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Evaluate quality and readability of online information for common rheumatologic diseases. Compare rheumatology patients' internet use and preferences to an objective evaluation of internet quality and readability. Five common rheumatologic diseases were searched on the web browser Google using English language. The first twenty websites from each of the five searches were evaluated for internet quality (e.g. content that is current, balanced, has specific aims, and is appropriately cited) using the DISCERN criteria and readability using the Flesch-Kincaid Grade Level (FKGL). The results were contrasted with a survey sent to patients with rheumatic disease. The survey measured patient likeliness to use and trust identified websites. Internet quality was similar (good) for all five diseases searched while readability was poor. There was an inverse relationship between internet quality and readability. Internet quality significantly differed across website sponsor, and readability significantly differed across disease and website sponsor. Common medical website sponsors with the highest combined quality and readability scores were Mayo Clinic and Web MD. Eight hundred and fifty-eight patients were sent a survey, of which 147 (17%) completed. Patients indicated they were most likely to use and trust a Mayo Clinic-sponsored website when compared to other common sponsored websites from our evaluation, followed by the American College of Rheumatology. Although we found good-quality information, all websites evaluated had readability levels above the recommended sixth-grade reading level. The website sponsor with the highest combined readability and quality score was also the most used and trusted by patients. Patients would like more information about credible and trusted websites from their medical providers.
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http://dx.doi.org/10.1007/s00296-020-04664-8 | DOI Listing |
J Craniofac Surg
September 2025
Department of Breast Plastic Surgery, Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shijingshan, Beijing, China.
Background: With the development of artificial intelligence, obtaining patient-centered medical information through large language models (LLMs) is crucial for patient education. However, existing digital resources in online health care have heterogeneous quality, and the reliability and readability of content generated by various AI models need to be evaluated to meet the needs of patients with different levels of cultural literacy.
Objective: This study aims to compare the accuracy and readability of different LLMs in providing medical information related to gynecomastia, and explore the most promising science education tools in practical clinical applications.
JCO Clin Cancer Inform
September 2025
USC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA.
Purpose: To evaluate a generative artificial intelligence (GAI) framework for creating readable lay abstracts and summaries (LASs) of urologic oncology research, while maintaining accuracy, completeness, and clarity, for the purpose of assessing their comprehension and perception among patients and caregivers.
Methods: Forty original abstracts (OAs) on prostate, bladder, kidney, and testis cancers from leading journals were selected. LASs were generated using a free GAI tool, with three versions per abstract for consistency.
Nat Prod Rep
September 2025
State Key Laboratory of Pharmaceutical Biotechnology, Institute of Functional Biomolecules, School of Life Sciences, Nanjing University, Nanjing 210023, China.
Covering: up to April 2025Bacterial aromatic polyketides represent a notable class of natural products that have found extensive applications in clinical treatments. In their biosynthesis, oxidative rearrangements represent critical transformations that typically afford diverse scaffolds, structural rigidity, and biological activities. In this context, it is evident that redox enzymes are frequently implicated in various rearrangement processes, whereby they facilitate the transformation of pathway precursors into mature natural products.
View Article and Find Full Text PDFJ Prosthet Dent
September 2025
Professor, Department of Prosthodontics, Faculty of Dentistry, Gazi University, Ankara, Turkey.
Statement Of Problem: Despite advances in artificial intelligence (AI), the quality, reliability, and understandability of health-related information provided by chatbots is still a question mark. Furthermore, studies on maxillofacial prosthesis (MP) information from AI chatbots are lacking.
Purpose: The purpose of this study was to assess and compare the reliability, quality, readability, and similarity of responses to MP-related questions generated by 4 different chatbots.
Int J Cardiovasc Imaging
September 2025
Klinikum Fürth, Friedrich-Alexander-University Erlangen- Nürnberg, Fürth, Germany.
Myocarditis is an inflammation of heart tissue. Cardiovascular magnetic resonance imaging (CMR) has emerged as an important non-invasive imaging tool for diagnosing myocarditis, however, interpretation remains a challenge for novice physicians. Advancements in machine learning (ML) models have further improved diagnostic accuracy, demonstrating good performance.
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