AIMC Topic: Logistic Models

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Deep Diabetologist: Learning to Prescribe Hypoglycemic Medications with Recurrent Neural Networks.

Studies in health technology and informatics Jan 1, 2017
In healthcare, applying deep learning models to electronic health records (EHRs) has drawn considerable attention. This sequential nature of EHR data make them wellmatched for the power of Recurrent Neural Network (RNN). In this poster, we propose "D...
Logistic Models Hypoglycemic Agents Diabetes Mellitus Neural Networks, Computer Machine Learning Clinical Decision-Making Learning Humans
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Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes - ELSA-Brasil: accuracy study.

Sao Paulo medical journal = Revista paulista de medicina Jan 1, 2017
CONTEXT AND OBJECTIVE:: Type 2 diabetes is a chronic disease associated with a wide range of serious health complications that have a major impact on overall health. The aims here were to develop and validate predictive models for detecting undiagnos...
Supervised Machine Learning Sensitivity and Specificity Male Female Middle Aged Diabetes Mellitus, Type 2 Humans Reproducibility of Results Brazil Neural Networks, Computer Aged Logistic Models Algorithms Adult Bayes Theorem Computer Simulation Feasibility Studies
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Prediction of pathologic femoral fractures in patients with lung cancer using machine learning algorithms: Comparison of computed tomography-based radiological features with clinical features versus without clinical features.

Journal of orthopaedic surgery (Hong Kong) Jan 1, 2017
PURPOSE: The purpose of this article is to compare the predictive power of two models trained with computed tomography (CT)-based radiological features and both CT-based radiological and clinical features for pathologic femoral fractures in patients ...
Tomography, X-Ray Computed Female Risk Factors Aged Humans Machine Learning Algorithms Lung Neoplasms Logistic Models Odds Ratio Fractures, Spontaneous Femoral Fractures Adult Male Middle Aged ROC Curve
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Evaluation of Machine Learning Methods to Predict Coronary Artery Disease Using Metabolomic Data.

Studies in health technology and informatics Jan 1, 2017
Metabolomic data can potentially enable accurate, non-invasive and low-cost prediction of coronary artery disease. Regression-based analytical approaches however might fail to fully account for interactions between metabolites, rely on a priori selec...
Humans Middle Aged Logistic Models Models, Theoretical Metabolomics Coronary Artery Disease Machine Learning Female Aged Male
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An imaging-based approach predicts clinical outcomes in prostate cancer through a novel support vector machine classification.

Oncotarget Nov 22, 2016
Preoperatively predict the probability of Prostate cancer (PCa) biochemical recurrence (BCR) is of definite clinical relevance. The purpose of this study was to develop an imaging-based approach in the prediction of 3-years BCR through a novel suppor...
Logistic Models Nomograms Treatment Outcome Support Vector Machine Predictive Value of Tests Prostatic Neoplasms Prostatectomy Humans Prognosis Aged Male
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A mobile platform for automated screening of asthma and chronic obstructive pulmonary disease.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
Chronic Obstructive Pulmonary Disease (COPD) and asthma each represent a large proportion of the global disease burden; COPD is the third leading cause of death worldwide and asthma is one of the most prevalent chronic diseases, afflicting over 300 m...
Mass Screening Surveys and Questionnaires Respiratory Function Tests Humans ROC Curve Algorithms Stethoscopes Smartphone Pulmonary Disease, Chronic Obstructive Logistic Models Asthma
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The effects of deep network topology on mortality prediction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
Deep learning has achieved remarkable results in the areas of computer vision, speech recognition, natural language processing and most recently, even playing Go. The application of deep-learning to problems in healthcare, however, has gained attenti...
Mortality Humans Neural Networks, Computer Machine Learning Models, Statistical Female Algorithms Regression Analysis Electronic Health Records Natural Language Processing Reproducibility of Results Odds Ratio Male Logistic Models
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High-accuracy user identification using EEG biometrics.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
We analyze brain waves acquired through a consumer-grade EEG device to investigate its capabilities for user identification and authentication. First, we show the statistical significance of the P300 component in event-related potential (ERP) data fr...
Signal Processing, Computer-Assisted Biometric Identification Evoked Potentials Algorithms Event-Related Potentials, P300 Brain Humans Logistic Models Neural Networks, Computer Electroencephalography Machine Learning Equipment Design
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Generalized Multifactor Dimensionality Reduction (GMDR) Analysis of Drug-Metabolizing Enzyme-Encoding Gene Polymorphisms may Predict Treatment Outcomes in Indian Breast Cancer Patients.

World journal of surgery Jul 1, 2016
BACKGROUND: Prediction of response and toxicity of chemotherapy can help personalize the treatment and choose effective yet non-toxic treatment regimen for a breast cancer patient. Interplay of variations in various drug-metabolizing enzyme (DME)-enc...
Humans Chemotherapy, Adjuvant Polymorphism, Single Nucleotide Female ATP Binding Cassette Transporter, Subfamily B Genotype Breast Neoplasms Cytochrome P-450 CYP2C19 Aged Logistic Models Middle Aged Multifactor Dimensionality Reduction Adult
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Statistical-learning strategies generate only modestly performing predictive models for urinary symptoms following external beam radiotherapy of the prostate: A comparison of conventional and machine-learning methods.

Medical physics May 1, 2016
PURPOSE: Given the paucity of available data concerning radiotherapy-induced urinary toxicity, it is important to ensure derivation of the most robust models with superior predictive performance. This work explores multiple statistical-learning strat...
Aged Aged, 80 and over Male Middle Aged Comorbidity Severity of Illness Index ROC Curve Logistic Models Humans Neural Networks, Computer Machine Learning Prognosis Follow-Up Studies Models, Biological Area Under Curve Multivariate Analysis Prostatic Neoplasms Urination Disorders Prostate Radiotherapy
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