AIMC Topic: Logistic Models

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Using Lexical Chains to Identify Text Difficulty: A Corpus Statistics and Classification Study.

IEEE journal of biomedical and health informatics Dec 6, 2018
Our goal is data-driven discovery of features for text simplification. In this paper, we investigate three types of lexical chains: exact, synonymous, and semantic. A lexical chain links semantically related words in a document. We examine their pote...
Medical Informatics Databases, Factual Semantics Logistic Models Consumer Health Information Support Vector Machine Decision Trees Natural Language Processing Bayes Theorem
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Utility of General and Specific Word Embeddings for Classifying Translational Stages of Research.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Conventional text classification models make a bag-of-words assumption reducing text into word occurrence counts per document. Recent algorithms such as word2vec are capable of learning semantic meaning and similarity between words in an entirely uns...
Humans Algorithms Logistic Models Support Vector Machine Decision Trees Natural Language Processing Bayes Theorem Semantics
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Scalable Electronic Phenotyping For Studying Patient Comorbidities.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Over 75 million Americans have multiple concurrent chronic conditions and medical decision making for these patients is mostly based on retrospective cohort studies. Current methods to generate cohorts of patients with comorbidities are neither scala...
Supervised Machine Learning International Classification of Diseases Diabetes Mellitus, Type 2 Humans Logistic Models Retrospective Studies Chronic Disease Comorbidity Myocardial Infarction
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An Interpretable ICU Mortality Prediction Model Based on Logistic Regression and Recurrent Neural Networks with LSTM units.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Most existing studies used logistic regression to establish scoring systems to predict intensive care unit (ICU) mortality. Machine learning-based approaches can achieve higher prediction accuracy but, unlike the scoring systems, frequently cannot pr...
Risk Assessment Humans Machine Learning Hospital Mortality Neural Networks, Computer Prognosis Logistic Models Databases, Genetic Intensive Care Units Hospitalization
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Application of Machine Learning Methods to Predict Non-Alcoholic Steatohepatitis (NASH) in Non-Alcoholic Fatty Liver (NAFL) Patients.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Non-alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease worldwide. NAFLD patients have excessive liver fat (steatosis), without other liver diseases and without excessive alcohol consumption. NAFLD consists of a spectr...
Hepatitis Alanine Transaminase Aspartate Aminotransferases Liver Function Tests Health Status Humans Decision Trees Biomarkers Supervised Machine Learning Fatty Liver Electronic Health Records Non-alcoholic Fatty Liver Disease Female Logistic Models Disease Progression Risk Factors Liver Cirrhosis Aged Case-Control Studies Male Cohort Studies Middle Aged Diabetes Mellitus, Type 2
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Biomarkers of erosive arthritis in systemic lupus erythematosus: Application of machine learning models.

PloS one Dec 4, 2018
OBJECTIVE: Limited evidences are available on biomarkers to recognize Systemic Lupus erythematosus (SLE) patients at risk to develop erosive arthritis. Anti-citrullinated peptide antibodies (ACPA) have been widely investigated and identified in up to...
Autoantibodies Risk Factors Anti-Citrullinated Protein Antibodies Rheumatoid Factor Humans Decision Trees Adult Arthritis Machine Learning Lupus Erythematosus, Systemic Middle Aged Cross-Sectional Studies Protein Carbamylation Biomarkers Male Cohort Studies Female Ultrasonography Logistic Models
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Machine-learned models using hematological inflammation markers in the prediction of short-term acute coronary syndrome outcomes.

Journal of translational medicine Dec 3, 2018
BACKGROUND: Increased systemic and local inflammation play a vital role in the pathophysiology of acute coronary syndrome. This study aimed to assess the usefulness of selected machine learning methods and hematological markers of inflammation in pre...
Machine Learning Biomarkers Reproducibility of Results Aged Humans Inflammation Models, Theoretical Treatment Outcome Acute Coronary Syndrome Time Factors Hospital Mortality ROC Curve Logistic Models
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A comparison of logistic regression models with alternative machine learning methods to predict the risk of in-hospital mortality in emergency medical admissions via external validation.

Health informatics journal Nov 29, 2018
We compare the performance of logistic regression with several alternative machine learning methods to estimate the risk of death for patients following an emergency admission to hospital based on the patients' first blood test results and physiologi...
Hospitalization Hospital Mortality ROC Curve Logistic Models Humans Machine Learning Emergency Service, Hospital Patient Admission
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A Machine Learning Approach to Predicting Need for Hospitalization for Pediatric Asthma Exacerbation at the Time of Emergency Department Triage.

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine Nov 29, 2018
OBJECTIVES: Pediatric asthma is a leading cause of emergency department (ED) utilization and hospitalization. Earlier identification of need for hospital-level care could triage patients more efficiently to high- or low-resource ED tracks. Existing t...
Retrospective Studies Female Hospitalization Male Humans Machine Learning Emergency Service, Hospital Status Asthmaticus Risk Assessment Adolescent Child Child, Preschool ROC Curve Logistic Models Triage
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A deep learning model for the detection of both advanced and early glaucoma using fundus photography.

PloS one Nov 27, 2018
PURPOSE: To build a deep learning model to diagnose glaucoma using fundus photography.
Image Interpretation, Computer-Assisted Diagnostic Techniques, Ophthalmological Humans Glaucoma Cross-Sectional Studies Disease Progression Deep Learning ROC Curve Logistic Models Fundus Oculi
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