AIMC Topic: Comprehension

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Hierarchical dynamic coding coordinates speech comprehension in the human brain.

Proceedings of the National Academy of Sciences of the United States of America
Speech comprehension involves transforming an acoustic waveform into meaning. To do so, the human brain generates a hierarchy of features that converts the sensory input into increasingly abstract language properties. However, little is known about h...

The ethics of simplification: balancing patient autonomy, comprehension, and accuracy in AI-generated radiology reports.

BMC medical ethics
BACKGROUND: Large language models (LLMs) such as GPT-4 are increasingly used to simplify radiology reports and improve patient comprehension. However, excessive simplification may undermine informed consent and autonomy by compromising clinical accur...

Learning to detect AI texts and learning the limits.

PloS one
This study investigates whether individuals can learn to accurately discriminate between human-written and AI-produced texts when provided with immediate feedback, and if they can use this feedback to recalibrate their self-perceived competence. We a...

Evaluation of ChatGPT-4 responses on physical activity guidance in children with cystic fibrosis: reliability, quality, and readability.

European journal of pediatrics
UNLABELLED: ChatGPT-4 is a widely used large language model that provides instant answers to a variety of health-related questions in different medical fields. This study aims to evaluate the reliability, quality, accuracy, and readability of ChatGPT...

Evaluating the readability and quality of AI-generated scoliosis education materials: a comparative analysis of five language models.

Scientific reports
The complexity of scoliosis-related terminology and treatment options often hinders patients and caregivers from understanding their choices, making it difficult to make informed decisions. As a result, many patients seek guidance from artificial int...

Performance of several large language models when answering common patient questions about type 1 diabetes in children: accuracy, comprehensibility and practicality.

BMC pediatrics
BACKGROUND: The use of large language models (LLMs) in healthcare has expanded significantly with advances in natural language processing. Models, such as ChatGPT and Google Gemini, are increasingly used to generate human-like responses to questions,...

Referential hallucination and clinical reliability in large language models: a comparative analysis using regenerative medicine guidelines for chronic pain.

Rheumatology international
This study compared language models' responses to open-ended questions on regenerative therapy guidelines for chronic pain, assessing their accuracy, reliability, usefulness, readability, semantic similarity, and hallucination rates. This cross-secti...

Artificial intelligence-generated informed patient consent in various ophthalmological procedures: A comparative study of correctness, completeness, readability, and real-word application between Deepseek and Chatgpt 4o.

Indian journal of ophthalmology
PURPOSE: To study the correctness, completeness, language and readability, and real-world applicability of artificial intelligence chatbots-generated informed consent forms for various ophthalmological procedures and interventions.

Investigating the role of AI explanations in lay individuals' comprehension of radiology reports: A metacognition lens.

PloS one
While there has been extensive research on techniques for explainable artificial intelligence (XAI) to enhance AI recommendations, the metacognitive processes in interacting with AI explanations remain underexplored. This study examines how AI explan...

Evaluating the Quality and Understandability of Radiology Report Summaries Generated by ChatGPT: Survey Study.

JMIR formative research
BACKGROUND: Radiology reports convey critical medical information to health care providers and patients. Unfortunately, they are often difficult for patients to comprehend, causing confusion and anxiety, thereby limiting patient engagement in health ...