AIMC Topic:
ROC Curve

Clear Filters Showing 1641 to 1650 of 3214 articles

Impact of radiomics on the breast ultrasound radiologist's clinical practice: From lumpologist to data wrangler.

European journal of radiology Jul 30, 2020
OBJECTIVE: The study aims to assess the impact of radiomics in the clinical practice of breast ultrasound, to determine which lesions are undetermined by the software, and to discuss the future of the radiologist's role.
Humans Artificial Intelligence Software Female Physician's Role Phyllodes Tumor Sensitivity and Specificity Breast Neoplasms Radiologists ROC Curve Biopsy Diagnosis, Differential Ultrasonography, Mammary Breast Fibroadenoma
View on PubMed DOI

Artificial neural networks improve early outcome prediction and risk classification in out-of-hospital cardiac arrest patients admitted to intensive care.

Critical care (London, England) Jul 30, 2020
BACKGROUND: Pre-hospital circumstances, cardiac arrest characteristics, comorbidities and clinical status on admission are strongly associated with outcome after out-of-hospital cardiac arrest (OHCA). Early prediction of outcome may inform prognosis,...
Humans Neural Networks, Computer Prognosis Middle Aged Risk Assessment ROC Curve Critical Care Hypothermia, Induced Female Reproducibility of Results Hospitalization Aged Male Out-of-Hospital Cardiac Arrest
View on PubMed DOI

A Comparison of Three-Dimensional Speckle Tracking Echocardiography Parameters in Predicting Left Ventricular Remodeling.

Journal of healthcare engineering Jul 30, 2020
Three-dimensional speckle tracking echocardiography (3D STE) is an emerging noninvasive method for predicting left ventricular remodeling (LVR) after acute myocardial infarction (AMI). Previous studies analyzed the predictive value of 3D STE with tra...
Myocardial Infarction Heart Ventricles Ventricular Remodeling Ventricular Dysfunction, Left Echocardiography Humans Risk Factors Models, Statistical Middle Aged Machine Learning Aged Predictive Value of Tests ROC Curve Female Adult Area Under Curve Reproducibility of Results Imaging, Three-Dimensional Sensitivity and Specificity Coronary Angiography Male Percutaneous Coronary Intervention
View on PubMed DOI

Soft Tissue Sarcoma: Preoperative MRI-Based Radiomics and Machine Learning May Be Accurate Predictors of Histopathologic Grade.

AJR. American journal of roentgenology Jul 29, 2020
The purpose of this study was to assess the value of radiomics features for differentiating soft tissue sarcomas (STSs) of different histopathologic grades. The T1-weighted and fat-suppressed T2-weighted MR images of 70 STSs of varying grades (35 l...
Sarcoma Soft Tissue Neoplasms ROC Curve Magnetic Resonance Imaging Predictive Value of Tests Neoplasm Grading Humans Machine Learning Retrospective Studies Female Aged Adult Male Middle Aged
View on PubMed DOI

Screening of Parkinsonian subtle fine-motor impairment from touchscreen typing via deep learning.

Scientific reports Jul 28, 2020
Fine-motor impairment (FMI) is progressively expressed in early Parkinson's Disease (PD) patients and is now known to be evident in the immediate prodromal stage of the condition. The clinical techniques for detecting FMI may not be robust enough and...
Mass Screening Parkinson Disease Middle Aged Self Report Deep Learning Confidence Intervals Cohort Studies Humans ROC Curve Motor Activity Female Smartphone Male
View on PubMed DOI

Signal Peptides Generated by Attention-Based Neural Networks.

ACS synthetic biology Jul 27, 2020
Short (15-30 residue) chains of amino acids at the amino termini of expressed proteins known as signal peptides (SPs) specify secretion in living cells. We trained an attention-based neural network, the Transformer model, on data from all available o...
Bacillus subtilis Databases, Protein Area Under Curve Bacterial Proteins Protein Sorting Signals Machine Learning ROC Curve
View on PubMed DOI

Inexpensive, non-invasive biomarkers predict Alzheimer transition using machine learning analysis of the Alzheimer's Disease Neuroimaging (ADNI) database.

PloS one Jul 27, 2020
The Alzheimer's Disease Neuroimaging (ADNI) database is an expansive undertaking by government, academia, and industry to pool resources and data on subjects at various stage of symptomatic severity due to Alzheimer's disease. As expected, magnetic r...
Humans Machine Learning Databases, Factual Alzheimer Disease Biomarkers Neuroimaging Disease Progression Brain Apolipoprotein A-V ROC Curve Magnetic Resonance Imaging Principal Component Analysis Area Under Curve
View on PubMed DOI

Prediction of 1-Year Mortality from Acute Myocardial Infarction Using Machine Learning.

The American journal of cardiology Jul 26, 2020
Risk stratification at hospital discharge could be instrumental in guiding postdischarge care. In this study, the risk models for 1-year mortality using machine learning (ML) were evaluated for guiding management of acute myocardial infarction (AMI) ...
Time Factors ROC Curve Logistic Models Predictive Value of Tests Registries Myocardial Infarction Aged Aged, 80 and over Male Middle Aged Algorithms Risk Assessment Humans Republic of Korea Machine Learning Female Risk Factors
View on PubMed DOI

Supervised machine learning for the early prediction of acute respiratory distress syndrome (ARDS).

Journal of critical care Jul 24, 2020
PURPOSE: Acute respiratory distress syndrome (ARDS) is a serious respiratory condition with high mortality and associated morbidity. The objective of this study is to develop and evaluate a novel application of gradient boosted tree models trained on...
Early Diagnosis ROC Curve Respiratory Distress Syndrome Area Under Curve Supervised Machine Learning Critical Care Adult Male Middle Aged Adolescent Humans Databases, Factual Retrospective Studies Intensive Care Units Female Risk Factors Aged Young Adult
View on PubMed DOI

The effect of deep convolutional neural networks on radiologists' performance in the detection of hip fractures on digital pelvic radiographs.

European journal of radiology Jul 23, 2020
PURPOSE: The purpose of our study is to develop deep convolutional neural network (DCNN) for detecting hip fractures using CT and MRI as a gold standard, and to evaluate the diagnostic performance of 7 readers with and without DCNN.
ROC Curve Image Processing, Computer-Assisted Magnetic Resonance Imaging Area Under Curve Pelvis Aged, 80 and over Male Middle Aged Humans Deep Learning Hip Fractures Neural Networks, Computer Radiographic Image Enhancement Tomography, X-Ray Computed Radiography, Abdominal Female Aged
View on PubMed DOI
Popular Topics
Recent Journals