AIMC Topic: Logistic Models

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Prospective Assessment of a Symptomatic Cerebral Vasospasm Predictive Neural Network Model.

World neurosurgery Jul 5, 2016
INTRODUCTION: The author introduced a symptomatic cerebral vasospasm (SCV) prediction model built with freeware based on a 91-patient dataset. In a prospective test group of 22 patients at the same hospital, this model outperformed logistic regressio...
Female Reproducibility of Results Aged Male Middle Aged Humans Rupture, Spontaneous Neural Networks, Computer Prospective Studies Cerebral Angiography Aneurysm, Ruptured Intracranial Aneurysm Ultrasonography, Doppler, Transcranial Risk Assessment Logistic Models Subarachnoid Hemorrhage Vasospasm, Intracranial
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Supporting Regularized Logistic Regression Privately and Efficiently.

PloS one Jun 6, 2016
As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects...
Cooperative Behavior Confidentiality Humans Computer Communication Networks Privacy Machine Learning Information Dissemination Logistic Models Computer Security Models, Statistical
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The use of machine learning for the identification of peripheral artery disease and future mortality risk.

Journal of vascular surgery Jun 3, 2016
OBJECTIVE: A key aspect of the precision medicine effort is the development of informatics tools that can analyze and interpret "big data" sets in an automated and adaptive fashion while providing accurate and actionable clinical information. The aim...
Humans Machine Learning Algorithms Decision Support Techniques Linear Models ROC Curve Genomics Logistic Models Peripheral Arterial Disease Predictive Value of Tests Area Under Curve Coronary Angiography Data Mining Ankle Brachial Index Databases, Factual Risk Factors Prognosis Aged Female Male Reproducibility of Results Middle Aged Risk Assessment
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Normal tissue complication probability (NTCP) modelling using spatial dose metrics and machine learning methods for severe acute oral mucositis resulting from head and neck radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology May 27, 2016
BACKGROUND AND PURPOSE: Severe acute mucositis commonly results from head and neck (chemo)radiotherapy. A predictive model of mucositis could guide clinical decision-making and inform treatment planning. We aimed to generate such a model using spatia...
Acute Disease Female Stomatitis Probability Humans Male Radiotherapy Dosage Machine Learning Logistic Models Radiation Injuries Clinical Decision-Making Models, Theoretical Head and Neck Neoplasms
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Developing Artificial Neural Network Models to Predict Functioning One Year After Traumatic Spinal Cord Injury.

Archives of physical medicine and rehabilitation May 18, 2016
OBJECTIVE: To develop mathematical models for predicting level of independence with specific functional outcomes 1 year after discharge from inpatient rehabilitation for spinal cord injury.
Spinal Cord Injuries Physical Therapy Modalities Models, Theoretical Recovery of Function Walking Humans Activities of Daily Living Neural Networks, Computer Reproducibility of Results Retrospective Studies Self Care Female Male Logistic Models
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Models of logistic regression analysis, support vector machine, and back-propagation neural network based on serum tumor markers in colorectal cancer diagnosis.

Genetics and molecular research : GMR May 13, 2016
We evaluated the application of three machine learning algorithms, including logistic regression, support vector machine and back-propagation neural network, for diagnosing congenital heart disease and colorectal cancer. By inspecting related serum t...
Adult Colorectal Neoplasms Biomarkers, Tumor Male Middle Aged Neural Networks, Computer Case-Control Studies Logistic Models Machine Learning CA-125 Antigen Membrane Proteins Humans Algorithms Support Vector Machine Female Aged
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Learning statistical models of phenotypes using noisy labeled training data.

Journal of the American Medical Informatics Association : JAMIA May 12, 2016
OBJECTIVE: Traditionally, patient groups with a phenotype are selected through rule-based definitions whose creation and validation are time-consuming. Machine learning approaches to electronic phenotyping are limited by the paucity of labeled traini...
Models, Statistical Myocardial Infarction Vocabulary, Controlled Medical Informatics Computing Humans Machine Learning Algorithms Phenotype Electronic Health Records Diabetes Mellitus, Type 2 Logistic Models
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Machine-Learning-Based Prediction of a Missed Scheduled Clinical Appointment by Patients With Diabetes.

Journal of diabetes science and technology May 3, 2016
BACKGROUND: About 10% of patients with diabetes discontinue treatment, resulting in the progression of diabetes-related complications and reduced quality of life.
Humans Machine Learning Algorithms Female Male No-Show Patients ROC Curve Logistic Models Diabetes Mellitus Area Under Curve
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Computer-based coding of free-text job descriptions to efficiently identify occupations in epidemiological studies.

Occupational and environmental medicine Apr 21, 2016
BACKGROUND: Mapping job titles to standardised occupation classification (SOC) codes is an important step in identifying occupational risk factors in epidemiological studies. Because manual coding is time-consuming and has moderate reliability, we de...
Job Description Humans Epidemiologic Methods Occupations Software Natural Language Processing United States Occupational Safety and Health Administration Algorithms Reproducibility of Results Epidemiologic Studies Case-Control Studies Industry Logistic Models Carcinoma, Renal Cell United States
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Folded concave penalized learning in identifying multimodal MRI marker for Parkinson's disease.

Journal of neuroscience methods Apr 19, 2016
BACKGROUND: Brain MRI holds promise to gauge different aspects of Parkinson's disease (PD)-related pathological changes. Its analysis, however, is hindered by the high-dimensional nature of the data.
Linear Models Logistic Models Pattern Recognition, Automated Humans Machine Learning Magnetic Resonance Imaging Diffusion Tensor Imaging Algorithms Parkinson Disease Brain Multimodal Imaging Sensitivity and Specificity Image Interpretation, Computer-Assisted
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