AIMC Topic: ROC Curve

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Internal and External Validation of a Machine Learning Risk Score for Acute Kidney Injury.

JAMA network open Aug 3, 2020
IMPORTANCE: Acute kidney injury (AKI) is associated with increased morbidity and mortality in hospitalized patients. Current methods to identify patients at high risk of AKI are limited, and few prediction models have been externally validated.
Aged, 80 and over Adult Male Middle Aged Risk Assessment ROC Curve Models, Statistical Retrospective Studies Acute Kidney Injury Female Risk Factors Aged Humans Machine Learning
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Computational discrimination between natural images based on gaze during mental imagery.

Scientific reports Aug 3, 2020
When retrieving image from memory, humans usually move their eyes spontaneously as if the image were in front of them. Such eye movements correlate strongly with the spatial layout of the recalled image content and function as memory cues facilitatin...
ROC Curve Area Under Curve Photic Stimulation Humans Fixation, Ocular Female Mental Recall Neural Networks, Computer Adult Imagery, Psychotherapy Male Eye Movements
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Robust Estimation of Breast Cancer Incidence Risk in Presence of Incomplete or Inaccurate Information.

Asian Pacific journal of cancer prevention : APJCP Aug 1, 2020
PURPOSE: To evaluate the robustness of multiple machine learning classifiers for breast cancer risk estimation in the presence of incomplete or inaccurate information.
Humans Neural Networks, Computer Machine Learning Prognosis Breast Neoplasms Middle Aged Incidence ROC Curve United States Female Aged Aged, 80 and over Adult Follow-Up Studies Data Interpretation, Statistical
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Multi-view secondary input collaborative deep learning for lung nodule 3D segmentation.

Cancer imaging : the official publication of the International Cancer Imaging Society Aug 1, 2020
BACKGROUND: Convolutional neural networks (CNNs) have been extensively applied to two-dimensional (2D) medical image segmentation, yielding excellent performance. However, their application to three-dimensional (3D) nodule segmentation remains a chal...
Deep Learning ROC Curve Imaging, Three-Dimensional Image Processing, Computer-Assisted Multiple Pulmonary Nodules Humans Neural Networks, Computer Tomography, X-Ray Computed
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Explainable artificial intelligence model to predict acute critical illness from electronic health records.

Nature communications Jul 31, 2020
Acute critical illness is often preceded by deterioration of routinely measured clinical parameters, e.g., blood pressure and heart rate. Early clinical prediction is typically based on manually calculated screening metrics that simply weigh these pa...
Humans Heart Rate Artificial Intelligence Early Diagnosis Sepsis Acute Lung Injury Prognosis ROC Curve Acute Kidney Injury Blood Pressure Critical Illness Area Under Curve Electronic Health Records Acute Disease
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Prediction of the development of acute kidney injury following cardiac surgery by machine learning.

Critical care (London, England) Jul 31, 2020
BACKGROUND: Cardiac surgery-associated acute kidney injury (CSA-AKI) is a major complication that results in increased morbidity and mortality after cardiac surgery. Most established prediction models are limited to the analysis of nonlinear relation...
Postoperative Complications ROC Curve Models, Statistical Cardiac Surgical Procedures Humans Aged Machine Learning Male Retrospective Studies Middle Aged Acute Kidney Injury Risk Assessment Female Reproducibility of Results
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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 Physician's Role Software Sensitivity and Specificity Phyllodes Tumor Female Radiologists Breast Neoplasms Biopsy ROC Curve Ultrasonography, Mammary Diagnosis, Differential Breast Fibroadenoma
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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,...
Out-of-Hospital Cardiac Arrest Risk Assessment ROC Curve Critical Care Hypothermia, Induced Humans Neural Networks, Computer Prognosis Female Reproducibility of Results Hospitalization Aged Male Middle Aged
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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...
Ventricular Dysfunction, Left Percutaneous Coronary Intervention Myocardial Infarction Heart Ventricles Ventricular Remodeling Male Imaging, Three-Dimensional Humans Echocardiography Models, Statistical Machine Learning Middle Aged Predictive Value of Tests Female ROC Curve Area Under Curve Reproducibility of Results Risk Factors Coronary Angiography Aged Adult Sensitivity and Specificity
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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...
Middle Aged ROC Curve Magnetic Resonance Imaging Predictive Value of Tests Neoplasm Grading Sarcoma Soft Tissue Neoplasms Retrospective Studies Female Aged Adult Male Humans Machine Learning
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