AIMC Topic: Medical Records
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Outlier Removal in Model-Based Missing Value Imputation for Medical Datasets.
Journal of healthcare engineering
Feb 4, 2018
Many real-world medical datasets contain some proportion of missing (attribute) values. In general, missing value imputation can be performed to solve this problem, which is to provide estimations for the missing values by a reasoning process based o...
Information extraction from Italian medical reports: An ontology-driven approach.
International journal of medical informatics
Dec 23, 2017
OBJECTIVE: In this work, we propose an ontology-driven approach to identify events and their attributes from episodes of care included in medical reports written in Italian. For this language, shared resources for clinical information extraction are ...
Medical subdomain classification of clinical notes using a machine learning-based natural language processing approach.
BMC medical informatics and decision making
Dec 1, 2017
BACKGROUND: The medical subdomain of a clinical note, such as cardiology or neurology, is useful content-derived metadata for developing machine learning downstream applications. To classify the medical subdomain of a note accurately, we have constru...
A natural language processing challenge for clinical records: Research Domains Criteria (RDoC) for psychiatry.
Journal of biomedical informatics
Oct 16, 2017
POETenceph - Automatic identification of clinical notes indicating encephalopathy using a realist ontology.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Nov 5, 2015
Identifying inpatients with encephalopathy is important. The disorder is prevalent, often missed, and puts patients at risk. We describe POETenceph, natural language processing pipeline, which ranks clinical notes on the extent to which they indicate...
MELLO: Medical lifelog ontology for data terms from self-tracking and lifelog devices.
International journal of medical informatics
Aug 17, 2015
OBJECTIVE: The increasing use of health self-tracking devices is making the integration of heterogeneous data and shared decision-making more challenging. Computational analysis of lifelog data has been hampered by the lack of semantic and syntactic ...
Expert guided natural language processing using one-class classification.
Journal of the American Medical Informatics Association : JAMIA
Jun 10, 2015
INTRODUCTION: Automatically identifying specific phenotypes in free-text clinical notes is critically important for the reuse of clinical data. In this study, the authors combine expert-guided feature (text) selection with one-class classification fo...
Recognition of activities of daily living in healthy subjects using two ad-hoc classifiers.
Biomedical engineering online
Jun 6, 2015
BACKGROUND: Activities of daily living (ADL) are important for quality of life. They are indicators of cognitive health status and their assessment is a measure of independence in everyday living. ADL are difficult to reliably assess using questionna...
Clinical Documents Clustering Based on Medication/Symptom Names Using Multi-View Nonnegative Matrix Factorization.
IEEE transactions on nanobioscience
May 21, 2015
Clinical documents are rich free-text data sources containing valuable medication and symptom information, which have a great potential to improve health care. In this paper, we build an integrating system for extracting medication names and symptom ...
Injury narrative text classification using factorization model.
BMC medical informatics and decision making
May 20, 2015
Narrative text is a useful way of identifying injury circumstances from the routine emergency department data collections. Automatically classifying narratives based on machine learning techniques is a promising technique, which can consequently redu...
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