首页|Investigators from University of Washington Release New Data on Artificial Intel ligence [Chat Generative Pretrained Transformer (Chatgpt) and Bard: Artificial Intelligence Does Not yet Provide Clinically Supported Answers for Hip and Knee ...]
Investigators from University of Washington Release New Data on Artificial Intel ligence [Chat Generative Pretrained Transformer (Chatgpt) and Bard: Artificial Intelligence Does Not yet Provide Clinically Supported Answers for Hip and Knee ...]
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Artificial Intelligence are presented in a new report. According to news reporting originating in Seattl e, Washington, by NewsRx journalists, research stated, "Advancements in artifici al intelligence (AI) have led to the creation of large language models (LLMs), s uch as Chat Generative Pretrained Transformer (ChatGPT) and Bard, that analyze o nline resources to synthesize responses to user queries. Despite their popularit y, the accuracy of LLM responses to medical questions remains unknown." The news reporters obtained a quote from the research from the University of Was hington, "This study aimed to compare the responses of ChatGPT and Bard regardin g treatments for hip and knee osteoarthritis with the American Academy of Orthop aedic Surgeons (AAOS) Evidence-Based Clinical Practice Guidelines (CPGs) recomme ndations. Both ChatGPT (Open AI) and Bard (Google) were queried regarding 20 tre atments (10 for hip and 10 for knee osteoarthritis) from the AAOS CPGs. Response s were classified by 2 reviewers as being in ‘Concordance, ‘ ‘Discordance, ‘ or ‘No Concordance ‘ with AAOS CPGs. A Cohen ‘s Kappa coefficient was used to asses s inter -rater reliability, and Chi -squared analyses were used to compare respo nses between LLMs. Overall, ChatGPT and Bard provided responses that were concor dant with the AAOS CPGs for 16 (80%) and 12 (60%) trea tments, respectively. Notably, ChatGPT and Bard encouraged the use of nonrecomme nded treatments in 30% and 60% of queries, respectiv ely. There were no differences in performance when evaluating by joint or by rec ommended versus non-recommended treatments. Studies were referenced in 6 (30% ) of the Bard responses and none (0%) of the ChatGPT responses. Of the 6 Bard responses, studies could only be identified for 1 (16.7% ). Of the remaining, 2 (33.3%) responses cited studies in journals that did not exist, 2 (33.3%) cited studies that could not be found with the information given, and 1 (16.7%) provided links to unrela ted studies. Both ChatGPT and Bard do not consistently provide responses that al ign with the AAOS CPGs."
SeattleWashingtonUnited StatesNort h and Central AmericaArthritisArtificial IntelligenceEmerging TechnologiesHealth and MedicineJoint Diseases and ConditionsKnee OsteoarthritisMachi ne LearningMusculoskeletal Diseases and ConditionsOsteoarthritisRheumatic Diseases and ConditionsUniversity of Washington