Vitro Pregnancy Image Interpretation, Computer-Assisted Treatment Outcome Female Time-Lapse Imaging Embryo Implantation Time Factors Infertility Predictive Value of Tests
View on PubMed DOI

Development and validation of a model to predict survival in colorectal cancer using a gradient-boosted machine.

Gut Sep 4, 2020
OBJECTIVE: The success of treatment planning relies critically on our ability to predict the potential benefit of a therapy. In colorectal cancer (CRC), several nomograms are available to predict different outcomes based on the use of tumour specific...
Humans Artificial Intelligence Middle Aged Risk Assessment Predictive Value of Tests Survival Analysis Sigmoidoscopy Prospective Studies Female Aged Colorectal Neoplasms Male
View on PubMed DOI

Stacking models for nearly optimal link prediction in complex networks.

Proceedings of the National Academy of Sciences of the United States of America Sep 4, 2020
Most real-world networks are incompletely observed. Algorithms that can accurately predict which links are missing can dramatically speed up network data collection and improve network model validation. Many algorithms now exist for predicting missin...
Models, Statistical Predictive Value of Tests Social Networking Humans Neural Networks, Computer Machine Learning
View on PubMed DOI

ALICE: a hybrid AI paradigm with enhanced connectivity and cybersecurity for a serendipitous encounter with circulating hybrid cells.

Theranostics Sep 2, 2020
A fully automated and accurate assay of rare cell phenotypes in densely-packed fluorescently-labeled liquid biopsy images remains elusive. Employing a hybrid artificial intelligence (AI) paradigm that combines traditional rule-based morphological ma...
Image Processing, Computer-Assisted Pancreatic Neoplasms Cell Count Reproducibility of Results Humans Predictive Value of Tests Microscopy, Fluorescence Machine Learning Aged Principal Component Analysis Internet of Things Software Biomarkers, Tumor Neoplastic Cells, Circulating Liquid Biopsy Female Male Computer Security Middle Aged
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.
Artificial Intelligence Algorithms Female Reproducibility of Results Aged Humans Lung Neoplasms Solitary Pulmonary Nodule Early Detection of Cancer Predictive Value of Tests Radiologists Sensitivity and Specificity Male Middle Aged Lung Deep Learning Tumor Burden Radiography, Thoracic Radiographic Image Enhancement
View on PubMed DOI

Machine learning-based radiomics analysis in predicting the meningioma grade using multiparametric MRI.

European journal of radiology Aug 28, 2020
PURPOSE: To investigate the prediction performance of radiomic models based on multiparametric MRI in predicting the meningioma grade.
Retrospective Studies ROC Curve Female Predictive Value of Tests Reproducibility of Results Humans Area Under Curve Male Preoperative Care Machine Learning Neoplasm Grading Middle Aged Meningioma Image Interpretation, Computer-Assisted Meningeal Neoplasms Multiparametric Magnetic Resonance Imaging
View on PubMed DOI

Biomarkers of the Response to Immune Checkpoint Inhibitors in Metastatic Urothelial Carcinoma.

Frontiers in immunology Aug 25, 2020
The mechanisms underlying the resistance to immune checkpoint inhibitors (ICIs) therapy in metastatic urothelial carcinoma (mUC) patients are not clear. It is of great significance to discern mUC patients who could benefit from ICI therapy in clinica...
Drug Resistance, Neoplasm Risk Factors Urothelium Biomarkers, Tumor Male Risk Assessment Gene Expression Profiling Humans Treatment Outcome Transcriptome Machine Learning Antibodies, Monoclonal, Humanized Time Factors Decision Support Techniques Urinary Bladder Neoplasms Immune Checkpoint Inhibitors Clinical Decision-Making Predictive Value of Tests B7-H1 Antigen Female Carcinoma Nomograms
View on PubMed DOI

Predicting bovine tuberculosis status of dairy cows from mid-infrared spectral data of milk using deep learning.

Journal of dairy science Aug 20, 2020
Bovine tuberculosis (bTB) is a zoonotic disease in cattle that is transmissible to humans, distributed worldwide, and considered endemic throughout much of England and Wales. Mid-infrared (MIR) analysis of milk is used routinely to predict fat and pr...
Neural Networks, Computer Spectrophotometry, Infrared Scotland Tuberculosis, Bovine England Phenotype Cattle Female Predictive Value of Tests Sensitivity and Specificity Lactation Animals Milk Deep Learning
View on PubMed DOI

Automated quantification of myocardial tissue characteristics from native T mapping using neural networks with uncertainty-based quality-control.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Aug 20, 2020
BACKGROUND: Tissue characterisation with cardiovascular magnetic resonance (CMR) parametric mapping has the potential to detect and quantify both focal and diffuse alterations in myocardial structure not assessable by late gadolinium enhancement. Nat...
Image Interpretation, Computer-Assisted Automation Cardiomyopathies Predictive Value of Tests Uncertainty Humans Bayes Theorem Neural Networks, Computer Reproducibility of Results Myocardium Quality Control Ventricular Function, Left Stroke Volume Case-Control Studies Magnetic Resonance Imaging
View on PubMed DOI
Popular Topics
Recent Journals