AIMC Topic: Logistic Models

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Support Vector Machines and logistic regression to predict temporal artery biopsy outcomes.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie Aug 31, 2018
OBJECTIVE: Support vector machines (SVM) is a newer statistical method that has been reported to be advantageous to traditional logistic regression for clinical classification. We determine if SVM can better predict the results of temporal artery bio...
Humans ROC Curve Logistic Models Temporal Arteries Support Vector Machine Predictive Value of Tests Biopsy Giant Cell Arteritis
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A novel logistic regression model combining semi-supervised learning and active learning for disease classification.

Scientific reports Aug 29, 2018
Traditional supervised learning classifier needs a lot of labeled samples to achieve good performance, however in many biological datasets there is only a small size of labeled samples and the remaining samples are unlabeled. Labeling these unlabeled...
Humans Machine Learning Disease Logistic Models Supervised Machine Learning
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Identifying people at risk of developing type 2 diabetes: A comparison of predictive analytics techniques and predictor variables.

International journal of medical informatics Aug 28, 2018
BACKGROUND: The present study aims to identify the patients at risk of type 2 diabetes (T2D). There is a body of literature that uses machine learning classification algorithms to predict development of T2D among patients. The current study compares ...
Humans Neural Networks, Computer Machine Learning Algorithms Support Vector Machine Predictive Value of Tests Disease Progression Female Diabetes Mellitus, Type 2 Risk Factors Logistic Models Male Mass Screening Middle Aged
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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...
Bayes Theorem Discriminant Analysis Supervised Machine Learning Climate Change Logistic Models Neural Networks, Computer Support Vector Machine Statistics, Nonparametric Algorithms Models, Statistical Pollen Ecosystem Decision Trees Africa Fossils
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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...
Infant, Newborn Young Adult Adult Cohort Studies Logistic Models Machine Learning Fetal Development Retrospective Studies Pregnancy Body Mass Index Infant, Small for Gestational Age Female Smoking Fetal Macrosomia Pregnancy Trimester, Second Gestational Weight Gain Statistics as Topic Humans Nova Scotia Neural Networks, Computer
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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...
Quantitative Trait Loci Genotype Computational Biology Logistic Models Gene Expression Regulation Humans Gene Expression Profiling Gene Regulatory Networks Polymorphism, Single Nucleotide Machine Learning Algorithms
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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...
Logistic Models Area Under Curve Surgical Wound Infection Machine Learning Algorithms Decision Support Techniques Male Humans Risk Assessment Infant ROC Curve Retrospective Studies Female Infant, Newborn Risk Factors
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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...
Supervised Machine Learning Intention Construction Industry Risk-Taking Humans Social Norms Surveys and Questionnaires ROC Curve Logistic Models Decision Trees
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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...
Electronic Health Records Female Reproducibility of Results Aged Middle Aged Case-Control Studies Neural Networks, Computer Deep Learning Aged, 80 and over Algorithms Male Databases, Factual Logistic Models Computer Simulation Area Under Curve Heart Failure Humans Medical Informatics
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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...
Fetus Ultrasonography, Prenatal Perception Diagnosis, Computer-Assisted ROC Curve Congenital Abnormalities Decision Trees Mobile Applications Humans Logistic Models Area Under Curve Algorithms Machine Learning Support Vector Machine Pregnancy Bayes Theorem Health Status Female Regression Analysis Internet Reproducibility of Results Telemedicine
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