AIMC Topic: ROC Curve

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Prediction of Major Complications and Readmission After Lumbar Spinal Fusion: A Machine Learning-Driven Approach.

World neurosurgery May 28, 2021
BACKGROUND: Given the significant cost and morbidity of patients undergoing lumbar fusion, accurate preoperative risk-stratification would be of great utility. We aim to develop a machine learning model for prediction of major complications and readm...
Risk Assessment Postoperative Complications ROC Curve Logistic Models Treatment Outcome Lumbar Vertebrae Models, Statistical Patient Readmission Female Predictive Value of Tests Risk Factors Area Under Curve Aged Spinal Fusion Male Middle Aged Humans Machine Learning Algorithms Retrospective Studies
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A deep learning system for detecting diabetic retinopathy across the disease spectrum.

Nature communications May 28, 2021
Retinal screening contributes to early detection of diabetic retinopathy and timely treatment. To facilitate the screening process, we develop a deep learning system, named DeepDR, that can detect early-to-late stages of diabetic retinopathy. DeepDR ...
Aged Severity of Illness Index Deep Learning ROC Curve Diabetes Mellitus, Type 2 Humans Fundus Oculi Diabetic Retinopathy Image Interpretation, Computer-Assisted Datasets as Topic
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Machine learning prediction of sleep stages in dairy cows from heart rate and muscle activity measures.

Scientific reports May 25, 2021
Sleep is important for cow health and shows promise as a tool for assessing welfare, but methods to accurately distinguish between important sleep stages are difficult and impractical to use with cattle in typical farm environments. The objective of ...
Heart Rate Polysomnography Sleep Stages Animals Cattle Neural Networks, Computer ROC Curve Machine Learning Myocardium Models, Biological
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COVID-19 diagnosis by routine blood tests using machine learning.

Scientific reports May 24, 2021
Physicians taking care of patients with COVID-19 have described different changes in routine blood parameters. However, these changes hinder them from performing COVID-19 diagnoses. We constructed a machine learning model for COVID-19 diagnosis that ...
SARS-CoV-2 Aged Sensitivity and Specificity Male Severity of Illness Index ROC Curve Area Under Curve Eosinophils Thorax Machine Learning COVID-19 Biomarkers Tomography, X-Ray Computed Female Humans Serum Albumin Prothrombin Hematologic Tests
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Fast screening of covariates in population models empowered by machine learning.

Journal of pharmacokinetics and pharmacodynamics May 21, 2021
One of the objectives of Pharmacometry (PMX) population modeling is the identification of significant and clinically relevant relationships between parameters and covariates. Here, we demonstrate how this complex selection task could benefit from sup...
Drug Evaluation, Preclinical Pharmacokinetics Humans Neural Networks, Computer Machine Learning Algorithms ROC Curve Support Vector Machine Models, Statistical Bayes Theorem
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Spectroscopic and deep learning-based approaches to identify and quantify cerebral microhemorrhages.

Scientific reports May 21, 2021
Cerebral microhemorrhages (CMHs) are associated with cerebrovascular disease, cognitive impairment, and normal aging. One method to study CMHs is to analyze histological sections (5-40 μm) stained with Prussian blue. Currently, users manually and sub...
Disease Management Spectrum Analysis Deep Learning ROC Curve Humans Image Processing, Computer-Assisted Cerebral Hemorrhage Data Interpretation, Statistical
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Prediction of the risk of C5 palsy after posterior laminectomy and fusion with cervical myelopathy using a support vector machine: an analysis of 184 consecutive patients.

Journal of orthopaedic surgery and research May 21, 2021
BACKGROUND: This study aimed to predict C5 palsy (C5P) after posterior laminectomy and fusion (PLF) with cervical myelopathy (CM) from routinely available variables using a support vector machine (SVM) method.
Laminectomy Cervical Vertebrae Spinal Fusion Multivariate Analysis Spinal Cord Diseases Paralysis Postoperative Complications ROC Curve Logistic Models Support Vector Machine Humans Forecasting Retrospective Studies Female Risk Factors Aged Male Middle Aged
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Analysing wideband absorbance immittance in normal and ears with otitis media with effusion using machine learning.

Scientific reports May 20, 2021
Wideband Absorbance Immittance (WAI) has been available for more than a decade, however its clinical use still faces the challenges of limited understanding and poor interpretation of WAI results. This study aimed to develop Machine Learning (ML) too...
Machine Learning Aged Young Adult Adult Middle Aged Humans Neural Networks, Computer Image Processing, Computer-Assisted Databases as Topic Pressure Statistics as Topic Otitis Media with Effusion Infant Adolescent Child, Preschool Child ROC Curve Ear Radio Waves Acoustic Impedance Tests
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Deep learning predicts cardiovascular disease risks from lung cancer screening low dose computed tomography.

Nature communications May 20, 2021
Cancer patients have a higher risk of cardiovascular disease (CVD) mortality than the general population. Low dose computed tomography (LDCT) for lung cancer screening offers an opportunity for simultaneous CVD risk estimation in at-risk patients. Ou...
Follow-Up Studies Datasets as Topic Aged, 80 and over Coronary Vessels Clinical Trials as Topic Adult Male Image Processing, Computer-Assisted Cardiovascular Diseases Lung Neoplasms Retrospective Studies Middle Aged Electrocardiography Tomography, X-Ray Computed Risk Assessment Humans Mass Screening Female Lung Risk Factors Deep Learning Aged ROC Curve
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Feasibility of predicting allele specific expression from DNA sequencing using machine learning.

Scientific reports May 19, 2021
Allele specific expression (ASE) concerns divergent expression quantity of alternative alleles and is measured by RNA sequencing. Multiple studies show that ASE plays a role in hereditary diseases by modulating penetrance or phenotype severity. Howev...
Humans Bias Feasibility Studies Alleles Machine Learning Gene Expression Regulation ROC Curve Genome, Human Polymorphism, Single Nucleotide Models, Genetic Sequence Analysis, DNA
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