AIMC Topic: Comprehension
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Artificial intelligence chatbots versus traditional medical resources for patient education on "Labor Epidurals": an evaluation of accuracy, emotional tone, and readability.
International journal of obstetric anesthesia
Nov 26, 2024
BACKGROUND: Labor epidural analgesia is a widely used method for pain relief in childbirth, yet information accessibility for expectant mothers remains a challenge. Artificial intelligence (AI) chatbots like Chat Generative Pre-Trained Transformer (C...
A multimetric health literacy analysis of phalloplasty techniques: Comparing artificial intelligence and online resources.
Journal of plastic, reconstructive & aesthetic surgery : JPRAS
Nov 26, 2024
BACKGROUND: This study aims to compare the informational quality of online and artificial intelligence (AI) - sources on different phalloplasty donor sites to assess reliability and accessibility.
How Useful are Current Chatbots Regarding Urology Patient Information? Comparison of the Ten Most Popular Chatbots' Responses About Female Urinary Incontinence.
Journal of medical systems
Nov 13, 2024
This research evaluates the readability and quality of patient information material about female urinary incontinence (fUI) in ten popular artificial intelligence (AI) supported chatbots. We used the most recent versions of 10 widely-used chatbots, i...
ChatGPT for parents' education about early childhood caries: A friend or foe?
International journal of paediatric dentistry
Nov 12, 2024
BACKGROUND: With the increasing popularity of online sources for health information, parents may seek information related to early childhood caries (ECC) from artificial intelligence-based chatbots.
Enhancing Spanish Patient Education Materials: Comparing the Readability of Artificial Intelligence-Generated Spanish Patient Education Materials to the Society of Pediatric Dermatology Spanish Patient Brochures.
Pediatric dermatology
Nov 12, 2024
Patient education materials (PEMs) are crucial for improving patient adherence and outcomes; however, they may not be accessible due to high reading levels. Our study used seven readability measures to compare the readability of Spanish PEMs from the...
Artificial intelligence as a modality to enhance the readability of neurosurgical literature for patients.
Journal of neurosurgery
Nov 8, 2024
OBJECTIVE: In this study the authors assessed the ability of Chat Generative Pretrained Transformer (ChatGPT) 3.5 and ChatGPT4 to generate readable and accurate summaries of published neurosurgical literature.
Utilization of Artificial Intelligence in the Creation of Patient Information on Laryngology Topics.
The Laryngoscope
Nov 6, 2024
OBJECTIVE: To evaluate and compare the readability and quality of patient information generated by Chat-Generative Pre-Trained Transformer-3.5 (ChatGPT) and the American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) using validated instru...
HirMTL: Hierarchical Multi-Task Learning for dense scene understanding.
Neural networks : the official journal of the International Neural Network Society
Nov 4, 2024
In the realm of artificial intelligence, simultaneous multi-task learning is crucial, particularly for dense scene understanding. To address this, we introduce HirMTL, a novel hierarchical multi-task learning framework designed to enhance dense scene...
Assessment of Artificial Intelligence Chatbot Responses to Common Patient Questions on Bone Sarcoma.
Journal of surgical oncology
Oct 29, 2024
BACKGROUND AND OBJECTIVES: The potential impacts of artificial intelligence (AI) chatbots on care for patients with bone sarcoma is poorly understood. Elucidating potential risks and benefits would allow surgeons to define appropriate roles for these...
Assessing the Responses of Large Language Models (ChatGPT-4, Claude 3, Gemini, and Microsoft Copilot) to Frequently Asked Questions in Retinopathy of Prematurity: A Study on Readability and Appropriateness.
Journal of pediatric ophthalmology and strabismus
Oct 28, 2024
PURPOSE: To assess the appropriateness and readability of responses provided by four large language models (LLMs) (ChatGPT-4, Claude 3, Gemini, and Microsoft Copilot) to parents' queries pertaining to retinopathy of prematurity (ROP).
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