AI Medical Compendium Topic:
Semantics

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SemImput: Bridging Semantic Imputation with Deep Learning for Complex Human Activity Recognition.

Sensors (Basel, Switzerland)
The recognition of activities of daily living (ADL) in smart environments is a well-known and an important research area, which presents the real-time state of humans in pervasive computing. The process of recognizing human activities generally invol...

Distributed representation and one-hot representation fusion with gated network for clinical semantic textual similarity.

BMC medical informatics and decision making
BACKGROUND: Semantic textual similarity (STS) is a fundamental natural language processing (NLP) task which can be widely used in many NLP applications such as Question Answer (QA), Information Retrieval (IR), etc. It is a typical regression problem,...

BioConceptVec: Creating and evaluating literature-based biomedical concept embeddings on a large scale.

PLoS computational biology
A massive number of biological entities, such as genes and mutations, are mentioned in the biomedical literature. The capturing of the semantic relatedness of biological entities is vital to many biological applications, such as protein-protein inter...

Matching patients to clinical trials using semantically enriched document representation.

Journal of biomedical informatics
Recruiting eligible patients for clinical trials is crucial for reliably answering specific questions about medical interventions and evaluation. However, clinical trial recruitment is a bottleneck in clinical research and drug development. Our goal ...

Concept based auto-assignment of healthcare questions to domain experts in online Q&A communities.

International journal of medical informatics
BACKGROUND: Healthcare consumers are increasingly turning to the online health Q&A communities to seek answers for their questions because current general search engines are unable to digest complex health-related questions. Q&A communities are platf...

Evaluating sentence representations for biomedical text: Methods and experimental results.

Journal of biomedical informatics
Text representations ar one of the main inputs to various Natural Language Processing (NLP) methods. Given the fast developmental pace of new sentence embedding methods, we argue that there is a need for a unified methodology to assess these differen...

Relation Extraction from Clinical Narratives Using Pre-trained Language Models.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Natural language processing (NLP) is useful for extracting information from clinical narratives, and both traditional machine learning methods and more-recent deep learning methods have been successful in various clinical NLP tasks. These methods oft...

Using FHIR to Construct a Corpus of Clinical Questions Annotated with Logical Forms and Answers.

AMIA ... Annual Symposium proceedings. AMIA Symposium
This paper describes a novel technique for annotating logical forms and answers for clinical questions by utilizing Fast Healthcare Interoperability Resources (FHIR). Such annotations are widely used in building the semantic parsing models (which aim...

Predicting Adverse Drug-Drug Interactions with Neural Embedding of Semantic Predications.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The identification of drug-drug interactions (DDIs) is important for patient safety; yet, compared to other pharmacovigilance work, a limited amount of research has been conducted in this space. Recent work has successfully applied a method of derivi...