AIMC Topic: Natural Language Processing

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Representation of Social Determinants of Health terminology in medical subject headings: impact of added terms.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: To enhance and evaluate the quality of PubMed search results for Social Determinants of Health (SDoH) through the addition of new SDoH terms to Medical Subject Headings (MeSH).

Adapting Large Language Models for Automated Summarisation of Electronic Medical Records in Clinical Coding.

Studies in health technology and informatics
Encapsulating a patient's clinical narrative into a condensed, informative summary is indispensable to clinical coding. The intricate nature of the clinical text makes the summarisation process challenging for clinical coders. Recent developments in ...

Building a Natural Language Interface for FHIR Clinical Terminology Server.

Studies in health technology and informatics
While Fast Healthcare Interoperability Resources (FHIR) clinical terminology server enables quick and easy search and retrieval of coded medical data, it still has some drawbacks. When searching, any typographical errors, variations in word forms, or...

A review of feature selection strategies utilizing graph data structures and Knowledge Graphs.

Briefings in bioinformatics
Feature selection in Knowledge Graphs (KGs) is increasingly utilized in diverse domains, including biomedical research, Natural Language Processing (NLP), and personalized recommendation systems. This paper delves into the methodologies for feature s...

Artificial intelligence classifies primary progressive aphasia from connected speech.

Brain : a journal of neurology
Neurodegenerative dementia syndromes, such as primary progressive aphasias (PPA), have traditionally been diagnosed based, in part, on verbal and non-verbal cognitive profiles. Debate continues about whether PPA is best divided into three variants an...

Biomedical knowledge graph-optimized prompt generation for large language models.

Bioinformatics (Oxford, England)
MOTIVATION: Large language models (LLMs) are being adopted at an unprecedented rate, yet still face challenges in knowledge-intensive domains such as biomedicine. Solutions such as pretraining and domain-specific fine-tuning add substantial computati...

ChatMol: interactive molecular discovery with natural language.

Bioinformatics (Oxford, England)
MOTIVATION: Natural language is poised to become a key medium for human-machine interactions in the era of large language models. In the field of biochemistry, tasks such as property prediction and molecule mining are critically important yet technic...

Triangulating evidence in health sciences with Annotated Semantic Queries.

Bioinformatics (Oxford, England)
MOTIVATION: Integrating information from data sources representing different study designs has the potential to strengthen evidence in population health research. However, this concept of evidence "triangulation" presents a number of challenges for s...