AIMC Topic: ROC Curve

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A Comparison of Models Predicting One-Year Mortality at Time of Admission.

Journal of pain and symptom management Nov 23, 2021
CONTEXT: Hospitalization provides an opportunity to address end-of-life care (EoLC) preferences if patients at risk of death can be accurately identified while in the hospital. The modified Hospital One-Year Mortality Risk (mHOMR) uses demographic an...
Humans Machine Learning Retrospective Studies Hospitalization Hospital Mortality ROC Curve Logistic Models
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The new SUMPOT to predict postoperative complications using an Artificial Neural Network.

Scientific reports Nov 22, 2021
An accurate assessment of preoperative risk may improve use of hospital resources and reduce morbidity and mortality in high-risk surgical patients. This study aims at implementing an automated surgical risk calculator based on Artificial Neural Netw...
Risk Assessment Postoperative Complications Cohort Studies ROC Curve Predictive Value of Tests Area Under Curve Elective Surgical Procedures Emergency Treatment Humans Risk Factors Neural Networks, Computer Hospitalization Machine Learning Male Prognosis Middle Aged Retrospective Studies Intensive Care Units Female
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Machine learning approach for the prediction of postpartum hemorrhage in vaginal birth.

Scientific reports Nov 19, 2021
Postpartum hemorrhage is the leading cause of maternal morbidity. Clinical prediction of postpartum hemorrhage remains challenging, particularly in the case of a vaginal birth. We studied machine learning models to predict postpartum hemorrhage. Wome...
Models, Statistical Area Under Curve False Positive Reactions Risk ROC Curve Logistic Models Models, Theoretical Support Vector Machine Postpartum Hemorrhage Delivery, Obstetric Labor, Obstetric Tokyo Female Infant, Newborn Reproducibility of Results Young Adult Adult Middle Aged Deep Learning Adolescent Humans Neural Networks, Computer Machine Learning Pregnancy
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The prediction of surgical complications using artificial intelligence in patients undergoing major abdominal surgery: A systematic review.

Surgery Nov 18, 2021
BACKGROUND: Conventional statistics are based on a simple cause-and-effect principle. Postoperative complications, however, have a multifactorial and interrelated etiology. The application of artificial intelligence might be more accurate to predict ...
ROC Curve Humans Artificial Intelligence Algorithms Postoperative Complications
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Can we predict anti-seizure medication response in focal epilepsy using machine learning?

Clinical neurology and neurosurgery Nov 16, 2021
OBJECTIVE: The aim of this study was to evaluate the feasibility of machine learning approach based on clinical factors and diffusion tensor imaging (DTI) to predict anti-seizure medication (ASM) response in focal epilepsy. We hypothesized that ASM r...
Female Anticonvulsants Young Adult Diffusion Tensor Imaging Adult Epilepsies, Partial Male Humans Middle Aged Machine Learning ROC Curve Treatment Outcome Retrospective Studies Predictive Value of Tests
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Predicting 1p/19q co-deletion status from magnetic resonance imaging using deep learning in adult-type diffuse lower-grade gliomas: a discovery and validation study.

Laboratory investigation; a journal of technical methods and pathology Nov 15, 2021
Determination of 1p/19q co-deletion status is important for the classification, prognostication, and personalized therapy in diffuse lower-grade gliomas (LGG). We developed and validated a deep learning imaging signature (DLIS) from preoperative magn...
Humans Prognosis Female Reproducibility of Results Magnetic Resonance Imaging Neoplasm Grading Chromosome Deletion Chromosomes, Human, Pair 1 Chromosomes, Human, Pair 19 Middle Aged Deep Learning ROC Curve Glioma Adult Brain Neoplasms Male
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Machine learning models for screening carotid atherosclerosis in asymptomatic adults.

Scientific reports Nov 15, 2021
Carotid atherosclerosis (CAS) is a risk factor for cardiovascular and cerebrovascular events, but duplex ultrasonography isn't recommended in routine screening for asymptomatic populations according to medical guidelines. We aim to develop machine le...
ROC Curve Models, Theoretical Mass Screening Support Vector Machine Female Aged Male Humans Middle Aged Machine Learning Biomarkers Disease Susceptibility Asymptomatic Diseases Carotid Artery Diseases
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Predictive Analysis and Evaluation Model of Chronic Liver Disease Based on BP Neural Network with Improved Ant Colony Algorithm.

Journal of healthcare engineering Nov 15, 2021
Timely prediction of the mechanism and characteristics of chronic liver disease using next-generation information technology is an effective way to improve the diagnosis rate of chronic liver disease. In this paper, we have proposed a modified backpr...
ROC Curve Principal Component Analysis Liver Diseases Humans Neural Networks, Computer Algorithms
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Explainable machine learning model for predicting the occurrence of postoperative malnutrition in children with congenital heart disease.

Clinical nutrition (Edinburgh, Scotland) Nov 10, 2021
BACKGROUND & AIMS: Malnutrition is persistent in 50%-75% of children with congenital heart disease (CHD) after surgery, and early prediction is crucial for nutritional intervention. The aim of this study was to develop and validate machine learning (...
Clinical Decision Rules Predictive Value of Tests Malnutrition Postoperative Period Heart Defects, Congenital Machine Learning Algorithms Humans Prospective Studies Male Female Postoperative Complications Infant ROC Curve
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Employing phylogenetic tree shape statistics to resolve the underlying host population structure.

BMC bioinformatics Nov 10, 2021
BACKGROUND: Host population structure is a key determinant of pathogen and infectious disease transmission patterns. Pathogen phylogenetic trees are useful tools to reveal the population structure underlying an epidemic. Determining whether a populat...
Algorithms Phylogeny ROC Curve Support Vector Machine Machine Learning
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