AIMC Topic: Electronic Health Records
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Machine learning for phenotyping opioid overdose events.
Journal of biomedical informatics
Apr 25, 2019
OBJECTIVE: To develop machine learning models for classifying the severity of opioid overdose events from clinical data.
Evaluation of a machine learning algorithm for up to 48-hour advance prediction of sepsis using six vital signs.
Computers in biology and medicine
Apr 24, 2019
OBJECTIVE: Sepsis remains a costly and prevalent syndrome in hospitals; however, machine learning systems can increase timely sepsis detection using electronic health records. This study validates a gradient boosted ensemble machine learning tool for...
Predicting childhood obesity using electronic health records and publicly available data.
PloS one
Apr 22, 2019
BACKGROUND: Because of the strong link between childhood obesity and adulthood obesity comorbidities, and the difficulty in decreasing body mass index (BMI) later in life, effective strategies are needed to address this condition in early childhood. ...
Comparison of orthogonal NLP methods for clinical phenotyping and assessment of bone scan utilization among prostate cancer patients.
Journal of biomedical informatics
Apr 20, 2019
OBJECTIVE: Clinical care guidelines recommend that newly diagnosed prostate cancer patients at high risk for metastatic spread receive a bone scan prior to treatment and that low risk patients not receive it. The objective was to develop an automated...
PGxO and PGxLOD: a reconciliation of pharmacogenomic knowledge of various provenances, enabling further comparison.
BMC bioinformatics
Apr 18, 2019
BACKGROUND: Pharmacogenomics (PGx) studies how genomic variations impact variations in drug response phenotypes. Knowledge in pharmacogenomics is typically composed of units that have the form of ternary relationships gene variant - drug - adverse ev...
Neural transfer learning for assigning diagnosis codes to EMRs.
Artificial intelligence in medicine
Apr 12, 2019
OBJECTIVE: Electronic medical records (EMRs) are manually annotated by healthcare professionals and specialized medical coders with a standardized set of alphanumeric diagnosis and procedure codes, specifically from the International Classification o...
A deep learning model incorporating part of speech and self-matching attention for named entity recognition of Chinese electronic medical records.
BMC medical informatics and decision making
Apr 9, 2019
BACKGROUND: The Named Entity Recognition (NER) task as a key step in the extraction of health information, has encountered many challenges in Chinese Electronic Medical Records (EMRs). Firstly, the casual use of Chinese abbreviations and doctors' per...
A fine-grained Chinese word segmentation and part-of-speech tagging corpus for clinical text.
BMC medical informatics and decision making
Apr 9, 2019
BACKGROUND: Chinese word segmentation (CWS) and part-of-speech (POS) tagging are two fundamental tasks of Chinese text processing. They are usually preliminary steps for lots of Chinese natural language processing (NLP) tasks. There have been a large...
A hybrid approach for named entity recognition in Chinese electronic medical record.
BMC medical informatics and decision making
Apr 9, 2019
BACKGROUND: With the rapid spread of electronic medical records and the arrival of medical big data era, the application of natural language processing technology in biomedicine has become a hot research topic.
Evidential MACE prediction of acute coronary syndrome using electronic health records.
BMC medical informatics and decision making
Apr 9, 2019
BACKGROUND: Major adverse cardiac event (MACE) prediction plays a key role in providing efficient and effective treatment strategies for patients with acute coronary syndrome (ACS) during their hospitalizations. Existing prediction models have limita...
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