All of Us Publications

De-black-boxing health AI: demonstrating reproducible machine learning computable phenotypes using the N3C-RECOVER Long COVID model in the All of Us data repository

De-black-boxing health AI: demonstrating reproducible machine learning computable phenotypes using the N3C-RECOVER Long COVID model in the All of Us data repository

Pfaff ER, Girvin AT, Crosskey M, Gangireddy S, Master H, Wei WQ, Kerchberger VE, Weiner M, Harris PA, Basford M, Lunt C, Chute CG, Moffitt RA, Haendel M; N3C and RECOVER Consortia.  J Am Med Inform Assoc. 2023 May 22:ocad077. doi: 10.1093/jamia/ocad077. Epub ahead of print. PMID: 37218289.

Importance of missingness in baseline variables: A case study of the All of Us  Research Program

Importance of missingness in baseline variables: A case study of the All of Us Research Program

Cronin RM, Feng X, Sulieman L, Mapes B, Garbett S, Able A, Hale R, Couper MP, Sansbury H, Ahmedani BK, Chen Q.  PLoS One. 2023 May 18;18(5):e0285848. doi: 10.1371/journal.pone.0285848. PMID: 37200348.

Disparities in health-related quality of life among lesbian, gay, and bisexual cancer survivors

Disparities in health-related quality of life among lesbian, gay, and bisexual cancer survivors

Hoyt MA, Darabos K, Llave K. J Psychosoc Oncol. 2023 May 15:1-12. doi: 10.1080/07347332.2023.2210548. Epub ahead of print. PMID: 37183953.

Protocol for developing a personalised prediction model for viral suppression among under-represented populations in the context of the COVID-19 pandemic

Protocol for developing a personalised prediction model for viral suppression among under-represented populations in the context of the COVID-19 pandemic

Zhang J, Yang X, Weissman S, Li X, Olatosi B. BMJ Open. 2023 May 15;13(5):e070869. doi: 10.1136/bmjopen-2022-070869. PMID: 37188476; PMCID: PMC10186088.

Socioeconomic and Racial/Ethnic Disparities in Perception of Health Status and Literacy in Spine Oncological Patients: Insights from the All of Us Research Program

Socioeconomic and Racial/Ethnic Disparities in Perception of Health Status and Literacy in Spine Oncological Patients: Insights from the All of Us Research Program

Elsamadicy AA, Wang C, Reeves BC, Sherman JJZ, Craft S, Rajjoub R, Koo A, Hersh AM, Pennington Z, Lo SL, Shin JH, Mendel E, Sciubba DM. Spine (Phila Pa 1976). 2023 May 8. doi: 10.1097/BRS.0000000000004712. Epub ahead of print. PMID: 37163649.

The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes

The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes

Huerta-Chagoya, A., Schroeder, P., Mandla, R. et al. Diabetologia 2023 Jul;66(7):1273-1288. doi: 10.1007/s00125-023-05912-9. Epub 2023 May 6. PMID: 37148359

The association of cutaneous squamous cell carcinoma and basal cell carcinoma with solid organ transplantation: a cross-sectional study of the All Of Us Research Program

The association of cutaneous squamous cell carcinoma and basal cell carcinoma with solid organ transplantation: a cross-sectional study of the All Of Us Research Program

Belzer A, Leasure AC, Cohen JM, Perkins SH. Int J Dermatol. 2023 Oct;62(10):e564-e566. doi: 10.1111/ijd.16700. Epub 2023 May 5. PMID: 37144784.

Investigating the association between gender minority identity and skin cancer prevalence: A cohort study in the United States All of Us research program

Investigating the association between gender minority identity and skin cancer prevalence: A cohort study in the United States All of Us research program

Kamal K, Young K, Ly S, Manjaly P, Xiang DH, Zhou G, Mostaghimi A, Theodosakis N. J Eur Acad Dermatol Venereol. 2023 Apr 28. doi: 10.1111/jdv.19156. Epub ahead of print. PMID: 37114382.

Epidemiology and factors associated with cannabis use among patients with glaucoma in the All of Us  Research Program

Epidemiology and factors associated with cannabis use among patients with glaucoma in the All of Us Research Program

Wu JH, Radha Saseendrakumar B, Moghimi S, Sidhu S, Kamalipour A, Weinreb RN, Baxter SL.  Heliyon. 2023 Apr 25;9(5):e15811. doi: 10.1016/j.heliyon.2023.e15811. PMID: 37215923; PMCID: PMC10192773.

A machine learning model identifies patients in need of autoimmune disease testing using electronic health records

A machine learning model identifies patients in need of autoimmune disease testing using electronic health records

Forrest IS, Petrazzini BO, Duffy Á, Park JK, O’Neal AJ, Jordan DM, Rocheleau G, Nadkarni GN, Cho JH, Blazer AD, Do R. Nat Commun. 2023 Apr 25;14(1):2385. doi: 10.1038/s41467-023-37996-7. PMID: 37169741; PMCID: PMC10130143.