AIMC Topic: Natural Language Processing

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A natural language processing algorithm accurately classifies steatotic liver disease pathology to estimate the risk of cirrhosis.

Hepatology communications
BACKGROUND: Histopathology remains the gold standard for diagnosing and staging metabolic dysfunction-associated steatotic liver disease (MASLD). The feasibility of studying MASLD progression in electronic medical records based on histological featur...

A deep learning approach for Named Entity Recognition in Urdu language.

PloS one
Named Entity Recognition (NER) is a natural language processing task that has been widely explored for different languages in the recent decade but is still an under-researched area for the Urdu language due to its rich morphology and language comple...

Automating sedation state assessments using natural language processing.

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
INTRODUCTION: Common goals for procedural sedation are to control pain and ensure the patient is not moving to an extent that is impeding safe progress or completion of the procedure. Clinicians perform regular assessments of the adequacy of procedur...

Identification of pancreatic cancer risk factors from clinical notes using natural language processing.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
OBJECTIVES: Screening for pancreatic ductal adenocarcinoma (PDAC) is considered in high-risk individuals (HRIs) with established PDAC risk factors, such as family history and germline mutations in PDAC susceptibility genes. Accurate assessment of ris...

Model tuning or prompt Tuning? a study of large language models for clinical concept and relation extraction.

Journal of biomedical informatics
OBJECTIVE: To develop soft prompt-based learning architecture for large language models (LLMs), examine prompt-tuning using frozen/unfrozen LLMs, and assess their abilities in transfer learning and few-shot learning.

Automatic categorization of self-acknowledged limitations in randomized controlled trial publications.

Journal of biomedical informatics
OBJECTIVE: Acknowledging study limitations in a scientific publication is a crucial element in scientific transparency and progress. However, limitation reporting is often inadequate. Natural language processing (NLP) methods could support automated ...

Building large-scale registries from unstructured clinical notes using a low-resource natural language processing pipeline.

Artificial intelligence in medicine
Building clinical registries is an important step in clinical research and improvement of patient care quality. Natural Language Processing (NLP) methods have shown promising results in extracting valuable information from unstructured clinical notes...

Development of method using language processing techniques for extracting information on drug-health food product interactions.

British journal of clinical pharmacology
AIMS: Health food products (HFPs) are foods and products related to maintaining and promoting health. HFPs may sometimes cause unforeseen adverse health effects by interacting with drugs. Considering the importance of information on the interactions ...