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HESP Seminar - Nina Benway

Nina Benway

HESP Seminar - Nina Benway

Maryland Language Science Center | Hearing and Speech Sciences Monday, November 11, 2024 12:00 pm - 1:00 pm LeFrak Hall, 2166

Preparing Clinicians for a Future of Artificial Intelligence-Assisted Evidence-Based Practice through the Critical Appraisal of Clinical Artificial Intelligence

Abstract: Artificial intelligence (AI) is more capable and accessible than ever before. But what does this mean for clinical practice? How can speech-language clinicians evaluate the efficacy, validity, and reliability of AI and machine learning tools meant to automate parts of assessment and treatment? How can speech language clinicians be ethical consumers of these clinical AI technologies? It may be that clinical AI will serve clinicians and clients best when it embodies the evidence based framework already in use by the profession. Therefore, this presentation presents guidelines for the critical appraisal of clinical AI through the lens of validity, reliability, ethical use, and equitable use. A rubric is provided to assist clinicians in the critical appraisal of clinical AI tools.

 



 

Add to Calendar 11/11/24 12:00:00 11/11/24 13:00:00 America/New_York HESP Seminar - Nina Benway

Preparing Clinicians for a Future of Artificial Intelligence-Assisted Evidence-Based Practice through the Critical Appraisal of Clinical Artificial Intelligence

Abstract: Artificial intelligence (AI) is more capable and accessible than ever before. But what does this mean for clinical practice? How can speech-language clinicians evaluate the efficacy, validity, and reliability of AI and machine learning tools meant to automate parts of assessment and treatment? How can speech language clinicians be ethical consumers of these clinical AI technologies? It may be that clinical AI will serve clinicians and clients best when it embodies the evidence based framework already in use by the profession. Therefore, this presentation presents guidelines for the critical appraisal of clinical AI through the lens of validity, reliability, ethical use, and equitable use. A rubric is provided to assist clinicians in the critical appraisal of clinical AI tools.

 



 

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