Shafaat, Omid
5 papers on CoChatORCID 0000-0001-8793-7901
Most cited papers
- Verified
Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019
Murray, C. J. L., Aravkin, A. Y., Zheng, P., Abbafati, C., Abbas, K. M., Abbasi-Kangevari, M., Abd-Allah, F., Abdelalim, A., Abdollahi, M., Abdollahpour, I., et al. (2020) · The Lancet
Cardiovascular Health and Risk FactorsGlobal Health and Epidemiology
Cited by 9,854
- Verified
Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990–2019: a systematic analysis from the Global Burden of Disease Study 2019
Reitsma, M. B., Kendrick, P. J., Ababneh, E., Abbafati, C., Abbasi-Kangevari, M., Abdoli, A., Abedi, A., Abhilash, E. S., Abila, D. B., Aboyans, V., et al. (2021) · The Lancet
Smoking Behavior and CessationGlobal Cancer Incidence and Screening
Cited by 1,759
- Verified
Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021
Schumacher, A. E., Kyu, H. H., Aali, A., Abbafati, C., Abbas, J., Abbasgholizadeh, R., Abbasi, M. A., Abbasian, M., Abd ElHafeez, S., Abdelmasseh, M., et al. (2024) · The Lancet
Insurance, Mortality, Demography, Risk ManagementCOVID-19 epidemiological studies
Cited by 1,045
- Verified
Global, regional, and national progress towards Sustainable Development Goal 3.2 for neonatal and child health: All-cause and cause-specific mortality findings from the Global Burden of Disease Study 2019
Paulson, K. R., Kamath, A. M., Alam, T., Bienhoff, K., Abady, G. G., Abbas, J., Abbasi-Kangevari, M., Abbastabar, H., Abd-Allah, F., Abd-Elsalam, S. M., et al. (2021) · The Lancet
Global Maternal and Child HealthMaternal and Neonatal Healthcare
Cited by 498
- Verified
Confounding factors need to be accounted for in assessing bias by machine learning algorithms
Mukherjee, P., Shen, T. C., Liu, J., Mathai, T., Shafaat, O., & Summers, R. M. (2022) · Nature Medicine
Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI
Cited by 26
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