Shannon Wongvibulsin
Assistant Professor, Dermatology
School of Medicine
School of Medicine
B.S., University of California, Los Angeles, 2014, Bioengineering
M.D., Johns Hopkins, 2021, Biomedical Engineering
M.D., Johns Hopkins, 2021, Biomedical Engineering
University of California, Irvine
118 Medical Surge 1
Irvine, CA 92697
118 Medical Surge 1
Irvine, CA 92697
Websites
Academic Distinctions
Nomination to Sigma Xi, The Scientific Research Honor Society | December 2019
Awards and Honors
Dermatology Foundation, Dermatologist Investigator Research Fellowship | 2025
Skin of Color Society Early Career Innovation Award | 2023
Jonathan Epstein Scholar of the Interurban Clinical Club | 2021
1st Place Research Presentation at the 2021 Richard B. Williams American College of Physicians Medical Student Conference for Mid-Atlantic Chapters
Johns Hopkins Young Investigators’ Day David Yue Award | 2021
NIH Individual Predoctoral National Research Service Award (NRSA) MD/PhD Fellowship (F30) | August 2018
3rd Place in the American Medical Informatic Association Student Design Challenge | 2017
Hertz Foundation Fellowship Finalist | 2017
Johns Hopkins University Global Health Initiative Scholar | 2016
Johns Hopkins School of Medicine Innovative Student Award Honorable Mention | 2015
1st Place in Leaders of Tomorrow Summit’s “An Exercise in Innovation” Case Competition | 2015
50 Leaders of Tomorrow (Next Generation of Bioleaders) Award Recipient at the Leaders of Tomorrow Summit | 2015
UCLA Henry Samueli School of Engineering Outstanding Bachelor of Science Award | 2014
UCLA Howard Hughes Undergraduate Research Program Most Distinguished Senior Award | 2014
UCLA Science Poster Day Dean’s Prize | 2014
Edie Wasserman Memorial Senior Prize | 2014
Barry M. Goldwater Scholarship & Excellence in Education Foundation – Goldwater Scholarship 2013
UCLA School of Engineering & Applied Science Scholarships:
- Lockheed Martin & Stanton and Stockwell Architects Scholarship | 2014
- Jon C. Jones Memorial Scholarship| 2013
- John Slaughter Scholarship | 2011, 2012
Howard Hugher Undergraduate Research Program | 2012-2014
UCLA Biomedical Research Summer Scholarship | Summer 2012
UCLA Junior Undergraduate Research Scholar | 2011-2013
Chancellor’s Distinguished Student Awardee | 2011, 2012, 2013, 2014
Skin of Color Society Early Career Innovation Award | 2023
Jonathan Epstein Scholar of the Interurban Clinical Club | 2021
1st Place Research Presentation at the 2021 Richard B. Williams American College of Physicians Medical Student Conference for Mid-Atlantic Chapters
Johns Hopkins Young Investigators’ Day David Yue Award | 2021
NIH Individual Predoctoral National Research Service Award (NRSA) MD/PhD Fellowship (F30) | August 2018
3rd Place in the American Medical Informatic Association Student Design Challenge | 2017
Hertz Foundation Fellowship Finalist | 2017
Johns Hopkins University Global Health Initiative Scholar | 2016
Johns Hopkins School of Medicine Innovative Student Award Honorable Mention | 2015
1st Place in Leaders of Tomorrow Summit’s “An Exercise in Innovation” Case Competition | 2015
50 Leaders of Tomorrow (Next Generation of Bioleaders) Award Recipient at the Leaders of Tomorrow Summit | 2015
UCLA Henry Samueli School of Engineering Outstanding Bachelor of Science Award | 2014
UCLA Howard Hughes Undergraduate Research Program Most Distinguished Senior Award | 2014
UCLA Science Poster Day Dean’s Prize | 2014
Edie Wasserman Memorial Senior Prize | 2014
Barry M. Goldwater Scholarship & Excellence in Education Foundation – Goldwater Scholarship 2013
UCLA School of Engineering & Applied Science Scholarships:
- Lockheed Martin & Stanton and Stockwell Architects Scholarship | 2014
- Jon C. Jones Memorial Scholarship| 2013
- John Slaughter Scholarship | 2011, 2012
Howard Hugher Undergraduate Research Program | 2012-2014
UCLA Biomedical Research Summer Scholarship | Summer 2012
UCLA Junior Undergraduate Research Scholar | 2011-2013
Chancellor’s Distinguished Student Awardee | 2011, 2012, 2013, 2014
Publications
1. Dovigi E, Wongvibulsin S, Lee I, Novoa R, Cai Z, Rotemberg V, Daneshjou R. Augmented intelligence and dermatology-Part II: Bias, benchmarks, guidelines, ethics, regulation, and future directions. J Am Acad Dermatol. 2026 Jan;94(1):11-19. doi: 10.1016/j.jaad.2024.10.132. Epub 2025 Mar 14. PMID: 40090590.
2. Tang HS, Ebriani J, Yan MJ, Wongvibulsin S, Farshchian M. Artificial Intelligence in Patch Testing: Comprehensive Review of Current Applications and Future Prospects in Dermatology. JMIR Dermatol. 2025 Jun 2;8:e67154. doi: 10.2196/67154. PMID: 40457817; PMCID: PMC12178223.
3. Wongvibulsin S, Lee I. Artificial Intelligence and Dermatology. JAMA Dermatol. 2025 Mar 1;161(3):344. doi: 10.1001/jamadermatol.2024.4645. PMID: 39774621.
4. Johri S, Jeong J, Tran BA, Schlessinger DI, Wongvibulsin S, Barnes LA, Zhou HY, Cai ZR, Van Allen EM, Kim D, Daneshjou R, Rajpurkar P. An evaluation framework for clinical use of large language models in patient interaction tasks. Nat Med. 2025 Jan;31(1):77-86. doi: 10.1038/s41591-024-03328-5. Epub 2025 Jan 2. PMID: 39747685.
5. Wongvibulsin S, Yan MJ, Pahalyants V, Murphy W, Daneshjou R, Rotemberg V. Current State of Dermatology Mobile Applications With Artificial Intelligence Features. JAMA Dermatol. 2024 Jun 1;160(6):646-650. doi: 10.1001/jamadermatol.2024.0468. Erratum in: JAMA Dermatol. 2024 Jun 1;160(6):688. doi: 10.1001/jamadermatol.2024.1011. Erratum in: JAMA Dermatol. 2024 Jun 1;160(6):688. doi: 10.1001/jamadermatol.2024.1342. PMID: 38452263; PMCID: PMC10921342.
6. Lee I, Aninos A, Lester J, Rotemberg V, Schlessinger DI, Weed J, Wongvibulsin S, Daneshjou R. Engaging industry effectively and ethically in artificial intelligence from the Augmented Artificial Intelligence Committee Standards Workgroup. J Am Acad Dermatol. 2024 Aug;91(2):312-314. doi: 10.1016/j.jaad.2024.03.036. Epub 2024 Apr 30. PMID: 38691074.
7. Gui H, Rezaei SJ, Schlessinger D, Weed J, Lester J, Wongvibulsin S, Mitchell D, Ko J, Rotemberg V, Lee I, Daneshjou R. Dermatologists' Perspectives and Usage of Large Language Models in Practice: An Exploratory Survey. J Invest Dermatol. 2024 Oct;144(10):2298-2301. doi: 10.1016/j.jid.2024.03.028. Epub 2024 Apr 4. PMID: 38582369.
8. Wongvibulsin S, Sangers T, Clibborn C, Li YJ, Sharma N, Common JEA, Reynolds NJ, Tanaka RJ. A Report and Proposals for Future Activity from the Inaugural Artificial Intelligence in Dermatology Symposium Held at the International Societies for Investigative Dermatology 2023 Meeting. JID Innov. 2023 Sep 22;4(1):100236. doi: 10.1016/j.xjidi.2023.100236. PMID: 38282650; PMCID: PMC10810829.
9. Wongvibulsin S, Adamson AS. Deep learning for Mpox: Advances, challenges, and opportunities. Med. 2023 May 12;4(5):283-284. doi: 10.1016/j.medj.2023.04.002. PMID: 37178679; PMCID: PMC10176662.
10. Wongvibulsin S, Frech TM, Chren MM, Tkaczyk ER. Expanding Personalized, Data-Driven Dermatology: Leveraging Digital Health Technology and Machine Learning to Improve Patient Outcomes. JID Innov. 2022 Feb 1;2(3):100105. doi: 10.1016/j.xjidi.2022.100105. PMID: 35462957; PMCID: PMC9026581.
11. Kulkarni V, Okoye GA, Garza LA, Wongvibulsin S. Geospatial Heterogeneity of Hidradenitis Suppurativa Searches in the United States: Infodemiology Study of Google Search Data. JMIR Dermatol. 2022 Jun 9;5(2):e34594. doi: 10.2196/34594. PMID: 37632873; PMCID: PMC10334890.
12. Wongvibulsin S, Feterik K. Recommendations for Better Adoption of Medical Photography as a Clinical Tool. Interact J Med Res. 2022 Jul 18;11(2):e36102. doi: 10.2196/36102. PMID: 35849427; PMCID: PMC9345030.
13. Wongvibulsin S, Parthasarathy V, Pahalyants V, Murphy W, Sutaria N, Roh YS, Bordeaux ZA, Deng J, Taylor MT, Semenov YR, Kwatra SG. Latent class analysis identification of prurigo nodularis comorbidity phenotypes. Br J Dermatol. 2022 May;186(5):903-905. doi: 10.1111/bjd.20957. Epub 2022 Mar 25. PMID: 34927720.
14. Wongvibulsin S, Garibaldi BT, Antar AAR, Wen J, Wang MC, Gupta A, Bollinger R, Xu Y, Wang K, Betz JF, Muschelli J, Bandeen-Roche K, Zeger SL, Robinson ML. Development of Severe COVID-19 Adaptive Risk Predictor (SCARP), a Calculator to Predict Severe Disease or Death in Hospitalized Patients With COVID-19. Ann Intern Med. 2021 Jun;174(6):777-785. doi: 10.7326/M20-6754. Epub 2021 Mar 2. PMID: 33646849; PMCID: PMC7934337.
15. Wongvibulsin S, Sutaria N, Williams KA, Huang AH, Choi J, Roh YS, Hong M, Kelley D, Pahalyants V, Murphy W, Alphonse MP, Bakhshi P, Walia A, Semenov YR, Kwatra SG. A Nationwide Study of Prurigo Nodularis: Disease Burden and Healthcare Utilization in the United States. J Invest Dermatol. 2021 Oct;141(10):2530-2533.e1. doi: 10.1016/j.jid.2021.02.756. Epub 2021 Apr 3. PMID: 33823182; PMCID: PMC8603386.
16. Belzberg M, Alphonse MP, Brown I, Williams KA, Khanna R, Ho B, Wongvibulsin S, Pritchard T, Roh YS, Sutaria N, Choi J, Jedrych J, Johnston AD, Sarkar K, Vasavda C, Meixiong J, Dillen C, Bondesgaard K, Paolini JF, Chen W, Corcoran D, Devos N, Kwatra MM, Chien AL, Archer NK, Garza LA, Dong X, Kang S, Kwatra SG. Prurigo Nodularis Is Characterized by Systemic and Cutaneous T Helper 22 Immune Polarization. J Invest Dermatol. 2021 Sep;141(9):2208-2218.e14. doi: 10.1016/j.jid.2021.02.749. Epub 2021 Mar 23. PMID: 33771530; PMCID: PMC8384659.
17. Sutaria N, Alphonse MP, Marani M, Parthasarathy V, Deng J, Wongvibulsin S, Williams K, Roh YS, Choi J, Bordeaux Z, Pritchard T, Dillen C, Semenov YR, Kwatra MM, Archer NK, Garza LA, Dong X, Kang S, Kwatra SG. Cluster Analysis of Circulating Plasma Biomarkers in Prurigo Nodularis Reveals a Distinct Systemic Inflammatory Signature in African Americans. J Invest Dermatol. 2022 May;142(5):1300-1308.e3. doi: 10.1016/j.jid.2021.10.011. Epub 2021 Oct 27. PMID: 34717952; PMCID: PMC9038640.
18. Roh YS, Huang AH, Sutaria N, Choi U, Wongvibulsin S, Choi J, Bordeaux ZA, Parthasarathy V, Deng J, Patel DP, Canner JK, Grossberg AL, Kwatra SG. Real-world comorbidities of atopic dermatitis in the US adult ambulatory population. J Am Acad Dermatol. 2022 Apr;86(4):835-845. doi: 10.1016/j.jaad.2021.11.014. Epub 2021 Nov 18. PMID: 34800600.
19. Knowles KA, Xun H, Jang S, Pang S, Ng C, Sharma A, Spaulding EM, Singh R, Diab A, Osuji N, Materi J, Amundsen D, Wongvibulsin S, Weng D, Huynh P, Nanavati J, Wolff J, Marvel FA, Martin SS. Clinicians for CARE: A Systematic Review and Meta-Analysis of Interventions to Support Caregivers of Patients With Heart Disease. J Am Heart Assoc. 2021 Dec 21;10(24):e019706. doi: 10.1161/JAHA.120.019706. Epub 2021 Dec 7. PMID: 34873919; PMCID: PMC9075249.
20. Marvel FA, Spaulding EM, Lee MA, Yang WE, Demo R, Ding J, Wang J, Xun H, Shah LM, Weng D, Carter J, Majmudar M, Elgin E, Sheidy J, McLin R, Flowers J, Vilarino V, Lumelsky DN, Bhardwaj V, Padula WV, Shan R, Huynh PP, Wongvibulsin S, Leung C, Allen JK, Martin SS. Digital Health Intervention in Acute Myocardial Infarction. Circ Cardiovasc Qual Outcomes. 2021 Jul;14(7):e007741. doi: 10.1161/CIRCOUTCOMES.121.007741. Epub 2021 Jul 15. PMID: 34261332; PMCID: PMC8288197.
21. Bhardwaj V, Spaulding EM, Marvel FA, LaFave S, Yu J, Mota D, Lorigiano TJ, Huynh PP, Shan R, Yesantharao PS, Lee MA, Yang WE, Demo R, Ding J, Wang J, Xun H, Shah L, Weng D, Wongvibulsin S, Carter J, Sheidy J, McLin R, Flowers J, Majmudar M, Elgin E, Vilarino V, Lumelsky D, Leung C, Allen JK, Martin SS, Padula WV. Cost-effectiveness of a Digital Health Intervention for Acute Myocardial Infarction Recovery. Med Care. 2021 Nov 1;59(11):1023-1030. doi: 10.1097/MLR.0000000000001636. PMID: 34534188; PMCID: PMC8516712.
22. Kalinich M, Murphy W, Wongvibulsin S, Pahalyants V, Yu KH, Lu C, Wang F, Zubiri L, Naranbhai V, Gusev A, Kwatra SG, Reynolds KL, Semenov YR. Prediction of severe immune-related adverse events requiring hospital admission in patients on immune checkpoint inhibitors: study of a population level insurance claims database from the USA. J Immunother Cancer. 2021 Mar;9(3):e001935. doi: 10.1136/jitc-2020-001935. PMID: 33789879; PMCID: PMC8016099.
23. Wongvibulsin S, Pahalyants V, Kalinich M, Murphy W, Yu KH, Wang F, Chen ST, Reynolds K, Kwatra SG, Semenov YR. Epidemiology and risk factors for the development of cutaneous toxicities in patients treated with immune-checkpoint inhibitors: A United States population-level analysis. J Am Acad Dermatol. 2022 Mar;86(3):563-572. doi: 10.1016/j.jaad.2021.03.094. Epub 2021 Apr 2. PMID: 33819538; PMCID: PMC10285344.
24. Wongvibulsin S, Sutaria N, Kannan S, Alphonse MP, Belzberg M, Williams KA, Brown ID, Choi J, Roh YS, Pritchard T, Khanna R, Eseonu AC, Jedrych J, Dillen C, Kwatra MM, Chien AL, Archer N, Garza LA, Dong X, Kang S, Kwatra SG. Transcriptomic analysis of atopic dermatitis in African Americans is characterized by Th2/Th17-centered cutaneous immune activation. Sci Rep. 2021 May 27;11(1):11175. doi: 10.1038/s41598-021-90105-w. PMID: 34045476; PMCID: PMC8160001.
25. Aggarwal P, Choi J, Sutaria N, Roh YS, Wongvibulsin S, Williams KA, Huang AH, Boozalis E, Le T, Chavda R, Gabriel S, Kwatra SG. Clinical characteristics and disease burden in prurigo nodularis. Clin Exp Dermatol. 2021 Oct;46(7):1277-1284. doi: 10.1111/ced.14722. Epub 2021 Jun 22. PMID: 33969517.
26. Wongvibulsin S, Habeos EE, Huynh PP, Xun H, Shan R, Porosnicu Rodriguez KA, Wang J, Gandapur YK, Osuji N, Shah LM, Spaulding EM, Hung G, Knowles K, Yang WE, Marvel FA, Levin E, Maron DJ, Gordon NF, Martin SS. Digital Health Interventions for Cardiac Rehabilitation: Systematic Literature Review. J Med Internet Res. 2021 Feb 8;23(2):e18773. doi: 10.2196/18773. PMID: 33555259; PMCID: PMC7899799.
27. Wu KC, Wongvibulsin S, Tao S, Ashikaga H, Stillabower M, Dickfeld TM, Marine JE, Weiss RG, Tomaselli GF, Zeger SL. Baseline and Dynamic Risk Predictors of Appropriate Implantable Cardioverter Defibrillator Therapy. J Am Heart Assoc. 2020 Oct 20;9(20):e017002. doi: 10.1161/JAHA.120.017002. Epub 2020 Oct 7. PMID: 33023350; PMCID: PMC7763383.
28. Wongvibulsin S, Wu KC, Zeger SL. Improving Clinical Translation of Machine Learning Approaches Through Clinician-Tailored Visual Displays of Black Box Algorithms: Development and Validation. JMIR Med Inform. 2020 Jun 9;8(6):e15791. doi: 10.2196/15791. PMID: 32515746; PMCID: PMC7312245.
29. Radin JM, Peters S, Ariniello L, Wongvibulsin S, Galarnyk M, Waalen J, Steinhubl SR. Pregnancy health in POWERMOM participants living in rural versus urban zip codes. J Clin Transl Sci. 2020 Apr 6;4(5):457-462. doi: 10.1017/cts.2020.33. PMID: 33244436; PMCID: PMC7681139.
30. Wongvibulsin S, Rich AS, Rudin C, Jacoby DMP, et al. AI reflections in 2019. Nat Mach Intell 2, 2–9 (2020). https://doi.org/10.1038/s42256-019-0141-1.
31. Wongvibulsin, S., Wu, K.C. & Zeger, S.L. Clinical risk prediction with random forests for survival, longitudinal, and multivariate (RF-SLAM) data analysis. BMC Med Res Methodol 20, 1 (2020). https://doi.org/10.1186/s12874-019-0863-0.
32. Wongvibulsin S, Zeger SL. Enabling individualised health in learning healthcare systems. BMJ Evid Based Med. 2020 Aug;25(4):125-129. doi: 10.1136/bmjebm-2019-111190. Epub 2019 May 11. PMID: 31079062; PMCID: PMC7418610.
33. Yang WE, Shah LM, Spaulding EM, Wang J, Xun H, Weng D, Shan R, Wongvibulsin S, Marvel FA, Martin SS. The role of a clinician amid the rise of mobile health technology. J Am Med Inform Assoc. 2019 Nov 1;26(11):1385-1388. doi: 10.1093/jamia/ocz131. PMID: 31373364; PMCID: PMC6798562.
34. Shah LM, Yang WE, Demo RC, Lee MA, Weng D, Shan R, Wongvibulsin S, Spaulding EM, Marvel FA, Martin SS. Technical Guidance for Clinicians Interested in Partnering With Engineers in Mobile Health Development and Evaluation. JMIR Mhealth Uhealth. 2019 May 15;7(5):e14124. doi: 10.2196/14124. Erratum in: JMIR Mhealth Uhealth. 2022 Aug 18;10(8):e41813. doi: 10.2196/41813. PMID: 31094337; PMCID: PMC6540720.
35. Wongvibulsin S, Martin SS, Saria S, Zeger SL, Murphy SA. An Individualized, Data-Driven Digital Approach for Precision Behavior Change. Am J Lifestyle Med. 2019 Apr 25;14(3):289-293. doi: 10.1177/1559827619843489. PMID: 32477031; PMCID: PMC7232899.
36. Wongvibulsin S. Educational strategies to foster diversity and inclusion in machine intelligence. Nat Mach Intell. 2019 Feb;1(2):70-71. doi: 10.1038/s42256-019-0021-8. Epub 2019 Jan 28. PMID: 31396582; PMCID: PMC6687322.
37. Wongvibulsin S, Martin SS, Steinhubl SR, Muse ED. Connected Health Technology for Cardiovascular Disease Prevention and Management. Curr Treat Options Cardiovasc Med. 2019 May 18;21(6):29. doi: 10.1007/s11936-019-0729-0. PMID: 31104157; PMCID: PMC7263827.
38. Wongvibulsin S, Ho BK, Kwatra SG. Embracing machine learning and digital health technology for precision dermatology. J Dermatolog Treat. 2020 Aug;31(5):494-495. doi: 10.1080/09546634.2019.1623373. Epub 2019 Jun 14. PMID: 31122081; PMCID: PMC6911024.
39. Wongvibulsin S, Khanna R, Kwatra SG. Anatomic localization and quantitative analysis of the burden of itch in the United States. J Am Acad Dermatol. 2020 Jan;82(1):234-236. doi: 10.1016/j.jaad.2019.06.029. Epub 2019 Jun 20. PMID: 31228522; PMCID: PMC8720279.
40. Yang WE, Spaulding EM, Lumelsky D, Hung G, Huynh PP, Knowles K, Marvel FA, Vilarino V, Wang J, Shah LM, Xun H, Shan R, Wongvibulsin S, Martin SS. Strategies for the Successful Implementation of a Novel iPhone Loaner System (iShare) in mHealth Interventions: Prospective Study. JMIR Mhealth Uhealth. 2019 Dec 16;7(12):e16391. doi: 10.2196/16391. Erratum in: JMIR Mhealth Uhealth. 2021 Sep 20;9(9):e31472. doi: 10.2196/31472. PMID: 31841115; PMCID: PMC6937543.
41. Delva S, Waligora Mendez KJ, Cajita M, Koirala B, Shan R, Wongvibulsin S, Vilarino V, Gilmore DR, Han HR. Efficacy of Mobile Health for Self-management of Cardiometabolic Risk Factors: A Theory-Guided Systematic Review. J Cardiovasc Nurs. 2021 Jan/Feb;36(1):34-55. doi: 10.1097/JCN.0000000000000659. PMID: 32040072; PMCID: PMC7713761.
42. Wongvibulsin S, Daza EJ. Generating Actionable Insights: Machine Learning for Causal Inference with Individual-Level Patient Generated Data. MLHC: Proceedings of Machine Learning Research. 2018.
43. Wang J, Wongvibulsin S, Henry K, Fujita S. Quantifying and Visualizing Medication Adherence in Patients Following Acute Myocardial Infarction. AMIA Annu Symp Proc. 2018 Apr 16;2017:2299-2303. PMID: 29854272; PMCID: PMC5977657.
44. Wongvibulsin, Shannon & Vazirani, Sondra & Li, Zhaoping & Heber, David. (2014). Vitamin D - Beyond Bones: Its Relationship to Obesity, Metabolic Syndrome, and Diabetes. Journal of Nutritional Therapeutics. 3. 133-141. 10.6000/1929-5634.2014.03.03.4.
45. Wongvibulsin S, Lee SS, Hui KK. Achieving Balance Through the Art of Eating: Demystifying Eastern Nutrition and Blending it with Western Nutrition. J Tradit Complement Med. 2012 Jan;2(1):1-5. doi: 10.1016/s2225-4110(16)30065-7. PMID: 24716109; PMCID: PMC3943006.
2. Tang HS, Ebriani J, Yan MJ, Wongvibulsin S, Farshchian M. Artificial Intelligence in Patch Testing: Comprehensive Review of Current Applications and Future Prospects in Dermatology. JMIR Dermatol. 2025 Jun 2;8:e67154. doi: 10.2196/67154. PMID: 40457817; PMCID: PMC12178223.
3. Wongvibulsin S, Lee I. Artificial Intelligence and Dermatology. JAMA Dermatol. 2025 Mar 1;161(3):344. doi: 10.1001/jamadermatol.2024.4645. PMID: 39774621.
4. Johri S, Jeong J, Tran BA, Schlessinger DI, Wongvibulsin S, Barnes LA, Zhou HY, Cai ZR, Van Allen EM, Kim D, Daneshjou R, Rajpurkar P. An evaluation framework for clinical use of large language models in patient interaction tasks. Nat Med. 2025 Jan;31(1):77-86. doi: 10.1038/s41591-024-03328-5. Epub 2025 Jan 2. PMID: 39747685.
5. Wongvibulsin S, Yan MJ, Pahalyants V, Murphy W, Daneshjou R, Rotemberg V. Current State of Dermatology Mobile Applications With Artificial Intelligence Features. JAMA Dermatol. 2024 Jun 1;160(6):646-650. doi: 10.1001/jamadermatol.2024.0468. Erratum in: JAMA Dermatol. 2024 Jun 1;160(6):688. doi: 10.1001/jamadermatol.2024.1011. Erratum in: JAMA Dermatol. 2024 Jun 1;160(6):688. doi: 10.1001/jamadermatol.2024.1342. PMID: 38452263; PMCID: PMC10921342.
6. Lee I, Aninos A, Lester J, Rotemberg V, Schlessinger DI, Weed J, Wongvibulsin S, Daneshjou R. Engaging industry effectively and ethically in artificial intelligence from the Augmented Artificial Intelligence Committee Standards Workgroup. J Am Acad Dermatol. 2024 Aug;91(2):312-314. doi: 10.1016/j.jaad.2024.03.036. Epub 2024 Apr 30. PMID: 38691074.
7. Gui H, Rezaei SJ, Schlessinger D, Weed J, Lester J, Wongvibulsin S, Mitchell D, Ko J, Rotemberg V, Lee I, Daneshjou R. Dermatologists' Perspectives and Usage of Large Language Models in Practice: An Exploratory Survey. J Invest Dermatol. 2024 Oct;144(10):2298-2301. doi: 10.1016/j.jid.2024.03.028. Epub 2024 Apr 4. PMID: 38582369.
8. Wongvibulsin S, Sangers T, Clibborn C, Li YJ, Sharma N, Common JEA, Reynolds NJ, Tanaka RJ. A Report and Proposals for Future Activity from the Inaugural Artificial Intelligence in Dermatology Symposium Held at the International Societies for Investigative Dermatology 2023 Meeting. JID Innov. 2023 Sep 22;4(1):100236. doi: 10.1016/j.xjidi.2023.100236. PMID: 38282650; PMCID: PMC10810829.
9. Wongvibulsin S, Adamson AS. Deep learning for Mpox: Advances, challenges, and opportunities. Med. 2023 May 12;4(5):283-284. doi: 10.1016/j.medj.2023.04.002. PMID: 37178679; PMCID: PMC10176662.
10. Wongvibulsin S, Frech TM, Chren MM, Tkaczyk ER. Expanding Personalized, Data-Driven Dermatology: Leveraging Digital Health Technology and Machine Learning to Improve Patient Outcomes. JID Innov. 2022 Feb 1;2(3):100105. doi: 10.1016/j.xjidi.2022.100105. PMID: 35462957; PMCID: PMC9026581.
11. Kulkarni V, Okoye GA, Garza LA, Wongvibulsin S. Geospatial Heterogeneity of Hidradenitis Suppurativa Searches in the United States: Infodemiology Study of Google Search Data. JMIR Dermatol. 2022 Jun 9;5(2):e34594. doi: 10.2196/34594. PMID: 37632873; PMCID: PMC10334890.
12. Wongvibulsin S, Feterik K. Recommendations for Better Adoption of Medical Photography as a Clinical Tool. Interact J Med Res. 2022 Jul 18;11(2):e36102. doi: 10.2196/36102. PMID: 35849427; PMCID: PMC9345030.
13. Wongvibulsin S, Parthasarathy V, Pahalyants V, Murphy W, Sutaria N, Roh YS, Bordeaux ZA, Deng J, Taylor MT, Semenov YR, Kwatra SG. Latent class analysis identification of prurigo nodularis comorbidity phenotypes. Br J Dermatol. 2022 May;186(5):903-905. doi: 10.1111/bjd.20957. Epub 2022 Mar 25. PMID: 34927720.
14. Wongvibulsin S, Garibaldi BT, Antar AAR, Wen J, Wang MC, Gupta A, Bollinger R, Xu Y, Wang K, Betz JF, Muschelli J, Bandeen-Roche K, Zeger SL, Robinson ML. Development of Severe COVID-19 Adaptive Risk Predictor (SCARP), a Calculator to Predict Severe Disease or Death in Hospitalized Patients With COVID-19. Ann Intern Med. 2021 Jun;174(6):777-785. doi: 10.7326/M20-6754. Epub 2021 Mar 2. PMID: 33646849; PMCID: PMC7934337.
15. Wongvibulsin S, Sutaria N, Williams KA, Huang AH, Choi J, Roh YS, Hong M, Kelley D, Pahalyants V, Murphy W, Alphonse MP, Bakhshi P, Walia A, Semenov YR, Kwatra SG. A Nationwide Study of Prurigo Nodularis: Disease Burden and Healthcare Utilization in the United States. J Invest Dermatol. 2021 Oct;141(10):2530-2533.e1. doi: 10.1016/j.jid.2021.02.756. Epub 2021 Apr 3. PMID: 33823182; PMCID: PMC8603386.
16. Belzberg M, Alphonse MP, Brown I, Williams KA, Khanna R, Ho B, Wongvibulsin S, Pritchard T, Roh YS, Sutaria N, Choi J, Jedrych J, Johnston AD, Sarkar K, Vasavda C, Meixiong J, Dillen C, Bondesgaard K, Paolini JF, Chen W, Corcoran D, Devos N, Kwatra MM, Chien AL, Archer NK, Garza LA, Dong X, Kang S, Kwatra SG. Prurigo Nodularis Is Characterized by Systemic and Cutaneous T Helper 22 Immune Polarization. J Invest Dermatol. 2021 Sep;141(9):2208-2218.e14. doi: 10.1016/j.jid.2021.02.749. Epub 2021 Mar 23. PMID: 33771530; PMCID: PMC8384659.
17. Sutaria N, Alphonse MP, Marani M, Parthasarathy V, Deng J, Wongvibulsin S, Williams K, Roh YS, Choi J, Bordeaux Z, Pritchard T, Dillen C, Semenov YR, Kwatra MM, Archer NK, Garza LA, Dong X, Kang S, Kwatra SG. Cluster Analysis of Circulating Plasma Biomarkers in Prurigo Nodularis Reveals a Distinct Systemic Inflammatory Signature in African Americans. J Invest Dermatol. 2022 May;142(5):1300-1308.e3. doi: 10.1016/j.jid.2021.10.011. Epub 2021 Oct 27. PMID: 34717952; PMCID: PMC9038640.
18. Roh YS, Huang AH, Sutaria N, Choi U, Wongvibulsin S, Choi J, Bordeaux ZA, Parthasarathy V, Deng J, Patel DP, Canner JK, Grossberg AL, Kwatra SG. Real-world comorbidities of atopic dermatitis in the US adult ambulatory population. J Am Acad Dermatol. 2022 Apr;86(4):835-845. doi: 10.1016/j.jaad.2021.11.014. Epub 2021 Nov 18. PMID: 34800600.
19. Knowles KA, Xun H, Jang S, Pang S, Ng C, Sharma A, Spaulding EM, Singh R, Diab A, Osuji N, Materi J, Amundsen D, Wongvibulsin S, Weng D, Huynh P, Nanavati J, Wolff J, Marvel FA, Martin SS. Clinicians for CARE: A Systematic Review and Meta-Analysis of Interventions to Support Caregivers of Patients With Heart Disease. J Am Heart Assoc. 2021 Dec 21;10(24):e019706. doi: 10.1161/JAHA.120.019706. Epub 2021 Dec 7. PMID: 34873919; PMCID: PMC9075249.
20. Marvel FA, Spaulding EM, Lee MA, Yang WE, Demo R, Ding J, Wang J, Xun H, Shah LM, Weng D, Carter J, Majmudar M, Elgin E, Sheidy J, McLin R, Flowers J, Vilarino V, Lumelsky DN, Bhardwaj V, Padula WV, Shan R, Huynh PP, Wongvibulsin S, Leung C, Allen JK, Martin SS. Digital Health Intervention in Acute Myocardial Infarction. Circ Cardiovasc Qual Outcomes. 2021 Jul;14(7):e007741. doi: 10.1161/CIRCOUTCOMES.121.007741. Epub 2021 Jul 15. PMID: 34261332; PMCID: PMC8288197.
21. Bhardwaj V, Spaulding EM, Marvel FA, LaFave S, Yu J, Mota D, Lorigiano TJ, Huynh PP, Shan R, Yesantharao PS, Lee MA, Yang WE, Demo R, Ding J, Wang J, Xun H, Shah L, Weng D, Wongvibulsin S, Carter J, Sheidy J, McLin R, Flowers J, Majmudar M, Elgin E, Vilarino V, Lumelsky D, Leung C, Allen JK, Martin SS, Padula WV. Cost-effectiveness of a Digital Health Intervention for Acute Myocardial Infarction Recovery. Med Care. 2021 Nov 1;59(11):1023-1030. doi: 10.1097/MLR.0000000000001636. PMID: 34534188; PMCID: PMC8516712.
22. Kalinich M, Murphy W, Wongvibulsin S, Pahalyants V, Yu KH, Lu C, Wang F, Zubiri L, Naranbhai V, Gusev A, Kwatra SG, Reynolds KL, Semenov YR. Prediction of severe immune-related adverse events requiring hospital admission in patients on immune checkpoint inhibitors: study of a population level insurance claims database from the USA. J Immunother Cancer. 2021 Mar;9(3):e001935. doi: 10.1136/jitc-2020-001935. PMID: 33789879; PMCID: PMC8016099.
23. Wongvibulsin S, Pahalyants V, Kalinich M, Murphy W, Yu KH, Wang F, Chen ST, Reynolds K, Kwatra SG, Semenov YR. Epidemiology and risk factors for the development of cutaneous toxicities in patients treated with immune-checkpoint inhibitors: A United States population-level analysis. J Am Acad Dermatol. 2022 Mar;86(3):563-572. doi: 10.1016/j.jaad.2021.03.094. Epub 2021 Apr 2. PMID: 33819538; PMCID: PMC10285344.
24. Wongvibulsin S, Sutaria N, Kannan S, Alphonse MP, Belzberg M, Williams KA, Brown ID, Choi J, Roh YS, Pritchard T, Khanna R, Eseonu AC, Jedrych J, Dillen C, Kwatra MM, Chien AL, Archer N, Garza LA, Dong X, Kang S, Kwatra SG. Transcriptomic analysis of atopic dermatitis in African Americans is characterized by Th2/Th17-centered cutaneous immune activation. Sci Rep. 2021 May 27;11(1):11175. doi: 10.1038/s41598-021-90105-w. PMID: 34045476; PMCID: PMC8160001.
25. Aggarwal P, Choi J, Sutaria N, Roh YS, Wongvibulsin S, Williams KA, Huang AH, Boozalis E, Le T, Chavda R, Gabriel S, Kwatra SG. Clinical characteristics and disease burden in prurigo nodularis. Clin Exp Dermatol. 2021 Oct;46(7):1277-1284. doi: 10.1111/ced.14722. Epub 2021 Jun 22. PMID: 33969517.
26. Wongvibulsin S, Habeos EE, Huynh PP, Xun H, Shan R, Porosnicu Rodriguez KA, Wang J, Gandapur YK, Osuji N, Shah LM, Spaulding EM, Hung G, Knowles K, Yang WE, Marvel FA, Levin E, Maron DJ, Gordon NF, Martin SS. Digital Health Interventions for Cardiac Rehabilitation: Systematic Literature Review. J Med Internet Res. 2021 Feb 8;23(2):e18773. doi: 10.2196/18773. PMID: 33555259; PMCID: PMC7899799.
27. Wu KC, Wongvibulsin S, Tao S, Ashikaga H, Stillabower M, Dickfeld TM, Marine JE, Weiss RG, Tomaselli GF, Zeger SL. Baseline and Dynamic Risk Predictors of Appropriate Implantable Cardioverter Defibrillator Therapy. J Am Heart Assoc. 2020 Oct 20;9(20):e017002. doi: 10.1161/JAHA.120.017002. Epub 2020 Oct 7. PMID: 33023350; PMCID: PMC7763383.
28. Wongvibulsin S, Wu KC, Zeger SL. Improving Clinical Translation of Machine Learning Approaches Through Clinician-Tailored Visual Displays of Black Box Algorithms: Development and Validation. JMIR Med Inform. 2020 Jun 9;8(6):e15791. doi: 10.2196/15791. PMID: 32515746; PMCID: PMC7312245.
29. Radin JM, Peters S, Ariniello L, Wongvibulsin S, Galarnyk M, Waalen J, Steinhubl SR. Pregnancy health in POWERMOM participants living in rural versus urban zip codes. J Clin Transl Sci. 2020 Apr 6;4(5):457-462. doi: 10.1017/cts.2020.33. PMID: 33244436; PMCID: PMC7681139.
30. Wongvibulsin S, Rich AS, Rudin C, Jacoby DMP, et al. AI reflections in 2019. Nat Mach Intell 2, 2–9 (2020). https://doi.org/10.1038/s42256-019-0141-1.
31. Wongvibulsin, S., Wu, K.C. & Zeger, S.L. Clinical risk prediction with random forests for survival, longitudinal, and multivariate (RF-SLAM) data analysis. BMC Med Res Methodol 20, 1 (2020). https://doi.org/10.1186/s12874-019-0863-0.
32. Wongvibulsin S, Zeger SL. Enabling individualised health in learning healthcare systems. BMJ Evid Based Med. 2020 Aug;25(4):125-129. doi: 10.1136/bmjebm-2019-111190. Epub 2019 May 11. PMID: 31079062; PMCID: PMC7418610.
33. Yang WE, Shah LM, Spaulding EM, Wang J, Xun H, Weng D, Shan R, Wongvibulsin S, Marvel FA, Martin SS. The role of a clinician amid the rise of mobile health technology. J Am Med Inform Assoc. 2019 Nov 1;26(11):1385-1388. doi: 10.1093/jamia/ocz131. PMID: 31373364; PMCID: PMC6798562.
34. Shah LM, Yang WE, Demo RC, Lee MA, Weng D, Shan R, Wongvibulsin S, Spaulding EM, Marvel FA, Martin SS. Technical Guidance for Clinicians Interested in Partnering With Engineers in Mobile Health Development and Evaluation. JMIR Mhealth Uhealth. 2019 May 15;7(5):e14124. doi: 10.2196/14124. Erratum in: JMIR Mhealth Uhealth. 2022 Aug 18;10(8):e41813. doi: 10.2196/41813. PMID: 31094337; PMCID: PMC6540720.
35. Wongvibulsin S, Martin SS, Saria S, Zeger SL, Murphy SA. An Individualized, Data-Driven Digital Approach for Precision Behavior Change. Am J Lifestyle Med. 2019 Apr 25;14(3):289-293. doi: 10.1177/1559827619843489. PMID: 32477031; PMCID: PMC7232899.
36. Wongvibulsin S. Educational strategies to foster diversity and inclusion in machine intelligence. Nat Mach Intell. 2019 Feb;1(2):70-71. doi: 10.1038/s42256-019-0021-8. Epub 2019 Jan 28. PMID: 31396582; PMCID: PMC6687322.
37. Wongvibulsin S, Martin SS, Steinhubl SR, Muse ED. Connected Health Technology for Cardiovascular Disease Prevention and Management. Curr Treat Options Cardiovasc Med. 2019 May 18;21(6):29. doi: 10.1007/s11936-019-0729-0. PMID: 31104157; PMCID: PMC7263827.
38. Wongvibulsin S, Ho BK, Kwatra SG. Embracing machine learning and digital health technology for precision dermatology. J Dermatolog Treat. 2020 Aug;31(5):494-495. doi: 10.1080/09546634.2019.1623373. Epub 2019 Jun 14. PMID: 31122081; PMCID: PMC6911024.
39. Wongvibulsin S, Khanna R, Kwatra SG. Anatomic localization and quantitative analysis of the burden of itch in the United States. J Am Acad Dermatol. 2020 Jan;82(1):234-236. doi: 10.1016/j.jaad.2019.06.029. Epub 2019 Jun 20. PMID: 31228522; PMCID: PMC8720279.
40. Yang WE, Spaulding EM, Lumelsky D, Hung G, Huynh PP, Knowles K, Marvel FA, Vilarino V, Wang J, Shah LM, Xun H, Shan R, Wongvibulsin S, Martin SS. Strategies for the Successful Implementation of a Novel iPhone Loaner System (iShare) in mHealth Interventions: Prospective Study. JMIR Mhealth Uhealth. 2019 Dec 16;7(12):e16391. doi: 10.2196/16391. Erratum in: JMIR Mhealth Uhealth. 2021 Sep 20;9(9):e31472. doi: 10.2196/31472. PMID: 31841115; PMCID: PMC6937543.
41. Delva S, Waligora Mendez KJ, Cajita M, Koirala B, Shan R, Wongvibulsin S, Vilarino V, Gilmore DR, Han HR. Efficacy of Mobile Health for Self-management of Cardiometabolic Risk Factors: A Theory-Guided Systematic Review. J Cardiovasc Nurs. 2021 Jan/Feb;36(1):34-55. doi: 10.1097/JCN.0000000000000659. PMID: 32040072; PMCID: PMC7713761.
42. Wongvibulsin S, Daza EJ. Generating Actionable Insights: Machine Learning for Causal Inference with Individual-Level Patient Generated Data. MLHC: Proceedings of Machine Learning Research. 2018.
43. Wang J, Wongvibulsin S, Henry K, Fujita S. Quantifying and Visualizing Medication Adherence in Patients Following Acute Myocardial Infarction. AMIA Annu Symp Proc. 2018 Apr 16;2017:2299-2303. PMID: 29854272; PMCID: PMC5977657.
44. Wongvibulsin, Shannon & Vazirani, Sondra & Li, Zhaoping & Heber, David. (2014). Vitamin D - Beyond Bones: Its Relationship to Obesity, Metabolic Syndrome, and Diabetes. Journal of Nutritional Therapeutics. 3. 133-141. 10.6000/1929-5634.2014.03.03.4.
45. Wongvibulsin S, Lee SS, Hui KK. Achieving Balance Through the Art of Eating: Demystifying Eastern Nutrition and Blending it with Western Nutrition. J Tradit Complement Med. 2012 Jan;2(1):1-5. doi: 10.1016/s2225-4110(16)30065-7. PMID: 24716109; PMCID: PMC3943006.
Professional Societies
Women's Dermatologic Society
Skin of Color Society
Sigma Xi, The Scientific Research Honor Society
American Medical Informatics Association
International Biometric Society
American Medical Association
Tau Beta Pi, Engineering Honor Society
Alpha Lambda Delta & Phi Eta Sigma
Biomedical Engineering Society
Graduate Programs
Dermatology
Link to this profile
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https://faculty.uci.edu/profile/?facultyId=7383
Last updated
08/03/2026
08/03/2026