AIMC Topic: Natural Language Processing

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Synthetic data for annotation and extraction of family history information from clinical text.

Journal of biomedical semantics
BACKGROUND: The limited availability of clinical texts for Natural Language Processing purposes is hindering the progress of the field. This article investigates the use of synthetic data for the annotation and automated extraction of family history ...

Accuracy of Asthma Computable Phenotypes to Identify Pediatric Asthma at an Academic Institution.

Methods of information in medicine
OBJECTIVES: Asthma is a heterogenous condition with significant diagnostic complexity, including variations in symptoms and temporal criteria. The disease can be difficult for clinicians to diagnose accurately. Properly identifying asthma patients fr...

Conversation-Based Information Delivery Method for Facility Management.

Sensors (Basel, Switzerland)
Facility management platforms are widely used in the facility maintenance phase of the building life cycle. However, a large amount of complex building information affects facility managers' efficiency and user experience in retrieving specific infor...

Improving early diagnosis of rare diseases using Natural Language Processing in unstructured medical records: an illustration from Dravet syndrome.

Orphanet journal of rare diseases
BACKGROUND: The growing use of Electronic Health Records (EHRs) is promoting the application of data mining in health-care. A promising use of big data in this field is to develop models to support early diagnosis and to establish natural history. Dr...

Automatic Classification of the Korean Triage Acuity Scale in Simulated Emergency Rooms Using Speech Recognition and Natural Language Processing: a Proof of Concept Study.

Journal of Korean medical science
BACKGROUND: Rapid triage reduces the patients' stay time at an emergency department (ED). The Korean Triage Acuity Scale (KTAS) is mandatorily applied at EDs in South Korea. For rapid triage, we studied machine learning-based triage systems composed ...

Development and web deployment of an automated neuroradiology MRI protocoling tool with natural language processing.

BMC medical informatics and decision making
BACKGROUND: A systematic approach to MRI protocol assignment is essential for the efficient delivery of safe patient care. Advances in natural language processing (NLP) allow for the development of accurate automated protocol assignment. We aim to de...

Artificial intelligence and the future of life sciences.

Drug discovery today
Over the past few decades, the number of health and 'omics-related data' generated and stored has grown exponentially. Patient information can be collected in real time and explored using various artificial intelligence (AI) tools in clinical trials;...

Semantic Textual Similarity in Japanese Clinical Domain Texts Using BERT.

Methods of information in medicine
BACKGROUND: Semantic textual similarity (STS) captures the degree of semantic similarity between texts. It plays an important role in many natural language processing applications such as text summarization, question answering, machine translation, i...

Language Processing Model Construction and Simulation Based on Hybrid CNN and LSTM.

Computational intelligence and neuroscience
Deep learning is the latest trend of machine learning and artificial intelligence research. As a new field with rapid development over the past decade, it has attracted more and more researchers' attention. Convolutional Neural Network (CNN) model is...

Supporting the classification of patients in public hospitals in Chile by designing, deploying and validating a system based on natural language processing.

BMC medical informatics and decision making
BACKGROUND: In Chile, a patient needing a specialty consultation or surgery has to first be referred by a general practitioner, then placed on a waiting list. The Explicit Health Guarantees (GES in Spanish) ensures, by law, the maximum time to solve ...