AIMC Topic: Comprehension

Clear Filters Showing 231 to 240 of 271 articles

Assessing Healthcare Stakeholder Understanding of Machine Learning Documentation.

Studies in health technology and informatics
Artificial Intelligence (AI) has significantly advanced clinical decision support systems in healthcare, particularly using Machine Learning (ML) models. However, the technical nature of current ML model documentation often leads to lack of comprehen...

Evaluating the impact of AI-generated educational content on patient understanding and anxiety in endodontics and restorative dentistry: a comparative study.

BMC oral health
BACKGROUND: Effective patient education is critical in enhancing treatment outcomes and reducing anxiety in dental procedures. This study compares the effectiveness of AI-generated educational materials with traditional methods in improving patient c...

Evaluation of AI Summaries on Interdisciplinary Understanding of Ophthalmology Notes.

JAMA ophthalmology
IMPORTANCE: Specialized ophthalmology terminology limits comprehension for nonophthalmology clinicians and professionals, hindering interdisciplinary communication and patient care. The clinical implementation of large language models (LLMs) into pra...

Battle of the authors: Comparing neurosurgery articles written by humans and AI.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
BACKGROUND: The advancement of artificial intelligence (AI) has led to its application in various fields, including medical literature. This study compares the quality of neurosurgery articles written by human authors and those generated by ChatGPT, ...

Assessing the quality and readability of patient education materials on chemotherapy cardiotoxicity from artificial intelligence chatbots: An observational cross-sectional study.

Medicine
Artificial intelligence (AI) and the introduction of Large Language Model (LLM) chatbots have become a common source of patient inquiry in healthcare. The quality and readability of AI-generated patient education materials (PEM) is the subject of man...

Readability, reliability and quality of responses generated by ChatGPT, gemini, and perplexity for the most frequently asked questions about pain.

Medicine
It is clear that artificial intelligence-based chatbots will be popular applications in the field of healthcare in the near future. It is known that more than 30% of the world's population suffers from chronic pain and individuals try to access the h...

AI meets informed consent: a new era for clinical trial communication.

JNCI cancer spectrum
Clinical trials are fundamental to evidence-based medicine, providing patients with access to novel therapeutics and advancing scientific knowledge. However, patient comprehension of trial information remains a critical challenge, as registries like ...

The use of large language models to enhance cancer clinical trial educational materials.

JNCI cancer spectrum
BACKGROUND: Adequate patient awareness and understanding of cancer clinical trials is essential for trial recruitment, informed decision making, and protocol adherence. Although large language models (LLMs) have shown promise for patient education, t...

Composition as Nonlinear Combination in Semantic Space: A Computational Characterization of Compound Processing.

Cognitive science
Most Chinese words are compounds formed through the combination of meaningful characters. Yet, due to compositional complexity, it is poorly understood how this combinatorial process affects the access to the whole-word meaning. In the present study,...

Enhancing Patient Education on Cardiovascular Rehabilitation with Large Language Models.

Missouri medicine
INTRODUCTION: There are barriers that exist for individuals to adhere to cardiovascular rehabilitation programs. A key driver to patient adherence is appropriately educating patients. A growing education tool is using large language models to answer ...