AIMC Topic: Natural Language Processing

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Identifying Disinformation on the Extended Impacts of COVID-19: Methodological Investigation Using a Fuzzy Ranking Ensemble of Natural Language Processing Models.

Journal of medical Internet research
BACKGROUND: During the COVID-19 pandemic, the continuous spread of misinformation on the internet posed an ongoing threat to public trust and understanding of epidemic prevention policies. Although the pandemic is now under control, information regar...

Predicting drug-gene relations via analogy tasks with word embeddings.

Scientific reports
Natural language processing is utilized in a wide range of fields, where words in text are typically transformed into feature vectors called embeddings. BioConceptVec is a specific example of embeddings tailored for biology, trained on approximately ...

Lexical associations can characterize clinical documentation trends related to palliative care and metastatic cancer.

Scientific reports
Palliative care is known to improve quality of life in advanced cancer. Natural language processing offers insights to how documentation around palliative care in relation to metastatic cancer has changed. We analyzed inpatient clinical notes using u...

Assessment and Integration of Large Language Models for Automated Electronic Health Record Documentation in Emergency Medical Services.

Journal of medical systems
Automating Electronic Health Records (EHR) documentation can significantly reduce the burden on care providers, particularly in emergency care settings where rapid and accurate record-keeping is crucial. A critical aspect of this automation involves ...

A novel framework for sentiment classification employing Bi-GRU optimized by enhanced human evolutionary optimization algorithm.

Scientific reports
Sentiment analysis of content is highly essential for myriad natural language processing tasks. Particularly, as the movies are often created on the basis of public opinions, reviews of people have gained much attention, and analyzing sentiments has ...

Extracting Pediatric Information from Summaries of Product Characterics with a Large Language Model and No-Code.

Studies in health technology and informatics
Accurate medication information is important for children, as dosing errors can have severe consequences compared to adults. We propose an automated method to extract pediatric information from Summaries of Product Characteristics (SPC). We used AirO...

Explainable Versus Interpretable AI in Healthcare: How to Achieve Understanding.

Studies in health technology and informatics
The increasing adoption of deep learning methods has intensified the demand for explanations regarding how AI systems generate their results. This necessity originated primarily in the domain of image processing and has expanded to encompass the comp...

Artificial Intelligence in Narrative Feedback Analysis for Competency-Based Medical Education: A Review.

Studies in health technology and informatics
Competency-Based Medical Education (CBME) generates large volumes of qualitative data in the form of narrative feedback. Traditional qualitative analysis methods face limitations in managing this data's scale and complexity. This review explores the ...

Utilizing Large Language Models to Monitor Social Media for Disability: An Analysis of Sentiment and Disability Models in Tweets.

Studies in health technology and informatics
This study explores how well large language models (like the kind that powers ChatGPT) can analyze online conversations about disability rights. We specifically looked at whether these models could: 1) identify if tweets about people with disabilitie...

A Mixed-Methods Evaluation of LLM-Based Chatbots for Menopause.

Studies in health technology and informatics
The integration of Large Language Models (LLMs) into healthcare settings has gained significant attention, particularly for question-answering tasks. Given the high-stakes nature of healthcare, it is essential to ensure that LLM-generated content is ...