<body><div><figure><img src="https://img.particlenews.com/image.php?type=thumbnail_580x000&amp;url=19WxzX_0wLtUOKD00" alt="https://img.particlenews.com/image.php?url=19WxzX_0wLtUOKD00" width="600" height="400" ></figure>Course Director:James Gaensbauer, M.D., MScPHGuest Faculty: Daniel Brailita, M.D.October 25, 2025 - 12:00 - 1:00 p.m. Central Time - Live WebinarThis course examines the emerging role of large language models (LLMs) in tuberculosis (TB) care and research. Participants will explore how these models can process and analyze vast amounts of textual data, offering predictive insights into TB treatment outcomes, improving information extraction through natural language processing (NLP) techniques, and transforming patient-provider communication.<h2>Target Audience</h2>This course is designed for allied health professionals, nurses, nurse practitioners, physicians, physician assistants, resident/fellows, and healthcare professionals working in a public healthcare setting.<h2>Learning Objectives</h2>Upon completion of this activity, participants should be able to:<ul><li>Recognize the potential of large language models (LLMs) to analyze textual data and provide predictive insights into tuberculosis (TB) treatment outcomes.</li><li>Identify how natural language processing (NLP) techniques improve information extraction from unstructured data, such as medical records, in TB care.</li><li>Explain how LLMs can improve patient-provider communication.</li><li>Describe Ethical challenges raised by use of LLM</li></ul>Attendance at any Mayo Clinic course does not indicate or guarantee competence or proficiency in the skills, knowledge or performance of any care or procedure(s) which may be discussed or taught in this course.Course summaryAvailable credit: Event starts: 10/25/2024 - 12:00pmEvent ends: 10/25/2024 - 1:00pmInternet Live ActivityRochester, MN 55901United StatesBroadcast in Central TimeAll travel and lodging expenses are the sole responsibility of the individual registrant.Course DirectorsJames Gaensbauer, M.D., MScPHGuest FacultyDaniel Brailita, M.D.Credit Statement(s): AMAMayo Clinic College of Medicine and Science designates this live activity for a maximum of 1.00 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.ACPEMayo Clinic College of Medicine and Science designates this educational activity for a maximum of 1.00 ACPE Knowledge-based contact hours. Participants should claim only the credit commensurate with the extent of their participation in the activity.UAN Number: JA0000238-0000-24-107-L01-PANCCMayo Clinic College of Medicine and Science designates this activity for a maximum of 1.00 ANCC contact hours. Nurses should claim only the credit commensurate with the extent of their participation in the activity.Other Healthcare Professionals:A record of attendance will be provided to all registrants for requesting credits in accordance with state nursing boards, specialty societies or other professional associations.For disclosure information regarding Mayo Clinic School of Continuous Professional Development accreditation review committee member(s) and staff, please go here to review disclosures.<h2>Available Credit</h2>Please login or register to take this course.To claim credit for livestream participation in this course, learners must view the content during the hours posted for the live activity. This course is not approved for on-demand delivery.Commitment to Equity, Diversity and Inclusion Mayo Clinic School of Continuous Professional Development (MCSCPD) strives to foster a learning environment in which individual differences are valued, allowing all to achieve their fullest potential.Cancellation and Refund PolicyAll requests must be submitted in writing using the Contact Us Form.Any use of this site constitutes your agreement to the Terms and Conditions of Registration.</div></body>

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Large Language Models Use in Tuberculosis (TB)

Guest Faculty: Daniel Brailita, M.D. October 25, 2025 - 12:00 - 1:00 p.m. Central Time - Live Webinar. This course examines the emerging role of large language models (LLMs) in tuberculosis (TB) care and research. Participants will explore how these models can process and analyze vast amounts of textual data, offering predictive insights into TB treatment outcomes, improving information extraction through natural language processing (NLP) techniques, and transforming patient-provider communication.