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In this video, Jan Herzhoff, President of Health Markets at Elsevier, and Mie-Yun Lee, Chief of Staff at Elsevier, describe important considerations clinicians should make when implementing AI technology and how responsible AI principles play a vital role in the development of generative AI solutions for healthcare.ย
โFor us itโs super critical that this content is delivered in a very responsible way to healthcare providers across the globe.โ - Jan Herzhoffย
In this video, Elsevier Healthโs clinical experts Dr. Paul Helmuth and Dr. Claudine Lott share challenges that could come from using AI for clinical scenarios and how to address those challenges with technology.ย ย
โOne of the biggest considerations when implementing AI for clinical decision support for physicians is accuracy and trust in the answers. So we can address this by using a corpus of trusted, evidence-based information that the AI can draw from so that clinicians can have faith in the information theyโre receiving.โย - Dr. Claudine Lottย ย
In this video, Elsevier Healthโs technology experts Katie Scranton and Rhett Alden outline how a responsible AI framework can help mitigate potential ethical challenges with AI in healthcare and share their predictions on what the future holds for AI in the industry.ย
โIn the future of AI in healthcare I really see a move toward a careful and responsible application of these models in a way that will help clinicians solve their problems more efficiently, not in a way that would solve problems for clinicians.โย - Katie Scrantonย
In this video, data scientist and RN Leah Livingston shares how metrics like accuracy and potential harmfulness are important factors in determining the effectiveness of responses provided in ClinicalKey AI.ย
โClinicians can trust our results because weโve partnered with clinicians, statisticians, and data scientists to ensure weโve powered our study appropriately so that we can ensure reliable and valid data.โย - Leah Livingstonย