AIMC Topic: Machine Learning

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Automated Grading of Gliomas using Deep Learning in Digital Pathology Images: A modular approach with ensemble of convolutional neural networks.

AMIA ... Annual Symposium proceedings. AMIA Symposium Nov 5, 2015
Brain glioma is the most common primary malignant brain tumors in adults with different pathologic subtypes: Lower Grade Glioma (LGG) Grade II, Lower Grade Glioma (LGG) Grade III, and Glioblastoma Multiforme (GBM) Grade IV. The survival and treatment...
Image Processing, Computer-Assisted Machine Learning Glioma Electronic Data Processing Brain Neoplasms Glioblastoma Humans Neural Networks, Computer
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Learning a Severity Score for Sepsis: A Novel Approach based on Clinical Comparisons.

AMIA ... Annual Symposium proceedings. AMIA Symposium Nov 5, 2015
Sepsis is one of the leading causes of death in the United States. Early administration of treatment has been shown to decrease sepsis-related mortality and morbidity. Existing scoring systems such as the Acute Physiology and Chronic Health Evaluatio...
Sepsis Shock, Septic APACHE Machine Learning Humans Electronic Data Processing Prognosis
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Handling Temporality of Clinical Events for Drug Safety Surveillance.

AMIA ... Annual Symposium proceedings. AMIA Symposium Nov 5, 2015
Using longitudinal data in electronic health records (EHRs) for post-marketing adverse drug event (ADE) detection allows for monitoring patients throughout their medical history. Machine learning methods have been shown to be efficient and effective ...
Product Surveillance, Postmarketing Electronic Health Records Drug-Related Side Effects and Adverse Reactions Machine Learning Algorithms Databases, Factual Humans
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Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution.

AMIA ... Annual Symposium proceedings. AMIA Symposium Nov 5, 2015
Clinical studies model the average treatment effect (ATE), but apply this population-level effect to future individuals. Due to recent developments of machine learning algorithms with useful statistical guarantees, we argue instead for modeling the i...
Algorithms Risk Humans Machine Learning
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Finding Cervical Cancer Symptoms in Swedish Clinical Text using a Machine Learning Approach and NegEx.

AMIA ... Annual Symposium proceedings. AMIA Symposium Nov 5, 2015
Detection of early symptoms in cervical cancer is crucial for early treatment and survival. To find symptoms of cervical cancer in clinical text, Named Entity Recognition is needed. In this paper the Clinical Entity Finder, a machine-learning tool tr...
Machine Learning Electronic Health Records Humans Uterine Cervical Neoplasms Natural Language Processing Data Curation Female Sweden
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Recognizing Disjoint Clinical Concepts in Clinical Text Using Machine Learning-based Methods.

AMIA ... Annual Symposium proceedings. AMIA Symposium Nov 5, 2015
Clinical concept recognition (CCR) is a fundamental task in clinical natural language processing (NLP) field. Almost all current machine learning-based CCR systems can only recognize clinical concepts of consecutive words (called consecutive clinical...
Pattern Recognition, Automated Humans Machine Learning Natural Language Processing Semantics Algorithms
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Data-driven Temporal Prediction of Surgical Site Infection.

AMIA ... Annual Symposium proceedings. AMIA Symposium Nov 5, 2015
Analysis of data from Electronic Health Records (EHR) presents unique challenges, in particular regarding nonuniform temporal resolution of longitudinal variables. A considerable amount of patient information is available in the EHR - including blood...
Support Vector Machine Surgical Wound Infection Digestive System Surgical Procedures Machine Learning Electronic Health Records Humans
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Automatic Classification of Structured Product Labels for Pregnancy Risk Drug Categories, a Machine Learning Approach.

AMIA ... Annual Symposium proceedings. AMIA Symposium Nov 5, 2015
With regular expressions and manual review, 18,342 FDA-approved drug product labels were processed to determine if the five standard pregnancy drug risk categories were mentioned in the label. After excluding 81 drugs with multiple-risk categories, 8...
Female Pregnancy Complications Risk Algorithms Pregnancy Drug Labeling Humans Machine Learning
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Machine Learning Approaches for Detecting Diabetic Retinopathy from Clinical and Public Health Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium Nov 5, 2015
INTRODUCTION: Annual eye examinations are recommended for diabetic patients in order to detect diabetic retinopathy and other eye conditions that arise from diabetes. Medically underserved urban communities in the US have annual screening rates that ...
Diabetic Retinopathy Machine Learning Sensitivity and Specificity Humans Medically Underserved Area Public Health Informatics Safety-net Providers Urban Population Nutrition Surveys Retinal Diseases United States Statistics as Topic
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Automated Reconciliation of Radiology Reports and Discharge Summaries.

AMIA ... Annual Symposium proceedings. AMIA Symposium Nov 5, 2015
We study machine learning techniques to automatically identify limb abnormalities (including fractures, dislocations and foreign bodies) from radiology reports. For patients presenting to the Emergency Room (ER) with suspected limb abnormalities (e.g...
Support Vector Machine Natural Language Processing Emergency Service, Hospital Software Diagnostic Errors Patient Discharge Summaries Wounds and Injuries Extremities Radiology Radiology Information Systems Humans Machine Learning
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