AIMC Topic:
Predictive Value of Tests

Clear Filters Showing 1231 to 1240 of 2129 articles

Novel artificial neural network and linear regression based equation for estimating visceral adipose tissue volume.

Clinical nutrition (Edinburgh, Scotland) Feb 14, 2020
BACKGROUND: There is a growing interest in fast and reliable assessment of abdominal visceral adipose tissue (VAT) volume for risk stratification of metabolic disorders. However, imaging based measurement of VAT is costly and limited by scanner avail...
Neural Networks, Computer Female Reproducibility of Results Aged Humans Radiographic Image Interpretation, Computer-Assisted Anthropometry Adiposity United Kingdom Linear Models Male Middle Aged Magnetic Resonance Imaging Predictive Value of Tests Intra-Abdominal Fat
View on PubMed DOI

Development and Validation of a Deep Neural Network for Accurate Evaluation of Endoscopic Images From Patients With Ulcerative Colitis.

Gastroenterology Feb 12, 2020
BACKGROUND & AIMS: There are intra- and interobserver variations in endoscopic assessment of ulcerative colitis (UC) and biopsies are often collected for histologic evaluation. We sought to develop a deep neural network system for consistent, objecti...
Predictive Value of Tests Biopsy Remission Induction Image Interpretation, Computer-Assisted Severity of Illness Index Adolescent Young Adult Female Colon Humans Diagnosis, Computer-Assisted Adult Reproducibility of Results Colonoscopy Treatment Outcome Deep Learning Databases, Factual Male Aged Wound Healing Prospective Studies Aged, 80 and over Colitis, Ulcerative Middle Aged
View on PubMed DOI

The Prediction of Human Abdominal Adiposity Based on the Combination of a Particle Swarm Algorithm and Support Vector Machine.

International journal of environmental research and public health Feb 10, 2020
: Abdominal adiposity is an important risk factor of chronic cardiovascular diseases, thus the prediction of abdominal adiposity and obesity can reduce the risks of contracting such diseases. However, the current prediction models display low accurac...
Diagnosis, Computer-Assisted Support Vector Machine Predictive Value of Tests Obesity, Abdominal Adiposity Humans Algorithms Risk Factors Sensitivity and Specificity
View on PubMed DOI

Detection of carbapenem-resistant Klebsiella pneumoniae on the basis of matrix-assisted laser desorption ionization time-of-flight mass spectrometry by using supervised machine learning approach.

PloS one Feb 6, 2020
BACKGROUND: Carbapenem-resistant Klebsiella pneumoniae (CRKP) is emerging as a significant pathogen causing healthcare-associated infections. Matrix-assisted laser desorption/ionisation mass spectrometry time-of-flight mass spectrometry (MALDI-TOF MS...
Carbapenems Anti-Bacterial Agents Cross Infection Humans Microbial Sensitivity Tests Klebsiella Infections Carbapenem-Resistant Enterobacteriaceae Algorithms Klebsiella pneumoniae Random Amplified Polymorphic DNA Technique Predictive Value of Tests DNA, Bacterial Supervised Machine Learning Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
View on PubMed DOI

Machine learning-based prediction of glioma margin from 5-ALA induced PpIX fluorescence spectroscopy.

Scientific reports Jan 29, 2020
Gliomas are infiltrative brain tumors with a margin difficult to identify. 5-ALA induced PpIX fluorescence measurements are a clinical standard, but expert-based classification models still lack sensitivity and specificity. Here a fully automatic clu...
Humans Machine Learning Computer Simulation Prognosis Pilot Projects Cell Line, Tumor Glioma Biomarkers, Tumor Brain Neoplasms Margins of Excision Cluster Analysis Protoporphyrins Predictive Value of Tests Spectrometry, Fluorescence Aminolevulinic Acid
View on PubMed DOI

Are neural networks the ultimate risk prediction models in patients at high risk of acute myocardial infarction?

European journal of preventive cardiology Jan 28, 2020
Risk Assessment Predictive Value of Tests Myocardial Infarction Humans Neural Networks, Computer
View on PubMed DOI

A machine-learning approach to predicting hypotensive events in ICU settings.

Computers in biology and medicine Jan 24, 2020
BACKGROUND: Predicting hypotension well in advance provides physicians with enough time to respond with proper therapeutic measures. However, the real-time prediction of hypotension with high positive predictive value (PPV) is a challenge. This is du...
Predictive Value of Tests Humans Hypotension Machine Learning Algorithms Intensive Care Units
View on PubMed DOI

Automated body composition analysis of clinically acquired computed tomography scans using neural networks.

Clinical nutrition (Edinburgh, Scotland) Jan 22, 2020
BACKGROUND & AIMS: The quantity and quality of skeletal muscle and adipose tissue is an important prognostic factor for clinical outcomes across several illnesses. Clinically acquired computed tomography (CT) scans are commonly used for quantificatio...
Lumbar Vertebrae Humans Adiposity Neural Networks, Computer Automation Tomography, X-Ray Computed North America Female Adipose Tissue Predictive Value of Tests Middle Aged Body Composition Deep Learning Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Europe Aged Sarcopenia Adult Muscle, Skeletal Male
View on PubMed DOI

Discovering hidden information in biosignals from patients using artificial intelligence.

Korean journal of anesthesiology Jan 16, 2020
Biosignals such as electrocardiogram or photoplethysmogram are widely used for determining and monitoring the medical condition of patients. It was recently discovered that more information could be gathered from biosignals by applying artificial int...
Humans Deep Learning Electrocardiography Predictive Value of Tests Artificial Intelligence Diagnosis, Computer-Assisted
View on PubMed DOI

Deep Learning to Distinguish Benign from Malignant Renal Lesions Based on Routine MR Imaging.

Clinical cancer research : an official journal of the American Association for Cancer Research Jan 14, 2020
PURPOSE: With increasing incidence of renal mass, it is important to make a pretreatment differentiation between benign renal mass and malignant tumor. We aimed to develop a deep learning model that distinguishes benign renal tumors from renal cell c...
Predictive Value of Tests Kidney Neoplasms Carcinoma, Renal Cell Adult Male Middle Aged Deep Learning Child Magnetic Resonance Imaging Diagnosis, Differential Adolescent Child, Preschool Female Humans Aged Neural Networks, Computer Aged, 80 and over Algorithms Young Adult Retrospective Studies
View on PubMed DOI
Popular Topics
Recent Journals