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Logistic Models

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Predictive pollen-based biome modeling using machine learning.

PloS one Aug 23, 2018
This paper investigates suitability of supervised machine learning classification methods for classification of biomes using pollen datasets. We assign modern pollen samples from Africa and Arabia to five biome classes using a previously published Af...
Discriminant Analysis Logistic Models Supervised Machine Learning Pollen Support Vector Machine Climate Change Neural Networks, Computer Fossils Models, Statistical Statistics, Nonparametric Algorithms Decision Trees Ecosystem Bayes Theorem Africa
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Comparison of logistic regression with machine learning methods for the prediction of fetal growth abnormalities: a retrospective cohort study.

BMC pregnancy and childbirth Aug 15, 2018
BACKGROUND: While there is increasing interest in identifying pregnancies at risk for adverse outcome, existing prediction models have not adequately assessed population-based risks, and have been based on conventional regression methods. The objecti...
Female Infant, Newborn Young Adult Adult Cohort Studies Neural Networks, Computer Machine Learning Humans Retrospective Studies Pregnancy Logistic Models Fetal Development Body Mass Index Infant, Small for Gestational Age Smoking Fetal Macrosomia Pregnancy Trimester, Second Gestational Weight Gain Statistics as Topic Nova Scotia
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Improving eQTL Analysis Using a Machine Learning Approach for Data Integration: A Logistic Model Tree Solution.

Journal of computational biology : a journal of computational molecular cell biology Jul 27, 2018
Expression quantitative trait loci (eQTL) analysis is an emerging method for establishing the impact of genetic variations (such as single nucleotide polymorphisms) on the expression levels of genes. Although different methods for evaluating the impa...
Gene Expression Profiling Gene Regulatory Networks Polymorphism, Single Nucleotide Humans Genotype Machine Learning Computational Biology Algorithms Logistic Models Gene Expression Regulation Quantitative Trait Loci
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Enhanced neonatal surgical site infection prediction model utilizing statistically and clinically significant variables in combination with a machine learning algorithm.

American journal of surgery Jul 24, 2018
BACKGROUND: Machine-learning can elucidate complex relationships/provide insight to important variables for large datasets. This study aimed to develop an accurate model to predict neonatal surgical site infections (SSI) using different statistical m...
Retrospective Studies Female Infant, Newborn Risk Factors Male Humans Machine Learning Algorithms Decision Support Techniques Area Under Curve Surgical Wound Infection Risk Assessment Infant ROC Curve Logistic Models
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Factors influencing unsafe behaviors: A supervised learning approach.

Accident; analysis and prevention Jun 18, 2018
Despite its potential, the use of machine learning in safety studies had been limited. Considering machine learning's advantage in predictive accuracy, this study used a supervised learning approach to evaluate the relative importance of different co...
ROC Curve Logistic Models Decision Trees Supervised Machine Learning Intention Construction Industry Risk-Taking Social Norms Humans Surveys and Questionnaires
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A study of generalizability of recurrent neural network-based predictive models for heart failure onset risk using a large and heterogeneous EHR data set.

Journal of biomedical informatics Jun 15, 2018
Recently, recurrent neural networks (RNNs) have been applied in predicting disease onset risks with Electronic Health Record (EHR) data. While these models demonstrated promising results on relatively small data sets, the generalizability and transfe...
Area Under Curve Heart Failure Medical Informatics Middle Aged Case-Control Studies Deep Learning Logistic Models Neural Networks, Computer Algorithms Databases, Factual Computer Simulation Electronic Health Records Female Reproducibility of Results Humans Aged Aged, 80 and over Male
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Fetal health status prediction based on maternal clinical history using machine learning techniques.

Computer methods and programs in biomedicine Jun 14, 2018
BACKGROUND AND OBJECTIVE: Congenital anomalies are seen at 1-3% of the population, probabilities of which are tried to be found out primarily through double, triple and quad tests during pregnancy. Also, ultrasonographical evaluations of fetuses enha...
Reproducibility of Results Ultrasonography, Prenatal Diagnosis, Computer-Assisted ROC Curve Mobile Applications Logistic Models Support Vector Machine Health Status Regression Analysis Humans Machine Learning Algorithms Pregnancy Female Telemedicine Fetus Perception Congenital Abnormalities Decision Trees Area Under Curve Bayes Theorem Internet
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Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers.

Medical physics Jun 13, 2018
PURPOSE: Machine learning classification algorithms (classifiers) for prediction of treatment response are becoming more popular in radiotherapy literature. General Machine learning literature provides evidence in favor of some classifier families (r...
Neoplasms Logistic Models Decision Trees Area Under Curve Chemoradiotherapy Neural Networks, Computer Machine Learning Software Prognosis Humans
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Using machine-learning approaches to predict non-participation in a nationwide general health check-up scheme.

Computer methods and programs in biomedicine May 29, 2018
BACKGROUND: In the time since the launch of a nationwide general health check-up and instruction program in Japan in 2008, interest in the formulation of an effective and efficient strategy to improve the participation rate has been growing. The aim ...
Adult Sensitivity and Specificity Male Middle Aged ROC Curve Databases, Factual Retrospective Studies Female Aged Humans Patient Compliance Machine Learning Japan Logistic Models Algorithms Normal Distribution Support Vector Machine Health Status Area Under Curve
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Comparison of variable selection methods for clinical predictive modeling.

International journal of medical informatics May 21, 2018
OBJECTIVE: Modern machine learning-based modeling methods are increasingly applied to clinical problems. One such application is in variable selection methods for predictive modeling. However, there is limited research comparing the performance of cl...
Adult Cohort Studies Child Logistic Models Humans Machine Learning
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