AIMC Topic: Logistic Models

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Quantitative computed tomography imaging-based classification of cement dust-exposed subjects with an artificial neural network technique.

Computers in biology and medicine Dec 21, 2021
BACKGROUND AND OBJECTIVE: Cement dust exposure is likely to affect the structural and functional alterations in segmental airways and parenchymal lungs. This study develops an artificial neural network (ANN) model for identifying cement dust-exposed ...
Neural Networks, Computer Tomography, X-Ray Computed Logistic Models Dust Humans Support Vector Machine
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Score and Correlation Coefficient-Based Feature Selection for Predicting Heart Failure Diagnosis by Using Machine Learning Algorithms.

Computational and mathematical methods in medicine Dec 20, 2021
Cardiovascular disease (CVD) is one of the most common causes of death that kills approximately 17 million people annually. The main reasons behind CVD are myocardial infarction and the failure of the heart to pump blood normally. Doctors could diagn...
Female Decision Trees Aged Aged, 80 and over Heart Failure Humans Algorithms Computational Biology Middle Aged Heart Disease Risk Factors Adult Neural Networks, Computer Databases, Factual Chi-Square Distribution Logistic Models Diagnosis, Computer-Assisted Male Machine Learning Electronic Health Records Support Vector Machine
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Variance-based global sensitivity analysis for rear-end crash investigation using deep learning.

Accident; analysis and prevention Dec 8, 2021
Traffic accidents are rare events with inconsistent spatial and temporal dimensions; thus, accident injury severity (INJ-S) analysis faces a significant challenge in its classification and data stability. While classical statistical models have limit...
Deep Learning Logistic Models Models, Statistical Accidents, Traffic Humans Machine Learning
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Using Convolutional Neural Networks to Measure the Physiological Age of Caenorhabditis elegans.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2021
Caenorhabditis elegans (C. elegans) is a popular and excellent model for studies of aging due to its short lifespan. Methods for precisely measuring the physiological age of C. elegans are critically needed, especially for antiaging drug screening an...
Logistic Models Microscopy Linear Models Caenorhabditis elegans Aging Image Processing, Computer-Assisted Computational Biology Neural Networks, Computer Animals
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NegStacking: Drug-Target Interaction Prediction Based on Ensemble Learning and Logistic Regression.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2021
Drug-target interactions (DTIs) identification is an important issue of drug research, and many methods proposed to predict potential DTIs based on machine learning treat it as a binary classification problem. However, the number of known interacting...
Logistic Models Drug Development Computer Simulation Computational Biology Machine Learning
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Optimizing hepatitis B virus screening in the United States using a simple demographics-based model.

Hepatology (Baltimore, Md.) Dec 7, 2021
BACKGROUND AND AIMS: Chronic hepatitis B (CHB) affects >290 million persons globally, and only 10% have been diagnosed, presenting a severe gap that must be addressed. We developed logistic regression (LR) and machine learning (ML; random forest) mod...
Hepatitis B, Chronic Patient Selection Hispanic or Latino Sex Factors Nutrition Surveys United States Mass Screening Demography Black People Birth Cohort Epidemiological Models Humans White People Black or African American Machine Learning Asian ROC Curve Logistic Models Female Male
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Comparative Analysis for Prediction of Kidney Disease Using Intelligent Machine Learning Methods.

Computational and mathematical methods in medicine Dec 3, 2021
Chronic kidney disease (CKD) is a major burden on the healthcare system because of its increasing prevalence, high risk of progression to end-stage renal disease, and poor morbidity and mortality prognosis. It is rapidly becoming a global health cris...
Early Diagnosis Computational Biology Bangladesh Humans Logistic Models Renal Insufficiency, Chronic Machine Learning Decision Trees Databases, Factual
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A high-resolution trajectory data driven method for real-time evaluation of traffic safety.

Accident; analysis and prevention Dec 2, 2021
Real-time safety evaluation is essential for developing proactive safety management strategy and improving the overall traffic safety. This paper proposes a method for real-time evaluation of road safety, in which traffic states and conflicts are com...
Safety Logistic Models Humans Support Vector Machine Machine Learning Accidents, Traffic Research Design
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A Comparison among Different Machine Learning Pretest Approaches to Predict Stress-Induced Ischemia at PET/CT Myocardial Perfusion Imaging.

Computational and mathematical methods in medicine Nov 27, 2021
Traditional approach for predicting coronary artery disease (CAD) is based on demographic data, symptoms such as chest pain and dyspnea, and comorbidity related to cardiovascular diseases. Usually, these variables are analyzed by logistic regression ...
Aged Male Middle Aged Logistic Models Support Vector Machine Cohort Studies Computational Biology Machine Learning Algorithms Female Humans Myocardial Perfusion Imaging Positron Emission Tomography Computed Tomography Exercise Test Coronary Artery Disease Decision Trees Myocardial Ischemia Predictive Value of Tests Bayes Theorem
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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...
Logistic Models Humans Machine Learning Hospital Mortality ROC Curve Retrospective Studies Hospitalization
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