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Medical Informatics

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Exploiting semantic patterns over biomedical knowledge graphs for predicting treatment and causative relations.

Journal of biomedical informatics
BACKGROUND: Identifying new potential treatment options for medical conditions that cause human disease burden is a central task of biomedical research. Since all candidate drugs cannot be tested with animal and clinical trials, in vitro approaches a...

Evaluation of a Novel System to Enhance Clinicians' Recognition of Preadmission Adverse Drug Reactions.

Applied clinical informatics
BACKGROUND: Often unrecognized by providers, adverse drug reactions (ADRs) diminish patients' quality of life, cause preventable admissions and emergency department visits, and increase health care costs.

Label-indicator morpheme growth on LSTM for Chinese healthcare question department classification.

Journal of biomedical informatics
BACKGROUND: Current Chinese medicine has an urgent demand for convenient medical services. When facing a large number of patients, understanding patients' questions automatically and precisely is useful. Different from the high professional medical t...

Unsupervised Medical Entity Recognition and Linking in Chinese Online Medical Text.

Journal of healthcare engineering
Online medical text is full of references to medical entities (MEs), which are valuable in many applications, including medical knowledge-based (KB) construction, decision support systems, and the treatment of diseases. However, the diverse and ambig...

Towards precision informatics of pharmacovigilance: OAE-CTCAE mapping and OAE-based representation and analysis of adverse events in patients treated with cancer drugs.

AMIA ... Annual Symposium proceedings. AMIA Symposium
A critical issue in the usage of cancer drugs is its association with various adverse events (AEs) in some, but not all, patients. The National Cancer Institute (NCI) Common Terminology Criteria for Adverse Events (CTCAE) is a controlled terminology ...

Deep learning for healthcare applications based on physiological signals: A review.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: We have cast the net into the ocean of knowledge to retrieve the latest scientific research on deep learning methods for physiological signals. We found 53 research papers on this topic, published from 01.01.2008 to 31.12.20...

Complex analyses on clinical information systems using restricted natural language querying to resolve time-event dependencies.

Journal of biomedical informatics
PURPOSE: This paper reports on a generic framework to provide clinicians with the ability to conduct complex analyses on elaborate research topics using cascaded queries to resolve internal time-event dependencies in the research questions, as an ext...

ProFUSO: Business process and ontology-based framework to develop ubiquitous computing support systems for chronic patients' management.

Journal of biomedical informatics
New advances in telemedicine, ubiquitous computing, and artificial intelligence have supported the emergence of more advanced applications and support systems for chronic patients. This trend addresses the important problem of chronic illnesses, high...

A hybrid model based on neural networks for biomedical relation extraction.

Journal of biomedical informatics
Biomedical relation extraction can automatically extract high-quality biomedical relations from biomedical texts, which is a vital step for the mining of biomedical knowledge hidden in the literature. Recurrent neural networks (RNNs) and convolutiona...

Qcorp: an annotated classification corpus of Chinese health questions.

BMC medical informatics and decision making
BACKGROUND: Health question-answering (QA) systems have become a typical application scenario of Artificial Intelligent (AI). An annotated question corpus is prerequisite for training machines to understand health information needs of users. Thus, we...