AIMC Topic: Natural Language Processing

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Digital Epidemiology of Prescription Drug References on X (Formerly Twitter): Neural Network Topic Modeling and Sentiment Analysis.

Journal of medical Internet research
BACKGROUND: Data from the social media platform X (formerly Twitter) can provide insights into the types of language that are used when discussing drug use. In past research using latent Dirichlet allocation (LDA), we found that tweets containing "st...

Using machine learning methods to predict all-cause somatic hospitalizations in adults: A systematic review.

PloS one
AIM: In this review, we investigated how Machine Learning (ML) was utilized to predict all-cause somatic hospital admissions and readmissions in adults.

The state of artificial intelligence in medical research: A survey of corresponding authors from top medical journals.

PloS one
Natural Language Processing (NLP) is a subset of artificial intelligence that enables machines to understand and respond to human language through Large Language Models (LLMs)‥ These models have diverse applications in fields such as medical research...

Incidental pulmonary nodules: Natural language processing analysis of radiology reports.

Respiratory medicine and research
BACKGROUND: Pulmonary nodules are a common incidental finding on chest Computed Tomography scans (CT), most of the time outside of lung cancer screening (LCS). We aimed to evaluate the number of incidental pulmonary nodules (IPN) found in 1 year in o...

Utility of Machine Learning, Natural Language Processing, and Artificial Intelligence in Predicting Hospital Readmissions After Orthopaedic Surgery: A Systematic Review and Meta-Analysis.

JBJS reviews
BACKGROUND: Numerous applications and strategies have been utilized to help assess the trends and patterns of readmissions after orthopaedic surgery in an attempt to extrapolate possible risk factors and causative agents. The aim of this work is to s...

LERCause: Deep learning approaches for causal sentence identification from nuclear safety reports.

PloS one
Identifying causal sentences from nuclear incident reports is essential for advancing nuclear safety research and applications. Nonetheless, accurately locating and labeling causal sentences in text data is challenging, and might benefit from the usa...

Finding the Needle in the Haystack: Can Natural Language Processing of Students' Evaluations of Teachers Identify Teaching Concerns?

Journal of general internal medicine
BACKGROUND: Institutions rely on student evaluations of teaching (SET) to ascertain teaching quality. Manual review of narrative comments can identify faculty with teaching concerns but can be resource and time-intensive.

VAIV bio-discovery service using transformer model and retrieval augmented generation.

BMC bioinformatics
BACKGROUND: There has been a considerable advancement in AI technologies like LLM and machine learning to support biomedical knowledge discovery.

Self-Administered Interventions Based on Natural Language Processing Models for Reducing Depressive and Anxiety Symptoms: Systematic Review and Meta-Analysis.

JMIR mental health
BACKGROUND: The introduction of natural language processing (NLP) technologies has significantly enhanced the potential of self-administered interventions for treating anxiety and depression by improving human-computer interactions. Although these ad...

Utilizing natural language processing to analyze student narrative reflections for medical curriculum improvement.

Medical teacher
MOTIVATION: Medical curricula improvement is an ongoing process to keep material relevant and improve the student's learning experience to better prepare them for patient care. Many programs utilize end-of-year evaluations, but these frequently have ...