首页|Investigators from University of Toronto Release New Data on Artificial Intellig ence (Navigating the Uncommon: Challenges In Applying Evidence-based Medicine To Rare Diseases and the Prospects of Artificial Intelligence Solutions)
Investigators from University of Toronto Release New Data on Artificial Intellig ence (Navigating the Uncommon: Challenges In Applying Evidence-based Medicine To Rare Diseases and the Prospects of Artificial Intelligence Solutions)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Artificial Intelligen ce have been presented. According to news reporting originating in Toronto, Cana da, by NewsRx editors, the research stated, “The study of rare diseases has long been an area of challenge for medical researchers, with agonizingly slow moveme nt towards improved understanding of pathophysiology and treatments compared wit h more common illnesses. The push towards evidence-based medicine (EBM), which p rioritizes certain types of evidence over others, poses a particular issue when mapped onto rare diseases, which may not be feasibly investigated using the meth odologies endorsed by EBM, due to a number of constraints.” The news reporters obtained a quote from the research from the University of Tor onto, “While other trial designs have been suggested to overcome these limitatio ns (with varying success), perhaps the most recent and enthusiastically adopted is the application of artificial intelligence to rare disease data. This paper c ritically examines the pitfalls of EBM (and its trial design offshoots) as it pe rtains to rare diseases, exploring the current landscape of AI as a potential so lution to these challenges. This discussion is also taken a step further, provid ing philosophical commentary on the weaknesses and dangers of AI algorithms appl ied to rare disease research. While not proposing a singular solution, this arti cle does provide a thoughtful reminder that no ‘one-size-fits-all’ approach exis ts in the complex world of rare diseases.”
TorontoCanadaNorth and Central Ameri caArtificial IntelligenceEmerging TechnologiesHealth and MedicineMachine LearningRare Diseases and ConditionsUniversity of Toronto
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