AIMC Topic: Comprehension

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Evaluating artificial intelligence chatbots for patient education in oral and maxillofacial radiology.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: This study aimed to compare the quality and readability of the responses generated by 3 publicly available artificial intelligence (AI) chatbots in answering frequently asked questions (FAQs) related to Oral and Maxillofacial Radiology (OM...

Performance of Artificial Intelligence Chatbots in Responding to Patient Queries Related to Traumatic Dental Injuries: A Comparative Study.

Dental traumatology : official publication of International Association for Dental Traumatology
BACKGROUND/AIM: Artificial intelligence (AI) chatbots have become increasingly prevalent in recent years as potential sources of online healthcare information for patients when making medical/dental decisions. This study assessed the readability, qua...

Comparative evaluation of responses from DeepSeek-R1, ChatGPT-o1, ChatGPT-4, and dental GPT chatbots to patient inquiries about dental and maxillofacial prostheses.

BMC oral health
BACKGROUND: Artificial intelligence chatbots have the potential to inform and guide patients by providing human-like responses to questions about dental and maxillofacial prostheses. Information regarding the accuracy and qualifications of these resp...

Improvement of metaphor understanding via a cognitive linguistic model based on hierarchical classification and artificial intelligence SVM.

Scientific reports
This study aims to enhance computers' ability to understand and generate metaphors, offering a novel perspective and technical approach in the field of natural language processing. It proposes a metaphor recognition algorithm that combines a Convolut...

Evaluating an AI Chatbot "Prostate Cancer Info" for Providing Quality Prostate Cancer Screening Information: Cross-Sectional Study.

JMIR cancer
BACKGROUND: Generative artificial intelligence (AI) chatbots may be useful tools for supporting shared prostate cancer (PrCA) screening decisions, but the information produced by these tools sometimes lack quality or credibility. "Prostate Cancer Inf...

Artificial intelligence in pediatric dental trauma: do artificial intelligence chatbots address parental concerns effectively?

BMC oral health
BACKGROUND: This study focused on two Artificial Intelligence chatbots, ChatGPT 3.5 and Google Gemini, as the primary tools for answering questions related to traumatic dental injuries. The aim of this study to evaluate the reliability, understandabi...

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...

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...