AIMC Topic: Natural Language Processing

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Comparison of active learning algorithms in classifying head computed tomography reports using bidirectional encoder representations from transformers.

International journal of computer assisted radiology and surgery
PURPOSE: Systems equipped with natural language (NLP) processing can reduce missed radiological findings by physicians, but the annotation costs are burden in the development. This study aimed to compare the effects of active learning (AL) algorithms...

Assessment of Real-Time Natural Language Processing for Improving Diagnostic Specificity: A Prospective, Crossover Exploratory Study.

Applied clinical informatics
BACKGROUND:  Reliable, precise, timely, and clear documentation of diagnoses is difficult. Poor specificity or the absence of diagnostic documentation can lead to decreased revenue and increased payor denials, audits, and queries to providers. Nuance...

Utilizing natural language processing to identify pediatric patients experiencing status epilepticus.

Seizure
PURPOSE: Compare the identification of patients with established status epilepticus (ESE) and refractory status epilepticus (RSE) in electronic health records (EHR) using human review versus natural language processing (NLP) assisted review.

Hybrid natural language processing tool for semantic annotation of medical texts in Spanish.

BMC bioinformatics
BACKGROUND: Natural language processing (NLP) enables the extraction of information embedded within unstructured texts, such as clinical case reports and trial eligibility criteria. By identifying relevant medical concepts, NLP facilitates the genera...

An Intelligent System for Classifying Patient Complaints Using Machine Learning and Natural Language Processing: Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Accurate classification of patient complaints is crucial for enhancing patient satisfaction management in health care settings. Traditional manual methods for categorizing complaints often lack efficiency and precision. Thus, there is a g...

Public Health Discussions on Social Media: Evaluating Automated Sentiment Analysis Methods.

JMIR formative research
BACKGROUND: Sentiment analysis is one of the most widely used methods for mining and examining text. Social media researchers need guidance on choosing between manual and automated sentiment analysis methods.

Schizophrenia more employable than depression? Language-based artificial intelligence model ratings for employability of psychiatric diagnoses and somatic and healthy controls.

PloS one
Artificial Intelligence (AI) assists recruiting and job searching. Such systems can be biased against certain characteristics. This results in potential misrepresentations and consequent inequalities related to people with mental health disorders. He...

Artificial Intelligence, Machine Learning and Big Data in Radiation Oncology.

Hematology/oncology clinics of North America
This review explores the applications of artificial intelligence and machine learning (AI/ML) in radiation oncology, focusing on computer vision (CV) and natural language processing (NLP) techniques. We examined CV-based AI/ML in digital pathology an...

Annotated corpus for traditional formula-disease relationships in biomedical articles.

Scientific data
The Traditional Formula (TF), a combination of herbs prepared in accordance with traditional medicine principles, is increasingly garnering global attention as an alternative to modern medicine. Specifically, there is growing interest in exploring TF...

Revolutionizing Health Care: The Transformative Impact of Large Language Models in Medicine.

Journal of medical Internet research
Large language models (LLMs) are rapidly advancing medical artificial intelligence, offering revolutionary changes in health care. These models excel in natural language processing (NLP), enhancing clinical support, diagnosis, treatment, and medical ...