AIMC Topic: Natural Language Processing

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Potential of Large Language Models in Health Care: Delphi Study.

Journal of medical Internet research
BACKGROUND: A large language model (LLM) is a machine learning model inferred from text data that captures subtle patterns of language use in context. Modern LLMs are based on neural network architectures that incorporate transformer methods. They al...

Vocabulary Matters: An Annotation Pipeline and Four Deep Learning Algorithms for Enzyme Named Entity Recognition.

Journal of proteome research
Enzymes are indispensable in many biological processes, and with biomedical literature growing exponentially, effective literature review becomes increasingly challenging. Natural language processing methods offer solutions to streamline this process...

A roadmap to artificial intelligence (AI): Methods for designing and building AI ready data to promote fairness.

Journal of biomedical informatics
OBJECTIVES: We evaluated methods for preparing electronic health record data to reduce bias before applying artificial intelligence (AI).

Improving span-based Aspect Sentiment Triplet Extraction with part-of-speech filtering and contrastive learning.

Neural networks : the official journal of the International Neural Network Society
Aspect Sentiment Triple Extraction (ASTE), a subtask of fine-grained sentiment analysis, aims to extract aspect terms, opinion terms, and their corresponding sentiment polarities from sentences. Previous methods often enumerated all possible spans of...

Assessing the Suitability of Artificial Intelligence-Based Chatbots as Counseling Agents for Patients with Brain Tumor: A Comprehensive Survey Analysis.

World neurosurgery
OBJECTIVE: The internet, particularly social media, has become a popular resource for learning about health and investigating one's own health conditions. The development of artificial intelligence (AI) chatbots has been fueled by the increasing avai...

Giving a Voice to Patients With Smell Disorders Associated With COVID-19: Cross-Sectional Longitudinal Analysis Using Natural Language Processing of Self-Reports.

JMIR public health and surveillance
BACKGROUND: Smell disorders are commonly reported with COVID-19 infection. The smell-related issues associated with COVID-19 may be prolonged, even after the respiratory symptoms are resolved. These smell dysfunctions can range from anosmia (complete...

Predicting the Utility of Scientific Articles for Emerging Pandemics Using Their Titles and Natural Language Processing.

Disaster medicine and public health preparedness
OBJECTIVE: Not all scientific publications are equally useful to policy-makers tasked with mitigating the spread and impact of diseases, especially at the start of novel epidemics and pandemics. The urgent need for actionable, evidence-based informat...

Harnessing Generative Artificial Intelligence for Medical Education.

Academic medicine : journal of the Association of American Medical Colleges
Generative artificial intelligence (AI) tools powered by large language models (LLMs) are poised to transform medical education. Generative AI's broad knowledge base and powerful natural language processing allow educators to use it for numerous task...

A nursing note-aware deep neural network for predicting mortality risk after hospital discharge.

International journal of nursing studies
BACKGROUND: ICU readmissions and post-discharge mortality pose significant challenges. Previous studies used EHRs and machine learning models, but mostly focused on structured data. Nursing records contain crucial unstructured information, but their ...