AIMC Topic: ROC Curve

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Radiographical assessment of tumour stroma and treatment outcomes using deep learning: a retrospective, multicohort study.

The Lancet. Digital health Jun 1, 2021
BACKGROUND: The tumour stroma microenvironment plays an important part in disease progression and its composition can influence treatment response and outcomes. Histological evaluation of tumour stroma is limited by access to tissue, spatial heteroge...
Tomography, X-Ray Computed Female Stomach Neoplasms Biomarkers, Tumor Male Humans Neural Networks, Computer Prognosis Retrospective Studies Predictive Value of Tests Area Under Curve Radiography Progression-Free Survival Disease-Free Survival Middle Aged Deep Learning China ROC Curve Proportional Hazards Models Stomach Chemotherapy, Adjuvant
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Development of a field artificial intelligence triage tool: Confidence in the prediction of shock, transfusion, and definitive surgical therapy in patients with truncal gunshot wounds.

The journal of trauma and acute care surgery Jun 1, 2021
BACKGROUND: In-field triage tools for trauma patients are limited by availability of information, linear risk classification, and a lack of confidence reporting. We therefore set out to develop and test a machine learning algorithm that can overcome ...
Wounds, Gunshot Shock Injury Severity Score Models, Cardiovascular Trauma Centers Adult Male Risk Assessment ROC Curve Blood Transfusion Emergency Medical Services Triage Feasibility Studies Hemorrhage Artificial Intelligence Thoracic Injuries Retrospective Studies Female Young Adult Humans
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Continuous Prediction of Mortality in the PICU: A Recurrent Neural Network Model in a Single-Center Dataset.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies Jun 1, 2021
OBJECTIVES: Develop, as a proof of concept, a recurrent neural network model using electronic medical records data capable of continuously assessing an individual child's risk of mortality throughout their ICU stay as a proxy measure of severity of i...
Humans Neural Networks, Computer Retrospective Studies Infant Child Hospital Mortality Intensive Care Units, Pediatric ROC Curve
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Predicting Antibiotic Resistance in Hospitalized Patients by Applying Machine Learning to Electronic Medical Records.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America Jun 1, 2021
BACKGROUND: Computerized decision support systems are becoming increasingly prevalent with advances in data collection and machine learning (ML) algorithms. However, they are scarcely used for empiric antibiotic therapy. Here, we predict the antibiot...
Machine Learning Electronic Health Records ROC Curve Humans Logistic Models Drug Resistance, Microbial
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Rib fracture detection in computed tomography images using deep convolutional neural networks.

Medicine May 21, 2021
To evaluate the rib fracture detection performance in computed tomography (CT) images using a software based on a deep convolutional neural network (DCNN) and compare it with the rib fracture diagnostic performance of doctors.We included CT images fr...
Retrospective Studies Tomography, X-Ray Computed Female Aged Aged, 80 and over Humans Software Rib Fractures Deep Learning ROC Curve Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Young Adult Adult Male Middle Aged
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Pathogenic potential assessment of the Shiga toxin-producing by a source attribution-considered machine learning model.

Proceedings of the National Academy of Sciences of the United States of America May 18, 2021
Instead of conventional serotyping and virulence gene combination methods, methods have been developed to evaluate the pathogenic potential of newly emerging pathogens. Among them, the machine learning (ML)-based method using whole-genome sequencing ...
Shiga Toxin 2 Escherichia coli Infections Whole Genome Sequencing Virulence Shiga-Toxigenic Escherichia coli Escherichia coli Proteins Machine Learning Reproducibility of Results ROC Curve Support Vector Machine Humans
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Predicting in-hospital mortality in ICU patients with sepsis using gradient boosting decision tree.

Medicine May 14, 2021
Sepsis is a leading cause of mortality in the intensive care unit. Early prediction of sepsis can reduce the overall mortality rate and cost of sepsis treatment. Some studies have predicted mortality and development of sepsis using machine learning m...
Clinical Decision Rules Male Middle Aged Sepsis Female Adolescent Aged Humans Aged, 80 and over Machine Learning Young Adult Algorithms Adult Intensive Care Units Hospital Mortality ROC Curve Logistic Models Support Vector Machine Decision Trees
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Retinal photograph-based deep learning algorithms for myopia and a blockchain platform to facilitate artificial intelligence medical research: a retrospective multicohort study.

The Lancet. Digital health May 1, 2021
BACKGROUND: By 2050, almost 5 billion people globally are projected to have myopia, of whom 20% are likely to have high myopia with clinically significant risk of sight-threatening complications such as myopic macular degeneration. These are diagnose...
Humans Artificial Intelligence Algorithms Retrospective Studies Reproducibility of Results Biomedical Research Myopia Deep Learning Macular Degeneration Datasets as Topic Proof of Concept Study Blockchain Cohort Studies ROC Curve Area Under Curve Retina
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Deep-learning-based cardiovascular risk stratification using coronary artery calcium scores predicted from retinal photographs.

The Lancet. Digital health May 1, 2021
BACKGROUND: Coronary artery calcium (CAC) score is a clinically validated marker of cardiovascular disease risk. We developed and validated a novel cardiovascular risk stratification system based on deep-learning-predicted CAC from retinal photograph...
Vascular Calcification Coronary Artery Disease Retina United Kingdom Algorithms Republic of Korea Proportional Hazards Models Kaplan-Meier Estimate Female ROC Curve Aged Adult Predictive Value of Tests Male Area Under Curve Cardiovascular Diseases Singapore Middle Aged Risk Assessment Deep Learning Humans
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Deep learning enabled classification of Mayo endoscopic subscore in patients with ulcerative colitis.

European journal of gastroenterology & hepatology May 1, 2021
OBJECTIVE: Previous reports of deep learning-assisted assessment of Mayo endoscopic subscore (MES) in ulcerative colitis have only explored the ability to distinguish disease remission (MES 0/1) from severe disease (MES 2/3) or inactive disease (MES ...
Humans Retrospective Studies Colonoscopy Severity of Illness Index Deep Learning ROC Curve Colitis, Ulcerative Intestinal Mucosa
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