AIMC Topic: Natural Language Processing

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Natural Language Processing in Gastroenterology: Current Applications and Future Directions.

Gastrointestinal endoscopy clinics of North America
Natural language processing (NLP), a branch of artificial intelligence, has rapidly gained importance in health care for converting unstructured clinical data into structured formats, enhancing decision-making, research, and patient care. Gastroenter...

Using natural language processing to identify emergency department patients with incidental lung nodules requiring follow-up.

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
OBJECTIVES: For emergency department (ED) patients, lung cancer may be detected early through incidental lung nodules (ILNs) discovered on chest CTs. However, there are significant errors in the communication and follow-up of incidental findings on E...

Extraction and classification of structured data from unstructured hepatobiliary pathology reports using large language models: a feasibility study compared with rules-based natural language processing.

Journal of clinical pathology
AIMS: Structured reporting in pathology is not universally adopted and extracting elements essential to research often requires expensive and time-intensive manual curation. The accuracy and feasibility of using large language models (LLMs) to extrac...

Factors Associated with Abusive Head Trauma in Young Children Presenting to Emergency Medical Services Using a Large Language Model.

Prehospital emergency care
OBJECTIVES: Abusive head trauma (AHT) is a leading cause of death in young children. Analyses of patient characteristics presenting to Emergency Medical Services (EMS) are often limited to structured data fields. Artificial Intelligence (AI) and Larg...

Natural Language Processing and Social Determinants of Health in Mental Health Research: AI-Assisted Scoping Review.

JMIR mental health
BACKGROUND: The use of natural language processing (NLP) in mental health research is increasing, with a wide range of applications and datasets being investigated.

Automated analysis of spoken language differentiates multiple system atrophy from Parkinson's disease.

Journal of neurology
BACKGROUND AND OBJECTIVES: Patients with synucleinopathies such as multiple system atrophy (MSA) and Parkinson's disease (PD) frequently display speech and language abnormalities. We explore the diagnostic potential of automated linguistic analysis o...

BiomedRAG: A retrieval augmented large language model for biomedicine.

Journal of biomedical informatics
Retrieval-augmented generation (RAG) involves a solution by retrieving knowledge from an established database to enhance the performance of large language models (LLM). , these models retrieve information at the sentence or paragraph level, potential...

Natural language processing to identify suicidal ideation and anhedonia in major depressive disorder.

BMC medical informatics and decision making
BACKGROUND: Anhedonia and suicidal ideation are symptoms of major depressive disorder (MDD) that are not regularly captured in structured scales but may be captured in unstructured clinical notes. Natural language processing (NLP) techniques may be u...

Hierarchical graph-based integration network for propaganda detection in textual news articles on social media.

Scientific reports
During the Covid-19 pandemic, the widespread use of social media platforms has facilitated the dissemination of information, fake news, and propaganda, serving as a vital source of self-reported symptoms related to Covid-19. Existing graph-based mode...

Integrating CNN and Bi-LSTM for protein succinylation sites prediction based on Natural Language Processing technique.

Computers in biology and medicine
Protein succinylation, a post-translational modification wherein a succinyl group (-CO-CH₂-CH₂-CO-) attaches to lysine residues, plays a critical regulatory role in cellular processes. Dysregulated succinylation has been implicated in the onset and p...