AI Medical Compendium Topic:
Electronic Health Records

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Family history information extraction via deep joint learning.

BMC medical informatics and decision making
Family history (FH) information, including family members, side of family of family members (i.e., maternal or paternal), living status of family members, observations (diseases) of family members, etc., is very important in the decision-making proce...

Family member information extraction via neural sequence labeling models with different tag schemes.

BMC medical informatics and decision making
BACKGROUND: Family history information (FHI) described in unstructured electronic health records (EHRs) is a valuable information source for patient care and scientific researches. Since FHI is usually described in the format of free text, the entire...

Artificial intelligence approaches using natural language processing to advance EHR-based clinical research.

The Journal of allergy and clinical immunology
The wide adoption of electronic health record systems in health care generates big real-world data that open new venues to conduct clinical research. As a large amount of valuable clinical information is locked in clinical narratives, natural languag...

Long Short-Term Memory Recurrent Neural Networks for Multiple Diseases Risk Prediction by Leveraging Longitudinal Medical Records.

IEEE journal of biomedical and health informatics
Individuals suffer from chronic diseases without being identified in time, which brings lots of burden of disease to the society. This paper presents a multiple disease risk prediction method to systematically assess future disease risks for patients...

On Clinical Event Prediction in Patient Treatment Trajectory Using Longitudinal Electronic Health Records.

IEEE journal of biomedical and health informatics
Healthcare process leaves patient treatment trajectory (PTT), described as a sequence of interdependent clinical events affiliated with a large volume of longitudinal therapy and treatment information. Predicting the future clinical event in PTT, as ...

Improving clinical named entity recognition in Chinese using the graphical and phonetic feature.

BMC medical informatics and decision making
BACKGROUND: Clinical Named Entity Recognition is to find the name of diseases, body parts and other related terms from the given text. Because Chinese language is quite different with English language, the machine cannot simply get the graphical and ...

Recent advances in Swedish and Spanish medical entity recognition in clinical texts using deep neural approaches.

BMC medical informatics and decision making
BACKGROUND: Text mining and natural language processing of clinical text, such as notes from electronic health records, requires specific consideration of the specialized characteristics of these texts. Deep learning methods could potentially mitigat...

The impact of extraneous features on the performance of recurrent neural network models in clinical tasks.

Journal of biomedical informatics
Electronic Medical Records (EMR) are a rich source of patient information, including measurements reflecting physiologic signs and administered therapies. Identifying which variables or features are useful in predicting clinical outcomes can be chall...

Incorporating medical code descriptions for diagnosis prediction in healthcare.

BMC medical informatics and decision making
BACKGROUND: Diagnosis aims to predict the future health status of patients according to their historical electronic health records (EHR), which is an important yet challenging task in healthcare informatics. Existing diagnosis prediction approaches m...