<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>5</volume><submitter>Bai J</submitter><pubmed_abstract>&lt;h4>Background&lt;/h4>Axial spondyloarthritis (axSpA) is a chronic autoinflammatory disease with heterogeneous clinical features, presenting considerable complexity for sustained patient self-management. Although the use of large language models (LLMs) in health care is rapidly expanding, there has been no rigorous assessment of their capacity to provide axSpA-specific health guidance.&lt;h4>Objective&lt;/h4>This study aimed to develop a patient-centered needs assessment tool and conduct a systematic evaluation of the quality of LLM-generated health advice for patients with axSpA.&lt;h4>Methods&lt;/h4>A 2-round Delphi consensus process guided the design of the questionnaire, which was subsequently administered to 84 patients with axSpA and 26 rheumatologists. Patient-identified key concerns were formulat</pubmed_abstract><journal>JMIR AI</journal><pagination>e79153</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12824573</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Assessing the Quality of AI Responses to Patient Concerns About Axial Spondyloarthritis: Delphi-Based Evaluation.</pubmed_title><pmcid>PMC12824573</pmcid><pubmed_authors>Zhang W</pubmed_authors><pubmed_authors>Ji X</pubmed_authors><pubmed_authors>Zhu J</pubmed_authors><pubmed_authors>Guo Y</pubmed_authors><pubmed_authors>Xue C</pubmed_authors><pubmed_authors>Bai J</pubmed_authors><pubmed_authors>Yu J</pubmed_authors><pubmed_authors>Wang Y</pubmed_authors></additional><is_claimable>false</is_claimable><name>Assessing the Quality of AI Responses to Patient Concerns About Axial Spondyloarthritis: Delphi-Based Evaluation.</name><description>&lt;h4>Background&lt;/h4>Axial spondyloarthritis (axSpA) is a chronic autoinflammatory disease with heterogeneous clinical features, presenting considerable complexity for sustained patient self-management. Although the use of large language models (LLMs) in health care is rapidly expanding, there has been no rigorous assessment of their capacity to provide axSpA-specific health guidance.&lt;h4>Objective&lt;/h4>This study aimed to develop a patient-centered needs assessment tool and conduct a systematic evaluation of the quality of LLM-generated health advice for patients with axSpA.&lt;h4>Methods&lt;/h4>A 2-round Delphi consensus process guided the design of the questionnaire, which was subsequently administered to 84 patients with axSpA and 26 rheumatologists. Patient-identified key concerns were formulat</description><dates><release>2026-01-01T00:00:00Z</release><publication>2026 Jan</publication><modification>2026-06-06T21:23:12.327Z</modification><creation>2026-06-05T03:11:48.256Z</creation></dates><accession>S-EPMC12824573</accession><cross_references><pubmed>41499772</pubmed><doi>10.2196/79153</doi></cross_references></HashMap>