AIMC Topic: ROC Curve

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Improving Young Stroke Prediction by Learning with Active Data Augmenter in a Large-Scale Electronic Medical Claims Database.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Electronic medical claims (EMC) database has been successfully used for predicting occurrences of stroke and a variety of other diseases. However, inadequate predictive performances have been observed in cases of rare occurrences due to both insuffic...
Neural Networks, Computer Machine Learning Forecasting Databases, Factual Adult Middle Aged Stroke ROC Curve Humans Area Under Curve
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Osteosarcoma Patients Classification Using Plain X-Rays and Metabolomic Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Osteosarcoma is the most common type of bone cancer. The primary means of osteosarcoma diagnosis is through evaluating plain x-rays. Using image analysis techniques, features that clinicians use to diagnose osteosarcoma can be quantified and studied ...
Osteosarcoma Radiography X-Rays ROC Curve Humans Image Processing, Computer-Assisted Algorithms Support Vector Machine Sensitivity and Specificity Metabolomics
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Patch-level Tumor Classification in Digital Histopathology Images with Domain Adapted Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Tumor histopathology is a crucial step in cancer diagnosis which involves visual inspection of imaging data to detect the presence of tumor cells among healthy tissues. This manual process can be time-consuming, error-prone, and influenced by the exp...
Humans Area Under Curve Image Interpretation, Computer-Assisted Neural Networks, Computer Histological Techniques Neoplasms Deep Learning ROC Curve
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Predicting Mortality in the Surgical Intensive Care Unit Using Artificial Intelligence and Natural Language Processing of Physician Documentation.

The American surgeon Jul 1, 2018
The purpose of this study was to use natural language processing of physician documentation to predict mortality in patients admitted to the surgical intensive care unit (SICU). The Multiparameter Intelligent Monitoring in Intensive Care III database...
Documentation General Surgery Severity of Illness Index Length of Stay Hospital Mortality ROC Curve United States Predictive Value of Tests Natural Language Processing Critical Care Humans Artificial Intelligence Retrospective Studies Intensive Care Units Electronic Health Records
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Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks.

JAMA ophthalmology Jul 1, 2018
IMPORTANCE: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide. The decision to treat is primarily based on the presence of plus disease, defined as dilation and tortuosity of retinal vessels. However, clinical diagn...
Algorithms Female Infant, Newborn Reproducibility of Results Humans Neural Networks, Computer ROC Curve Image Interpretation, Computer-Assisted Infant, Premature Gestational Age Sensitivity and Specificity Male Infant Deep Learning Retinopathy of Prematurity Photography Retinal Vessels
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Predicting Intensive Care Unit Readmission with Machine Learning Using Electronic Health Record Data.

Annals of the American Thoracic Society Jul 1, 2018
RATIONALE: Patients transferred from the intensive care unit to the wards who are later readmitted to the intensive care unit have increased length of stay, healthcare expenditure, and mortality compared with those who are never readmitted. Improving...
Patient Readmission Illinois Electronic Health Records Female Risk Assessment Male Machine Learning Time Factors Humans Middle Aged Retrospective Studies ROC Curve Critical Illness Follow-Up Studies Intensive Care Units
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The Development of a Machine Learning Inpatient Acute Kidney Injury Prediction Model.

Critical care medicine Jul 1, 2018
OBJECTIVES: To develop an acute kidney injury risk prediction model using electronic health record data for longitudinal use in hospitalized patients.
Algorithms Renal Replacement Therapy Acute Kidney Injury Electronic Health Records Humans Machine Learning ROC Curve Models, Statistical Area Under Curve Creatinine Female Reproducibility of Results Male Middle Aged
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[Comparison of machine learning method and logistic regression model in prediction of acute kidney injury in severely burned patients].

Zhonghua shao shang za zhi = Zhonghua shaoshang zazhi = Chinese journal of burns Jun 20, 2018
To build risk prediction models for acute kidney injury (AKI) in severely burned patients, and to compare the prediction performance of machine learning method and logistic regression model. The clinical data of 157 severely burned patients in Augu...
Burns Organ Dysfunction Scores Explosions Sepsis Machine Learning ROC Curve Logistic Models Acute Kidney Injury Fluid Therapy Humans Hospitalization Sensitivity and Specificity
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Predicting Corticosteroid-Free Biologic Remission with Vedolizumab in Crohn's Disease.

Inflammatory bowel diseases May 18, 2018
BACKGROUND AND AIMS: Vedolizumab (VDZ) is effective for Crohn's disease (CD) but costly and is slow to produce remission. Early knowledge of whether vedolizumab is likely to succeed is valuable for physicians, patients, and insurers.
Biological Products C-Reactive Protein Area Under Curve Crohn Disease Cohort Studies ROC Curve Humans Treatment Outcome Gastrointestinal Agents Young Adult Machine Learning Remission Induction Antibodies, Monoclonal, Humanized Adult Female Adrenal Cortex Hormones Male Middle Aged
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Automated Detection of Clinically Significant Prostate Cancer in mp-MRI Images Based on an End-to-End Deep Neural Network.

IEEE transactions on medical imaging May 1, 2018
Automated methods for detecting clinically significant (CS) prostate cancer (PCa) in multi-parameter magnetic resonance images (mp-MRI) are of high demand. Existing methods typically employ several separate steps, each of which is optimized individua...
Image Interpretation, Computer-Assisted ROC Curve Magnetic Resonance Imaging Humans Prostatic Neoplasms Neural Networks, Computer Prostate Algorithms Male
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