Virani SS, Alonso A, Aparicio HJ, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Cheng S, Delling FN, et al. Heart Disease and Stroke Statistics-2021 update: a report from the American Heart Association. Circulation. 2021;143:e254–743. https://doi.org/10.1161/CIR.0000000000000950.

Article  PubMed  Google Scholar 

Mensah GA, Roth GA, Fuster V. The global burden of cardiovascular diseases and risk factors: 2020 and beyond. J Am Coll Cardiol. 2019;74:2529–32. https://doi.org/10.1016/j.jacc.2019.10.009.

Article  PubMed  Google Scholar 

Zhu S, Gilbert M, Chetty I, Siddiqui F. The 2021 landscape of FDA-approved artificial intelligence/machine learning-enabled medical devices: an analysis of the characteristics and intended use. Int J Med Inform. 2022;165:104828. https://doi.org/10.1016/j.ijmedinf.2022.104828.

Article  PubMed  Google Scholar 

Hanneman K, Playford D, Dey D, van Assen M, Mastrodicasa D, Cook TS, et al. Value creation through artificial intelligence and cardiovascular imaging: a scientific statement from the American Heart Association. Circulation. 2024;149:e296–e311. https://doi.org/10.1161/CIR.0000000000001202.

Tat E, Bhatt DL, Rabbat MG. Addressing bias: artificial intelligence in cardiovascular medicine. Lancet Digit Health. 2020;2:e635–6. https://doi.org/10.1016/S2589-7500(20)30249-1.

Article  PubMed  Google Scholar 

Zhang K, Khosravi B, Vahdati S, Faghani S, Nugen F, Rassoulinejad-Mousavi SM, Moassefi M, Jagtap JMM, Singh Y, Rouzrokh P, et al. Mitigating bias in radiology machine learning: 2. model development. Radiol Artif Intell. 2022;4:e220010. https://doi.org/10.1148/ryai.220010.

Article  PubMed  PubMed Central  Google Scholar 

Rouzrokh P, Khosravi B, Faghani S, Moassefi M, Vera Garcia DV, Singh Y, Zhang K, Conte GM, Erickson BJ. Mitigating bias in radiology machine learning: 1. data handling. Radiol Artif Intell. 2022;4:e210290. https://doi.org/10.1148/ryai.210290.

Article  PubMed  PubMed Central  Google Scholar 

Faghani S, Khosravi B, Zhang K, Moassefi M, Jagtap JM, Nugen F, Vahdati S, Kuanar SP, Rassoulinejad-Mousavi SM, Singh Y, et al. Mitigating bias in radiology machine learning: 3. performance metrics. Radiol Artif Intell. 2022;4:e220061. https://doi.org/10.1148/ryai.220061.

Article  PubMed  PubMed Central  Google Scholar 

Chong LR, Tsai KT, Lee LL, Foo SG, Chang PC. Artificial intelligence predictive analytics in the management of outpatient MRI appointment no-shows. AJR Am J Roentgenol. 2020;215:1155–62. https://doi.org/10.2214/AJR.19.22594.

Article  PubMed  Google Scholar 

Winkel DJ, Suryanarayana VR, Ali AM, Gorich J, Buss SJ, Mendoza A, Schwemmer C, Sharma P, Schoepf UJ, Rapaka S. Deep learning for vessel-specific coronary artery calcium scoring: validation on a multi-centre dataset. Eur Heart J Cardiovasc Imaging. 2022;23:846–54. https://doi.org/10.1093/ehjci/jeab119.

Article  PubMed  Google Scholar 

Tzolos E, Williams MC, McElhinney P, Lin A, Grodecki K, Flores Tomasino G, Cadet S, Kwiecinski J, Doris M, Adamson PD, et al. Pericoronary adipose tissue attenuation, low-attenuation plaque burden, and 5-year risk of myocardial infarction. JACC Cardiovasc Imaging. 2022. https://doi.org/10.1016/j.jcmg.2022.02.004.

Article  PubMed  PubMed Central  Google Scholar 

Griffin WF, Choi AD, Riess JS, Marques H, Chang HJ, Choi JH, Doh JH, Her AY, Koo BK, Nam CW, et al. AI evaluation of stenosis on coronary CT angiography, comparison with quantitative coronary angiography and fractional flow reserve: a CREDENCE trial substudy. JACC Cardiovasc Imaging. 2022. https://doi.org/10.1016/j.jcmg.2021.10.020.

Article  PubMed  Google Scholar 

Bhuva AN, Bai W, Lau C, Davies RH, Ye Y, Bulluck H, McAlindon E, Culotta V, Swoboda PP, Captur G, et al. A multicenter, scan-rescan, human and machine learning CMR study to test generalizability and precision in imaging biomarker analysis. Circ Cardiovasc Imaging. 2019;12:e009214. https://doi.org/10.1161/CIRCIMAGING.119.009214.

Article  PubMed  Google Scholar 

Motwani M, Dey D, Berman DS, Germano G, Achenbach S, Al-Mallah MH, Andreini D, Budoff MJ, Cademartiri F, Callister TQ, et al. Machine learning for prediction of all-cause mortality in patients with suspected coronary artery disease: a 5-year multicentre prospective registry analysis. Eur Heart J. 2017;38:500–7. https://doi.org/10.1093/eurheartj/ehw188.

Article  PubMed  Google Scholar 

van Rosendael AR, Maliakal G, Kolli KK, Beecy A, Al’Aref SJ, Dwivedi A, Singh G, Panday M, Kumar A, Ma X, et al. Maximization of the usage of coronary CTA derived plaque information using a machine learning based algorithm to improve risk stratification; insights from the CONFIRM registry. J Cardiovasc Comput Tomogr. 2018;12:204–9. https://doi.org/10.1016/j.jcct.2018.04.011.

Article  PubMed  Google Scholar 

Churchwell K, Elkind MSV, Benjamin RM, Carson AP, Chang EK, Lawrence W, Mills A, Odom TM, Rodriguez CJ, Rodriguez F, et al. Call to action: structural racism as a fundamental driver of health disparities: a presidential advisory from the American Heart Association. Circulation. 2020;142:E454–68. https://doi.org/10.1161/Cir.0000000000000936.

Article  PubMed  Google Scholar 

Javed Z, Haisum Maqsood M, Yahya T, Amin Z, Acquah I, Valero-Elizondo J, Andrieni J, Dubey P, Jackson RK, Daffin MA, et al. Race, racism, and cardiovascular health: applying a social determinants of health framework to racial/ethnic disparities in cardiovascular disease. Circ Cardiovasc Qual Outcomes. 2022;15: e007917. https://doi.org/10.1161/CIRCOUTCOMES.121.007917.

Article  PubMed  Google Scholar 

Kyalwazi AN, Loccoh EC, Brewer LC, Ofili EO, Xu JM, Song Y, Maddoxe KEJ, Yeh RW, Wadhera RK. Disparities in cardiovascular mortality between Black and White adults in the United States, 1999 to 2019. Circulation. 2022;146:211–28. https://doi.org/10.1161/Circulationaha.122.060199.

Article  PubMed  PubMed Central  Google Scholar 

Centers for Disease Control and Prevention. CDC health disparities and inequalities report — United States, 2013. MMWR. 2013;62(Suppl 3):157–60.

Glynn P, Lloyd-Jones DM, Feinstein MJ, Carnethon M, Khan SS. Disparities in cardiovascular mortality related to heart failure in the United States. J Am Coll Cardiol. 2019;73(18):2354–5. https://doi.org/10.1016/j.jacc.2019.02.042.

Mazimba S, Peterson PN. JAHA spotlight on racial and ethnic disparities in cardiovascular disease. J Am Heart Assoc. 2021;10(17):e023650. https://doi.org/10.1161/JAHA.121.023650.

Hannan EL, Racz MJ, Walford G, Jacobs AK, Stamato NJ, Gesten F, Berger PB, Sharma S, King SB. Disparities in the use of drug-eluting coronary stents by race, ethnicity, payer, and hospital. Can J Cardiol. 2016;32: 987.e25 https://doi.org/10.1016/j.cjca.2016.01.012

Fang J, Yang QH, Ayala C, Loustalot F. Disparities in access to care among US adults with self-reported hypertension. Am J Hypertens. 2014;27:1377–86. https://doi.org/10.1093/ajh/hpu061.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Sullivan S, Hammadah M, Wilmot K, Ramadan R, Pearce BD, Shah A, Kaseer B, Gafeer MM, Lima BB, Kim JH, et al. Young women with coronary artery disease exhibit higher concentrations of interleukin-6 at baseline and in response to mental stress. J Am Heart Assoc. 2018;7:e010329. https://doi.org/10.1161/JAHA.118.010329.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kershaw KN, Lewis TT, Diez Roux AV, Jenny NS, Liu K, Penedo FJ, et al. Self-reported experiences of discrimination and inflammation among men and women: the multi-ethnic study of atherosclerosis. Health Psychol. 2016;35(4):343–50. https://doi.org/10.1037/hea0000331.

Liaudat CC, Vaucher P, De Francesco T, Jaunin-Stalder N, Herzig L, Verdon F, Favrat B, Locatelli I, Clair C. Sex/gender bias in the management of chest pain in ambulatory care. Womens Health. 2018;14:1745506518805641 https://doi.org/10.1177/1745506518805641 (Artn)

Shahian DM, Jacobs JP, Badhwar V, Kurlansky PA, Furnary AP, Cleveland JC, Lobdell KW, Vassileva C, von Ballmoos MCW, Thourani VH, et al. The Society of Thoracic Surgeons 2018 adult cardiac surgery risk models: part 1-background, design considerations, and model development. Ann Thorac Surg. 2018;105:1411–8. https://doi.org/10.1016/j.athoracsur.2018.03.002.

Article  PubMed  Google Scholar 

Sambola A, Del Blanco BG, Kunadian V, Vogel B, Chieffo A, Vidal M, Ratcovich H, Botti G, Wilkinson C, Mehran R. Sex-based differences in percutaneous coronary intervention outcomes in patients with ischaemic heart disease. Eur Cardiol. 2023;18:e06. https://doi.org/10.15420/ecr.2022.24.

Article  PubMed  PubMed Central  Google Scholar 

Daugherty SL, Magid DJ. Do sex differences exist in patient preferences for cardiovascular testing? Ann Emerg Med. 2011;57:561–2. https://doi.org/10.1016/j.annemergmed.2011.01.010.

Article  PubMed  PubMed Central  Google Scholar 

Lee P, Le Saux M, Siegel R, Goyal M, Chen C, Ma Y, Meltzer AC. Racial and ethnic disparities in the management of acute pain in US emergency departments: meta-analysis and systematic review. Am J Emerg Med. 2019;37:1770–7. https://doi.org/10.1016/j.ajem.2019.06.014.

Article  PubMed  Google Scholar 

Hsia RY, Sarkar N, Shen YC. Impact of ambulance diversion: Black patients with acute myocardial infarction had higher mortality than Whites. Health Aff (Millwood). 2017;36:1070–7. https://doi.org/10.1377/hlthaff.2016.0925.

Article  PubMed  Google Scholar 

Graham G. Racial and ethnic differences in acute coronary syndrome and myocardial infarction within the United States: from demographics to outcomes. Clin Cardiol. 2016;39:299–306. https://doi.org/10.1002/clc.22524.

Article  PubMed  PubMed Central  Google Scholar 

National Healthcare Quality and Disparities Report. Content last reviewed July 2023. Rockville: Agency for Healthcare Research and Quality; 2019. https://www.ahrq.gov/research/findings/nhqrdr/nhqdr19/index.html.

Popescu I, Huckfeldt P, Pane JD, Escarce JJ. Contributions of geography and nongeographic factors to the White-Black gap in hospital quality for coronary heart disease: a decomposition analysis. J Am Heart Assoc. 2019;8: e011964 https://doi.org/10.1161/JAHA.119.011964 (ARTN)

Johnson A. Understanding why Black patients have worse coronary heart disease outcomes: does the answer lie in knowing where patients seek care? J Am Heart Assoc. 2019;8:e014706. https://doi.org/10.1161/jaha.119.014706.

Article  PubMed  PubMed Central  Google Scholar 

Norris CM, Yip CYY, Nerenberg KA, Clavel MA, Pacheco C, Foulds HJA, Hardy M, Gonsalves CA, Jaffer S, Parry M, et al. State of the science in women’s cardiovascular disease: a Canadian perspective on the influence of sex and gender. J Am Heart Assoc. 2020;9:e015634. https://doi.org/10.1161/JAHA.119.015634.

Article  PubMed  PubMed Central  Google Scholar 

Geller SE, Koch AR, Roesch P, Filut A, Hallgren E, Carnes M. The more things change, the more they stay the same: a study to evaluate compliance with inclusion and assessment of women and minorities in randomized controlled trials. Acad Med. 2018;93:630–5. https://doi.org/10.1097/Acm.0000000000002027.

Article  PubMed  PubMed Central  Google Scholar 

Jin X, Chandramouli C, Allocco B, Gong E, Lam CSP, Yan LL. Women’s participation in cardiovascular clinical trials from 2010 to 2017. Circulation. 2020;141(7):540–8. https://doi.org/10.1161/Circulationaha.119.043594.

Lolic M, Araojo R, Okeke M, Temple RUS. racial and ethnic participation in global clinical trials by therapeutic areas. J Clin Pharm Ther. 2021;46:1576–81. https://doi.org/10.1111/jcpt.13532.

Article  PubMed  PubMed Central