HEA₃RT News & Publications

National Academies of Sciences, Engineering, and Medicine and National Academy of Medicine. 2023. Toward Equitable Innovation in Health and Medicine: A Framework. Washington, DC: The National Academies Press. https://doi.org/10.17226/27184.

Hong G, Less J, Masoudian B, et al. Trends in Pediatric Primary Care Visits During the COVID-19 Pandemic: Opportunity to Address Adolescent Behavioral Health Through Telemedicine. [published July 24, 2023]. Fam Med.

Amano A, Brown-Johnson CG, Winget M, Sinha A, Shah S, Sinsky C, Sharp C, Shanafelt T, Skeff K. Perspectives on the Intersection of Electronic Health Records and Health Care Team Communication, Function, and Well-being. JAMA Netw Open. 2023;6(5):e2313178. doi:10.1001/jamanetworkopen.2023.13178

Bajra R, Frazier W, Graves L, Jacobson K, Rodriguez A, Theobald M, Lin S. Feasibility and acceptability of a U.S. national telemedicine curriculum for medical students and residents: multi-institutional cross-sectional study. JMIR Medical Education. 2023;9:e43190.

Sossenheimer P, Hong G, Devon-Sand A, Lin S. Voice assistants’ responses to questions about the COVID-19 vaccine: national cross-sectional study. JMIR Formative Research. 2023;7:e43007.

Liaw W, Kueper J, Lin S, Bazemore A, Kakadiaris I. Competencies for the use of artificial intelligence in primary care. Annals of Family Medicine. 2022;20(6):559-563.

Adler-Milstein J, Aggarwal N, Ahmed M, Castner J, Evans B, Gonzalez A, James C, Lin S, Mandl K, Matheny M, Sendak M, Shachar C, Williams A. Meeting the moment: addressing barriers and facilitating clinical adoption of artificial intelligence in medical diagnosis. NAM Perspectives. 2022; Discussion Paper, Washington, DC. https://doi.org/10.31478/202209c.

Lu J, Sattler A, Wang S, Khaki AR, Callahan A, Fleming S, Fong R, Ehlert B, Li RC, Shieh L, Ramchandran K, Gensheimer MF, Chobot S, Pfohl S, Li S, Shum K, Parikh N, Desai P, Seevaratnam B, Hanson M, Smith M, Xu Y, Gokhale A, Lin S, Pfeffer MA, Teuteberg W, Shah NH. Considerations in the reliability and fairness audits of predictive models for advance care planning. Frontiers in Digital Health. 2022;4:943768

Hong G, Smith M, Lin S. The AI will see you now: feasibility and acceptability of a conversational AI medical interviewing system. JMIR Formative Research. 2022;6(6):e37028.

Lin S, Shah S, Sattler A, Smith M. Predicting avoidable healthcare utilization: practical considerations for AI/ML models in population health. Mayo Clinic Proceedings. 2022;97(4):653-657.

Li R, Smith M, Lu J, Avati A, Wang S, Teuteberg W, Shrum K, Hong G, Seevaratnam B, Westphal J, Dougherty M, Rao P, Asch S, Lin S, Sharp C, Shieh L, Shah N. Using AI to empower collaborative team workflows: two implementations for advance care planning and care escalation. NEJM Catalyst Innovations in Care Delivery. 2022;3(4). DOI: 10.1056/CAT.21.0457.

Gordon and Betty Moore Foundation and UCSF Center for Clinical Informatics and Improvement Research. Unlocking new opportunities for AI-enabled diagnosis [White paper]. 2022.

Yang Z, Silcox C, Sendak M, Rose S, Rehkopf D, Phillips R, Peterson L, Marino M, Maier J, Lin S, Liaw W, Kakadiaris I, Heintzman J, Chu I, Bazemore A. Advancing primary care with artificial intelligence and machine learning. Healthcare. 2022; 10:100594. 

Lin S. A clinician's guide to artificial intelligence: why and how primary care should lead the healthcare AI revolution. Journal of the American Board of Family Medicine. 2022; 35:175-184.

Holdsworth L, Park C, Asch S, Lin S. The use of technology-enabled and artificial intelligence support for pre-visit planning: findings from an environmental scan. Annals of Family Medicine. 2021;19(5):419-426. 

Hong G, Folcarelli A, Less J, Wang C, Erbasi N, Lin S. Voice assistants' responses to questions about cancer screening: a comparison of Alexa, Siri, Google Assistant, and Cortana. Annals of Family Medicine. 2021;19(5):447-449. 

Holdsworth LM, Kling SMR, Smith M, Safaeinili N, Shieh L, Vilendrer S, Garvert DW, Winget M, Asch SM, Li RC. Predicting and Responding to Clinical Deterioration in Hospitalized Patients by Using Artificial Intelligence: Protocol for a Mixed Methods, Stepped Wedge Study. JMIR Res Protoc. 2021;10(7):e27532.

Jung K, Kashyap S, Avati A, Harman S, Shaw H, Li R, Smith M, Shum K, Javitz J, Vetteth Y, Seto T, Bagley SC, Shah NH. A framework for making predictive models useful in practice. J Am Med Inform Assoc. 2021;28(6):1149-1158.

Teerink D, Bajra R, Fuchs L, Patel M, Jortberg B, Theobald M, Lin S. Future of telehealth. STFM National Telemedicine Curriculum for Medical Students and Residents. 2021.

Fuchs L, Bajra R, Patel M, Teerink D, Jortberg B, Theobald M, Lin S. Access and equity in telehealth. STFM National Telemedicine Curriculum for Medical Students and Residents. 2021.

Patel M, Bajra R, Fuchs L, Teerink D, Jortberg B, Theobald M, Lin S. Requirements for telehealth. STFM National Telemedicine Curriculum for Medical Students and Residents. 2021.

Bajra R, Fuchs L, Patel M, Teerink D, Jortberg B, Theobald M, Lin S. The telehealth encounter. STFM National Telemedicine Curriculum for Medical Students and Residents. 2021.

Jortberg B, Bajra R, Fuchs L, Patel M, Teerink D, Theobald M, Lin S. Introduction to telehealth. STFM National Telemedicine Curriculum for Medical Students and Residents. 2021.

Avati A, Li R, Smith M, et al. Empowering team-based advance care planning with artificial intelligence. Medium. 2021.

Smith M, Sattler A, Hong G, Lin S. From code to bedside: implementing artificial intelligence using quality improvement methods. Journal of General Internal Medicine. 2021;36(4):1061-1066.
 

Hong G, Wilcox L, Sattler A, Thomas S, Gonzalez N, Smith M, Hernandez J, Smith M, Lin S, Harrington R. Clinicians’ Experiences with EHR Documentation and Attitudes Toward AI-Assisted Documentation [White paper]. Retrieved from Stanford University School of Medicine and Google Health: med.stanford.edu/healthcare-ai and health.google. 2021.

Lin S, Sattler A, Smith M. Retooling primary care in the COVID-19 era. Mayo Clinic Proceedings. 2020; 95(9):1831-1834.

Lin S. The present and future of team documentation: the role of patients, families, and artificial intelligence. Mayo Clinic Proceedings. 2020; 95(5):852-855.

Luh J, Thompson R, Lin S. Clinical documentation and patient care using artificial intelligence in radiation oncology. Journal of the American College of Radiology. 2019; 16(9 pt B):1343-1346.

Lin S, Mahoney M, Sinsky C. Ten ways artificial intelligence will transform primary care. Journal of General Internal Medicine. 2019; 34(8):1626-1630.

Lin S, Shanafelt T, Asch S. Reimagining clinical documentation with artificial intelligence. Mayo Clinic Proceedings. 2018; 93(5):563-565.

Tsai T, Shah S, Gorrepati K, Genkins J, Han R, Safdi A, Sakata T, Tang K, Sangari A, Sattler A, Devon-Sand A, Sayana A, Smith M, Lin S. Validation of large language AI based patient message classification to automate workflows and reduce inbox burden.

• American Medical Informatics Association (AMIA) Annual Symposium, New Orleans, LA (2023)
• North American Primary Care Research Group (NAPCRG) 51st Annual Meeting, San Francisco, CA (2023)

Lin S. Health equity, workforce burnout and more: is generative AI the magic wand for reducing healthcare cost and improving care delivery?

• Generative AI for Healthcare Summit, Cambridge, MA (2023)

Lin S. The future front door of care: how generative AI will impact primary care physicians.

• Generative AI for Healthcare Summit, Cambridge, MA (2023)

Rikhye R, Liu Y, Sayres R, Liu Y, Lin S, Singh P, Ko J. Differences between patient and clinician submitted images: implications for virtual care of skin conditions.

• American Medical Informatics Association (AMIA) Annual Symposium, New Orleans, LA (2023)
• North American Primary Care Research Group (NAPCRG) 51st Annual Meeting, San Francisco, CA (2023)

Sayres R, Rikhye R, Liu Y, Singh P, Ko J, Lin S. Bridging the gap between community, academia, and industry to understand the utility of an AI-powered dermatology tool among everyday users.

• American Medical Informatics Association (AMIA) Annual Symposium, New Orleans, LA (2023)
• North American Primary Care Research Group (NAPCRG) 51st Annual Meeting, San Francisco, CA (2023)

Lin S. Advancing artificial intelligence and machine learning for the future of primary care and population health.

• North American Primary Care Research Group (NAPCRG) 51st Annual Meeting, San Francisco, CA (2023)

Lin S. Editors of family medicine journals meeting: artificial intelligence in family medicine publishing.

• North American Primary Care Research Group (NAPCRG) 51st Annual Meeting, San Francisco, CA (2023)

Lee J, Shah S, Levine M, Suffoletto J, Devon-Sand A, Lamaigre A, Strasser M, Wegrowski A, Smith M, Lin S. Feasibility and acceptability of a population health management tool with AI/ML risk prediction and clinical decision support.

• North American Primary Care Research Group (NAPCRG) 51st Annual Meeting, San Francisco, CA (2023)

Rikhye R, Sayres R, Liu Y, Liu Y, Lin S, Singh P, Ko J. Does the photograph matter? Comparing the accuracy of an AI-based skin condition classifier on patient versus clinician taken images.

• North American Primary Care Research Group (NAPCRG) 51st Annual Meeting, San Francisco, CA (2023)

Crowell T, Jeong J, Hong G, Devon-Sand A, Smith M, Lin S, Sattler A. Revolutionizing trial recruitment: how a quality improvement approach boosted participant engagement and enrollment rates.

• North American Primary Care Research Group (NAPCRG) 51st Annual Meeting, San Francisco, CA (2023)

Smith M, Lin S. Artificial Intelligence and Machine Learning Bootcamp.

• North American Primary Care Research Group (NAPCRG) 51st Annual Meeting, San Francisco, CA (2023)

Shah S, Wegrowski A, Lemaigre A, Desai P. Enabling Innovation at the Bedside Using STARR-OMOP.

• OHDSI 2023 Global Symposium, East Brunswick, NJ (2023)

Lin S, Sakata T, Sattler A, Hong G, Hayes K, Ho K, Shah S. Artificial intelligence at primary and emergency care interface to improve care delivery.

• North American Primary Care Research Group (NAPCRG) 51st Annual Meeting, San Francisco, CA (2023)

Shah, S. Unlocking Pandora’s Box: Generative AI in Healthcare Event.

• Stanford Masters of Science in Clinical Informatics Management Panel, Stanford, CA (2023)

Sattler A. Leveraging Multimodal Artificial Intelligence to Overcome Barriers to Equitable Depression and Anxiety Screening.

• Stanford University Department of Medicine Grand Rounds, Stanford, CA (2023)

Garcia P, Ma S, Smith M, Shah S. Leveraging generative AI for clinician efficiency.

• User Group Meeting, Verona, WI (2023)

Lin S. The future of primary care and population health with artificial intelligence and machine learning.

• AAFP Board of Directors Meeting, Stanford, CA (2023)
• The Future of AI Conference, Stanford Summer Session, Stanford, CA (2023)
• University Health Network Artificial Intelligence Seminar, Toronto, ON, Canada (2023)

Lin S. Generative AI and the future of primary care: a case study.

• Stanford Generative AI and Medicine Seminar, Stanford, CA (2023)

Srinivasan M, Shah S, Levine M, Suffoletto J, Lee J, Devon-Sand A, Smith M, Lin S. Integrating risk prediction tools with actionable insights into value-based health care.

• Stanford STARR Informatics Summit, Stanford, CA (2023)

Lu J, Sattler A, Wang S, Khaki AR, Callahan A, Fleming S, Fong R, Ehlert B, Li RC, Shieh L, Ramchandran K, Gensheimer MF, Chobot S, Pfohl S, Li S, Shum K, Parikh N, Desai P, Seevaratnam B, Hanson M, Smith M, Xu Y, Gokhale A, Lin S, Pfeffer MA, Teuteberg W, Shah NH. Can advance care planning AI models support better end-of-life care?

• American College of Physicians Annual Meeting, San Diego, CA (2023)

Lin S. Advancing artificial intelligence and machine learning for primary care and population health.

• Virginia Tech Carilion School of Medicine Expert Conversation, Roanoke, VA (2023)

Devon-Sand A, Siegel DH, Hong G, Ko J, Gonzalez M, Smith M, Schaekermann M, Hammel N, Strachan P, Singh P, Sayres R, Lin S, Crowell T, Nguyen T, Muralidharan V, Jeong Y, Liu Y, Liu Y. Bridging the gap between community, academia, and industry to understand the usefulness of an AI-powered dermatology tool among everyday users.

• Stanford 21st Annual Community Health Symposium, Stanford, CA (2023)

Lin S. Advancing artificial intelligence and machine learning for primary care and population health.

• UCSF Department of Family and Community Medicine Research Meeting, San Francisco, CA (2023)

Lin S, Sattler A, James C, Gonzalez A, Sendak M, Evans B. Overcoming key barriers to healthcare provider adoption of AI tools.

• Stanford University AI+Health Online Conference, Stanford, CA (2022)

Lin S, Smith M, Jasik C, Gorrepati K, Srinivasan M, Chang S, Sehgal N, Elliott T, Waldren S, Poon E, Gwynne M, Leroy G. Powering the future of continuous and asynchronous healthcare delivery with AI.

• Stanford University AI+Health Online Conference, Stanford, CA (2022)

Lin S, Shah S, Webster D, McCall C, Ko J, Sanders L, Bedgood D, Gonzalez M, Paul R. The role of community-engaged research and public data in advancing healthcare AI.

• Stanford University AI+Health Online Conference, Stanford, CA (2022)

Lin S, Phillips R, Liaw W, Woodard L, Maier J, Kallenberg G, Mandvi A, Jaen CB, Shi Y. Building AI capacity in primary care: supercharging the foundation of health systems.

• Stanford University AI+Health Online Conference, Stanford, CA (2022)

Lin S. Addressing barriers and facilitating clinical adoption of wearables: primary care perspective.

• Stanford Center for Digital Health Think Tank, Stanford, CA (2022)

Sossenheimer P, Hong G, Devon-Sand A, Lin S. Opportunities and challenges of voice assistants in providing public health information: COVID-19 vaccination.

• NAPCRG’s 50th Annual Meeting, Phoenix, AZ (2022)

Sattler A, Levine M, Hong G, Fitzpatrick J, Lin S. Patient, physician, and clinical pharmacist experiences piloting a remote patient monitoring platform for diabetes management.

• NAPCRG’s 50th Annual Meeting, Phoenix, AZ (2022)

Bedgood M, Devon-Sand A, Lin S, Weng K, Sharp C, Shah S. Data driven interventions to reduce documentation burden.

• NAPCRG’s 50th Annual Meeting, Phoenix, AZ (2022)

Bajra R, Frazier W, Graves L, Jacobson K, Rodriguez A, Theobald M, Lin S. Evaluation of a national telemedicine curriculum for medical students and residents: results from a multi-institutional study.

• NAPCRG’s 50th Annual Meeting, Phoenix, AZ (2022)

Shah S, Levine M, Smith M, Lin S. Reducing emergency department visits and hospitalizations with artificial intelligence in primary care.

• NAPCRG’s 50th Annual Meeting, Phoenix, AZ (2022)

Hong G, McMurchie A, Vue J, Masoudian B, Less J, Sifuentes S, Yanamandra A, Sattler A, Lin S. Trends in pediatric primary care visits during the COVID-19 pandemic.

• NAPCRG’s 50th Annual Meeting, Phoenix, AZ (2022)

Lin S. Meeting the moment: addressing barriers and facilitating clinical adoption of artificial intelligence in medical diagnosis.

• NAM-GAO Artificial Intelligence for Medical Diagnosis Webinar, Washington, DC (2022)

Hayes K, Hong G, Sakata T, Sattler A, Shah S, Smith M, Lin S. Role of future artificial intelligence tools for transitional care between emergency and primary care.

• ACEP Research Forum, San Francisco, CA (2022)

Shieh L, Smith M, Westphal J. AI and collaborative workflows predict and prevent clinical deterioration.

• Vizient Connections Business Summit, Las Vegas, NV (2022)

Sattler A, Smith M. Assessing and implementing AI and machine learning to optimize care.

• Vizient Connections Business Summit, Las Vegas, NV (2022)

Lin S. Toward a national strategy for implementing artificial intelligence and machine learning in primary care.

• STFM’s 55th Annual Spring Conference Research Plenary, Indianapolis, IN (2022)
• Philippine College of Physicians Annual Congress Plenary, Manila, Philippines (2022)
• HIMSS22 Machine Learning & AI for Healthcare Forum Keynote, Orlando, FL (2022)
• Stanford Center for Biomedical Informatics Research Colloquium, Stanford, CA (2022)
• Boston University Family Medicine 25th Anniversary Plenary, Boston, MA (2022)
• American Board of Family Medicine Board of Directors Meeting, Portland, OR (2022)
• Atlantic Health-Overlook Family Medicine 50th Anniversary Plenary, Summit, NJ (2022)

Hong G, Smith M, Lin S. The AI will see you now: feasibility and acceptability of a conversational AI medical interviewing system.

• STFM’s 55th Annual Spring Conference, Indianapolis, IN (2022)

Lin S. Practical considerations for implementing AI/ML predictive models to reduce preventable ED visits and hospitalizations.

• STFM’s 55th Annual Spring Conference, Indianapolis, IN (2022)

Lin S. Reimagining patient portals with AI/ML: relieving the burden on health care teams while maximizing the benefits for patients.

• STFM’s 55th Annual Spring Conference, Indianapolis, IN (2022)

Sattler A, Wong M, Schurgin M, Lin S. Healthcare providers’ perspectives inform development of technology-enabled intra-visit care management tools.

• STFM’s 55th Annual Spring Conference, Indianapolis, IN (2022)

Smith M, Lin S. Use of AI and machine learning for healthcare improvement.

• Stanford Medicine Advanced Course in Improvement Science, Palo Alto, CA (2022)

Bajra R, Fuchs L, Patel M, Teerink D, Jortberg B, Theobald M, Lin S. Test driving STFM’s national telemedicine curriculum: results from a multi-institutional pilot.

• STFM’s 55th Annual Spring Conference, Indianapolis, IN (2022)

Lin S, Chen J, Abraham M, Palm E, Bapu A, Ko M. From auto-diagnosis to auto-documentation: advancing the practice of medicine via AI.

• Stanford University AI+Health Conference (2021)

Lin S, Shieh L, Smith M, Li R, Shah S, Sattler S, Srinivasan M. Predicting clinical deterioration with AI.

• Stanford University AI+Health Conference (2021)

Spitler R, Lungren M, Wall D, Paredes P, Lin S. Challenges and opportunities for AI applications in precision health.

• Stanford University AI+Health Conference (2021)

Li R, Sharp C, Langlotz C, Adler-Milstein J, Smith M, Lin S. Clinical integration of AI.

• Stanford University AI+Health Conference (2021)

Halaas M, Langlotz C, Corrado G, Chandross K, Smith M, Vasanawala S. Academic-industry relations and AI.

• Stanford University AI+Health Conference (2021)

Smith M, Li R, Westphal J, Hong G, Lin S, Shieh L. Detect and save: predicting and preventing clinical deterioration using artificial intelligence.

• NAPCRG 49th Annual Meeting (2021)

Hong G, Smith M, Lin S. The AI will see you now: feasibility and acceptability of a conversational AI medical interviewing system.

• NAPCRG 49th Annual Meeting (2021)

Painter A, Lin S, Rahimi S, Abdulhussein H. Artificial intelligence in primary care and population health.

• AIMed Virtual Clinician Series (2021)

Bazemore A, Lin S, Kueper J, Liaw W. Training clinicians to use artificial intelligence.

• Gulf Coast Cluster for Artificial Intelligence in Healthcare (2021)

Lin S. Predicting clinical deterioration in primary care with AI/ML: practical considerations for translating and implementing predictive models to improve population health.

• AIMI Virtual Symposium (2021)

Lin S. Supercharging primary care: the role of AI/ML in predicting clinical deterioration and improving patient-provider electronic communications.

• Google Health Clinician Series (2021)

Lin S. From code to bedside: why and how family medicine should lead the healthcare AI revolution.

• University of Minnesota Family Medicine Grand Rounds (2021)
• STFM's 54th Annual Spring Conference (2021)
• STFM's 33rd Conference on Practice and Quality Improvement (2021)

Smith M, Sattler A, Hong G, Lin S. Implementing artificial intelligence using quality improvement methods.

• STFM's 54th Annual Spring Conference (2021)
• STFM's 33rd Conference on Practice and Quality Improvement (2021)

Hong G, Sattler A, Smith M, Lin S. Providers' experiences with EHR documentation and attitudes toward AI-assisted documentation.

• STFM's 54th Annual Spring Conference (2021)

Sattler A. Using QI methodology to implement big data solutions to solve clinical problems.

• STARR Lightning Talks (2021)

Lin S, Smith M. Setting a research agenda for the use of artificial intelligence and machine learning in primary care.

• ABFM and CPVHC AI/ML in Primary Care Virtual Summit (2021)

Lin S, Bajra R, Fuchs L, Teerink D, Jortberg B. Development of a national telemedicine curriculum for family medicine.

• AAFP Residency Leadership Summit, Kansas City, MO (2021)

Smith M, Lin S. Implementing artificial intelligence using quality improvement methods. 

• SMCI Affiliates and Faculty Lecture Series, Stanford, CA (2021)

Lin S. From code to bedside: why and how family medicine should lead the healthcare AI revolution. 

• STFM Conference on Medical Student Education (2021)
• Michigan State University College of Human Medicine Family Medicine Department Keynote, East Lansing, MI (2021)

Lin S, Peng L, Chapman W, Waldren S. How 2020 changed family medicine forever. 

• AAFP FMIG National Student Webinar (2020)

Li R, Muthu N, Smith M, Kandaswamy S, Chen J. It's not just a last mile problem: partnering with process improvement and human factors to integrate machine learning into healthcare delivery.

• AMIA Virtual Annual Symposium (2020)

Holdsworth L, Park C, Lin S. The potential use of artificial intelligence for pre-visit planning: findings from an environmental scan.

• NAPCRG's 48th Annual Meeting, San Francisco, CA (2020)

Trounce MB, Lin S, Hyams G. Disaster preparedness and lessons learned from the first wave of the COVID-19 pandemic.

• Stanford Medicine-Rambam Health Care Campus Collaboration Symposium (2020)

North S, Lin S, Clancy N, Suri R. Implementing and optimizing virtual care in diverse settings during a pandemic and beyond.

• AAFP's Family Medicine Experience (FMX) Annual Meeting, Chicago, IL (2020)

Lin S. Virtual patient care and telemedicine.

• STFM's Conference on Practice and Quality Improvement, St. Louis, MO (2020)

Sattler A, Smith M. From code to bedside: implementing artificial intelligence using quality improvement methods.

• Quality Improvement Scholarly Concentration Program MED 210: Principles and Practice of Healthcare Quality Improvement, Stanford, CA (2020)

Li R, Smith M. Building AI-enabled systems for patient care at Stanford.

• SMCI Affiliates and Faculty Lecture Series, Stanford, CA (2020)

Bhatia P, Shivade C, Diab M, Wallace B, Gangadharaiah R, Du N, Shafran I, Lin S. Natural language processing for medical conversations.

• Association for Computation Linguistics' 58th Annual Meeting, Seattle, WA (2020)

Hong G, Wang C, Less J, Erbasi N, Folcarelli A, Lin S. AI voice assistants' responses to questions about cancer screening.

• STFM's 53rd Annual Spring Conference, Salt Lake City, UT (2020)
• Stanford Innovations in Medical Education Conference, Stanford, CA (2020)
• Stanford COMET Research Symposium, Stanford, CA (2020)

Lin S. Artificial intelligence and machine learning in primary care.

• AAFP's AI/ML in Primary Care Executive Roundtable, San Jose, CA (2020)

Lin S. The present and future of team documentation: the role of patients, families, and AI.

• Cambridge Healthtech Institute's Digital Health Conference, San Francisco, CA (2020)
• American College of Cardiology's Colloquium on AI, San Francisco, CA (2019)
• Stanford Medicine's EHR National Symposium, Stanford, CA (2019)

Lin S. Ten ways artificial intelligence will transform primary care: implications for medical education.

• STFM's 52nd Annual Spring Conference, Toronto, Ontario (2019)
• STFM's 45th Conference on Medical Student Education, Jacksonville, FL (2019)
• Stanford Clinical Summer Internship, Stanford, CA (2019)