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Logistic Models

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Predicting the risk of acute care readmissions among rehabilitation inpatients: A machine learning approach.

Journal of biomedical informatics Sep 18, 2018
INTRODUCTION: Readmission from inpatient rehabilitation facilities to acute care hospitals is a serious problem. This study aims to develop a predictive model based on machine learning algorithms to identify patients at high risk of readmission.
Patient Readmission Risk North Carolina Outpatients Rehabilitation Support Vector Machine Longitudinal Studies Regression Analysis Inpatients Preventive Medicine Retrospective Studies Female Hospitalization Aged Sensitivity and Specificity Male Middle Aged ROC Curve Logistic Models Humans Machine Learning Algorithms
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Machine learning based on multi-parametric magnetic resonance imaging to differentiate glioblastoma multiforme from primary cerebral nervous system lymphoma.

European journal of radiology Sep 14, 2018
PURPOSE: To evaluate the performance of a machine learning method based on texture features in multi-parametric magnetic resonance imaging (MRI) to differentiate a glioblastoma multiforme (GBM) from a primary cerebral nervous system lymphoma (PCNSL).
Diagnosis, Differential Humans Glioblastoma Machine Learning Image Enhancement Middle Aged Brain ROC Curve Retrospective Studies Logistic Models Aged Female Lymphoma Adult Magnetic Resonance Imaging Brain Neoplasms Male
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Serum vitamin D deficiency and vitamin D receptor gene polymorphism are associated with increased risk of cardiovascular disease in a Chinese rural population.

Nutrition research (New York, N.Y.) Sep 13, 2018
Several studies have reported a conflicting association between vitamin D deficiency, vitamin D receptor (VDR) polymorphism, and the risk of cardiovascular disease (CVD). We hypothesized that serum 25(OH)D concentrations and single nucleotide polymor...
Asian People Haplotypes Gene Frequency Blood Glucose Adult Triglycerides Rural Population Humans Polymorphism, Single Nucleotide Vitamin D Male Biomarkers Genotype Receptors, Calcitriol Cardiovascular Diseases Female Vitamin D Deficiency Logistic Models Middle Aged Alleles Aged China
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Comparison of logistic regression, support vector machines, and deep learning classifiers for predicting memory encoding success using human intracranial EEG recordings.

Journal of neural engineering Sep 13, 2018
OBJECTIVE: We sought to test the performance of three strategies for binary classification (logistic regression, support vector machines, and deep learning) for the problem of predicting successful episodic memory encoding using direct brain recordin...
Deep Learning Logistic Models Support Vector Machine Predictive Value of Tests Electroencephalography Humans Algorithms Computer Simulation Theta Rhythm Stochastic Processes Memory, Episodic Mental Recall Electrodes, Implanted
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CGPS: A machine learning-based approach integrating multiple gene set analysis tools for better prioritization of biologically relevant pathways.

Journal of genetics and genomics = Yi chuan xue bao Sep 13, 2018
Gene set enrichment (GSE) analyses play an important role in the interpretation of large-scale transcriptome datasets. Multiple GSE tools can be integrated into a single method as obtaining optimal results is challenging due to the plethora of GSE to...
Oligonucleotide Array Sequence Analysis Panobinostat Multiple Myeloma Base Sequence Precursor Cell Lymphoblastic Leukemia-Lymphoma Biosynthetic Pathways Machine Learning Software Antineoplastic Agents Computational Biology Logistic Models Databases, Genetic
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A comparative study of logistic regression based machine learning techniques for prediction of early virological suppression in antiretroviral initiating HIV patients.

BMC medical informatics and decision making Sep 4, 2018
BACKGROUND: Treatment with effective antiretroviral therapy (ART) lowers morbidity and mortality among HIV positive individuals. Effective highly active antiretroviral therapy (HAART) should lead to undetectable viral load within 6 months of initiati...
Antiretroviral Therapy, Highly Active Male HIV Infections Viral Load Anti-HIV Agents Cohort Studies Logistic Models Humans Treatment Outcome Machine Learning Predictive Value of Tests Female CD4 Lymphocyte Count Adult
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Multiparametric ultrasomics of significant liver fibrosis: A machine learning-based analysis.

European radiology Sep 3, 2018
OBJECTIVE: To assess significant liver fibrosis by multiparametric ultrasomics data using machine learning.
Algorithms Decision Support Techniques Prospective Studies Female Adult Humans Neural Networks, Computer Machine Learning Liver Cirrhosis Support Vector Machine Decision Trees Area Under Curve Hepatitis B, Chronic Male Middle Aged Ultrasonography ROC Curve 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 Support Vector Machine Predictive Value of Tests Biopsy Giant Cell Arteritis Temporal Arteries
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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...
Machine Learning Logistic Models Supervised Machine Learning Disease Humans
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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 ...
Logistic Models Neural Networks, Computer Mass Screening Machine Learning Support Vector Machine Algorithms Humans Predictive Value of Tests Female Risk Factors Male Middle Aged Disease Progression Diabetes Mellitus, Type 2
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