首页|McGill University Health Center Reports Findings in Artificial Intelligence [Is Artificial Intelligence (AI) currently able to provide evidence-based scienti fic responses on methods that can improve the outcomes of embryo transfers? No]
McGill University Health Center Reports Findings in Artificial Intelligence [Is Artificial Intelligence (AI) currently able to provide evidence-based scienti fic responses on methods that can improve the outcomes of embryo transfers? No]
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news reporting from Montreal, Canada, by NewsRx journalists, research stated, “The rapid development of Artificial In telligence (AI) has raised questions about its potential uses in different secto rs of everyday life. Specifically in medicine, the question arose whether chatbo ts could be used as tools for clinical decision-making or patients’ and physicia ns’ education.” The news correspondents obtained a quote from the research from McGill Universit y Health Center, “To answer this question in the context of fertility, we conduc ted a test to determine whether current AI platforms can provide evidence-based responses regarding methods that can improve the outcomes of embryo transfers. W e asked nine popular chatbots to write a 300-word scientific essay, outlining sc ientific methods that improve embryo transfer outcomes. We then gathered the res ponses and extracted the methods suggested by each chatbot. Out of a total of 43 recommendations, which could be grouped into 19 similar categories, only 3/19 ( 15.8%) were evidence-based practices, those being ‘ultrasound-guide d embryo transfer’ in 7/9 (77.8%) chatbots, ‘single embryo transfer ’ in 4/9 (44.4%) and ‘use of a soft catheter’ in 2/9 (22.2% ), whereas some controversial responses like ‘preimplantation genetic testing’ a ppeared frequently (6/9 chatbots; 66.7%), along with other debatabl e recommendations like ‘endometrial receptivity assay’, ‘assisted hatching’ and ‘time-lapse incubator’. Our results suggest that AI is not yet in a position to give evidence-based recommendations in the field of fertility, particularly conc erning embryo transfer, since the vast majority of responses consisted of scient ifically unsupported recommendations. As such, both patients and physicians shou ld be wary of guiding care based on chatbot recommendations in infertility.”
MontrealCanadaNorth and Central Amer icaArtificial IntelligenceAssisted Reproductive TechniquesEmbryo TransferEmerging TechnologiesHealth and MedicineMachine LearningReproductive Medi cine
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