AIMC Topic: Machine Learning

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Clinical Word Sense Disambiguation with Interactive Search and Classification.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 10, 2017
Resolving word ambiguity in clinical text is critical for many natural language processing applications. Effective word sense disambiguation (WSD) systems rely on training a machine learning based classifier with abundant clinical text that is accura...
Models, Theoretical Humans Natural Language Processing Machine Learning Problem-Based Learning Algorithms
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Learning Effective Treatment Pathways for Type-2 Diabetes from a clinical data warehouse.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 10, 2017
Treatment guidelines for management of type-2 diabetes mellitus (T2DM) are controversial because existing evidence from randomized clinical trials do not address many important clinical questions. Data from Electronic Medical Records (EMRs) has been ...
Metformin Machine Learning Diabetes Mellitus, Type 2 Proportional Hazards Models Electronic Health Records Hypoglycemic Agents Critical Pathways Female Glycated Hemoglobin Consolidation Chemotherapy Sitagliptin Phosphate Humans Aged Adult Male Middle Aged
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Classification-by-Analogy: Using Vector Representations of Implicit Relationships to Identify Plausibly Causal Drug/Side-effect Relationships.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 10, 2017
An important aspect of post-marketing drug surveillance involves identifying potential side-effects utilizing adverse drug event (ADE) reporting systems and/or Electronic Health Records. These data are noisy, necessitating identified drug/ADE associa...
Adverse Drug Reaction Reporting Systems Product Surveillance, Postmarketing ROC Curve Humans Models, Theoretical Machine Learning Support Vector Machine Electronic Health Records Drug-Related Side Effects and Adverse Reactions
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Controlling testing volume for respiratory viruses using machine learning and text mining.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 10, 2017
Viral testing for pediatric inpatients with respiratory symptoms is common, with considerable associated charges. In an attempt to reduce testing volumes, we studied whether data available at the time of admission could aid in identifying children wi...
Hospitalization Sensitivity and Specificity Male Infant Adolescent Child, Preschool Child ROC Curve Machine Learning Retrospective Studies Respiratory Tract Infections Electronic Health Records Humans Virus Diseases Female Viruses Models, Theoretical Decision Trees Data Mining
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Accelerating Chart Review Using Automated Methods on Electronic Health Record Data for Postoperative Complications.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 10, 2017
Manual Chart Review (MCR) is an important but labor-intensive task for clinical research and quality improvement. In this study, aiming to accelerate the process of extracting postoperative outcomes from medical charts, we developed an automated post...
Surgical Wound Infection Medical Audit Machine Learning Algorithms Electronic Health Records Postoperative Complications Sepsis Shock, Septic Pneumonia Urinary Tract Infections Humans
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Automatic data source identification for clinical trial eligibility criteria resolution.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 10, 2017
Clinical trial coordinators refer to both structured and unstructured sources of data when evaluating a subject for eligibility. While some eligibility criteria can be resolved using structured data, some require manual review of clinical notes. An i...
Patient Selection Heart Failure Information Storage and Retrieval Clinical Trials as Topic Eligibility Determination Machine Learning Electronic Health Records Leukemia, Lymphocytic, Chronic, B-Cell Natural Language Processing Humans
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Resource Classification for Medical Questions.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 10, 2017
We present an approach for manually and automatically classifying the resource type of medical questions. Three types of resources are considered: patient-specific, general knowledge, and research. Using this approach, an automatic question answering...
Semantics Information Seeking Behavior Hypersensitivity Natural Language Processing Datasets as Topic Information Storage and Retrieval Humans Machine Learning Algorithms
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Predicting Prolonged Stay in the ICU Attributable to Bleeding in Patients Offered Plasma Transfusion.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 10, 2017
In blood transfusion studies, plasma transfusion (PPT) and bleeding are known to be associated with risk of prolonged ICU length of stay (ICU-LOS). However, as patients can show significant heterogeneity in response to a treatment, there might exists...
Humans Aged, 80 and over Male Middle Aged Length of Stay Machine Learning Intensive Care Units Female Aged Risk Blood Transfusion Regression Analysis Hemorrhage
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Bayesian Machine Learning Techniques for revealing complex interactions among genetic and clinical factors in association with extra-intestinal Manifestations in IBD patients.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 10, 2017
The objective of the study is to assess the predictive performance of three different techniques as classifiers for extra-intestinal manifestations in 152 patients with Crohn's disease. Naïve Bayes, Bayesian Additive Regression Trees and Bayesian Net...
Polymorphism, Genetic Female Risk Factors Male Genetic Predisposition to Disease Models, Statistical Bayes Theorem Crohn Disease Data Mining Humans Machine Learning Algorithms
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Integrated Machine Learning Approaches for Predicting Ischemic Stroke and Thromboembolism in Atrial Fibrillation.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 10, 2017
Atrial fibrillation (AF) is a common cardiac rhythm disorder, which increases the risk of ischemic stroke and other thromboembolism (TE). Accurate prediction of TE is highly valuable for early intervention to AF patients. However, the prediction perf...
Computer Simulation Prognosis Female Risk Factors Models, Biological Male Humans Atrial Fibrillation Area Under Curve Machine Learning Brain Ischemia Registries Thromboembolism Stroke
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