Adams, Lisa C.

Global, regional, and national prevalence of adult overweight and obesity, 1990–2021, with forecasts to 2050: a forecasting study for the Global Burden of Disease Study 2021

Ng, M., Gakidou, E., Lo, J., Abate, Y. H., Abbafati, C., Abbas, N., Abbasian, M., Abd ElHafeez, S., Abdel-Rahman, W. M., Abd-Elsalam, S., et al. (2025) · The Lancet

Obesity, Physical Activity, DietDiabetes, Cardiovascular Risks, and Lipoproteins

Cited by 1,151

Burden of 375 diseases and injuries, risk-attributable burden of 88 risk factors, and healthy life expectancy in 204 countries and territories, including 660 subnational locations, 1990–2023: a systematic analysis for the Global Burden of Disease Study 2023

Hay, S. I., Ong, K. L., Santomauro, D. F., A, B., Aalipour, M. A., Aalruz, H., Ababneh, H. S., Abaraogu, U. O., Abate, B. B., Abbafati, C., et al. (2025) · The Lancet

Global Health and EpidemiologyCardiovascular Health and Risk Factors

Cited by 916

Global burden of 292 causes of death in 204 countries and territories and 660 subnational locations, 1990–2023: a systematic analysis for the Global Burden of Disease Study 2023

Naghavi, M., Kyu, H. H., A, B., Aalipour, M. A., Aalruz, H., Ababneh, H. S., Abafita, B. J., Abaraogu, U. O., Abbafati, C., Abbasi, M., et al. (2025) · The Lancet

Insurance, Mortality, Demography, Risk ManagementGlobal Health and Epidemiology

Cited by 595

The global, regional, and national burden of cancer, 1990–2023, with forecasts to 2050: a systematic analysis for the Global Burden of Disease Study 2023

Force, L. M., Kocarnik, J. M., May, M. L., Bhangdia, K., Crist, A., Penberthy, L., Pritchett, N., Acheson, A., Deitesfeld, L., A, B., et al. (2025) · The Lancet

Global Cancer Incidence and ScreeningColorectal Cancer Screening and Detection

Cited by 494

SenNet recommendations for detecting senescent cells in different tissues

Suryadevara, V., Hudgins, A. D., Rajesh, A., Pappalardo, A., Karpova, A., Dey, A. K., Hertzel, A., Agudelo, A., Rocha, A., Soygur, B., et al. (2024) · Nature Reviews Molecular Cell Biology

Telomeres, Telomerase, and SenescenceGenetics, Aging, and Longevity in Model Organisms

Cited by 408

Current applications and challenges in large language models for patient care: a systematic review

Busch, F., Hoffmann, L., Rueger, C., van Dijk, E. H., Kader, R., Ortiz-Prado, E., Makowski, M. R., Saba, L., Hadamitzky, M., Kather, J. N., et al. (2025) · Communications Medicine

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 358

Leveraging gpt-4 for post hoc transformation of free-text radiology reports into structured reporting: a multilingual feasibility study

Adams, L. C., Truhn, D., Busch, F., Kader, A., Niehues, S. M., Makowski, M. R., & Bressem, K. K. (2023) · Radiology

Artificial Intelligence in Healthcare and EducationBiomedical Text Mining and Ontologies

Cited by 339

Global age-sex-specific all-cause mortality and life expectancy estimates for 204 countries and territories and 660 subnational locations, 1950–2023: a demographic analysis for the Global Burden of Disease Study 2023

Schumacher, A. E., Zheng, P., Barber, R. M., A, B., Aalipour, M. A., Aalruz, H., Ababneh, H. S., Abaraogu, U. O., Abbafati, C., Abbas, N., et al. (2025) · The Lancet

Insurance, Mortality, Demography, Risk ManagementGlobal Cancer Incidence and Screening

Cited by 209

Global, regional, and national trends in routine childhood vaccination coverage from 1980 to 2023 with forecasts to 2030: a systematic analysis for the Global Burden of Disease Study 2023

Haeuser, E., Byrne, S., Nguyen, J., Raggi, C., McLaughlin, S. A., Bisignano, C., Harris, A. A., Smith, A. E., Lindstedt, P. A., Smith, G., et al. (2025) · The Lancet

Vaccine Coverage and HesitancyGlobal Maternal and Child Health

Cited by 143

Large language models for structured reporting in radiology: past, present, and future

Busch, F., Hoffmann, L., dos Santos, D. P., Makowski, M. R., Saba, L., Prucker, P., Hadamitzky, M., Navab, N., Kather, J. N., Truhn, D., et al. (2024) · European Radiology

Artificial Intelligence in Healthcare and EducationRadiology practices and education

Cited by 134

Multinational Attitudes Toward AI in Health Care and Diagnostics Among Hospital Patients

Busch, F., Hoffmann, L., Xu, L., Zhang, L. J., Hu, B., García-Juárez, I., Toapanta-Yanchapaxi, L. N., Gorelik, N., Gorelik, V., Rodriguez-Granillo, G. A., et al. (2025) · JAMA Network Open

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 124

Global cross-sectional student survey on AI in medical, dental, and veterinary education and practice at 192 faculties

Busch, F., Hoffmann, L., Truhn, D., Ortiz-Prado, E., Makowski, M. R., Bressem, K. K., Adams, L. C., COMFORT Consortium, Abdala, N., Navarro, Á. A., et al. (2024) · BMC Medical Education

Artificial Intelligence in Healthcare and EducationInnovations in Medical Education

Cited by 108

Biomedical Ethical Aspects Towards the Implementation of Artificial Intelligence in Medical Education

Busch, F., Adams, L. C., & Bressem, K. K. (2023) · Medical Science Educator

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 88

Comparative Analysis of Multimodal Large Language Model Performance on Clinical Vignette Questions

Han, T., Adams, L. C., Bressem, K. K., Busch, F., Nebelung, S., & Truhn, D. (2024) · JAMA

Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications

Cited by 83

International pharmacy students' perceptions towards artificial intelligence in medicine—A multinational, multicentre cross‐sectional study

Busch, F., Hoffmann, L., Truhn, D., Palaian, S., Alomar, M., Shpati, K., Makowski, M. R., Bressem, K. K., & Adams, L. C. (2024) · British Journal of Clinical Pharmacology

Artificial Intelligence in Healthcare and EducationInnovations in Medical Education

Cited by 80

Multimodal Large Language Models are Generalist Medical Image Interpreters

Han, T., Adams, L. C., Nebelung, S., Kather, J. N., Bressem, K. K., & Truhn, D. (2023) · medRxiv

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 18

Reporting checklist for foundation and large language models in medical research (REFINE): an international consensus guideline

Mese, I., D’Antonoli, T. A., Bluethgen, C., Bressem, K., Cuocolo, R., Chaudhari, A., Tejani, A. S., Isaac, A., Ponsiglione, A., Meddeb, A., et al. (2026) · Diagnostic and Interventional Radiology

Artificial Intelligence in Healthcare and EducationMeta-analysis and systematic reviews

Cited by 17

Agentic systems in radiology: Principles, opportunities, privacy risks, regulation, and sustainability concerns.

Tzanis, E., Adams, L. C., Akinci D’Antonoli, T., Bressem, K. K., Cuocolo, R., Kocak, B., Malamateniou, C., & Klontzas, M. E. (2026) · Diagnostic and Interventional Imaging

Artificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical Imaging

Cited by 16

Evaluation of a retrieval-augmented generation-powered chatbot for pre-CT informed consent: a prospective comparative study

Busch, F., Kaibel, L., Nguyen, H., Lemke, T., Ziegelmayer, S., Graf, M., Marka, A. W., Endrös, L., Prucker, P., Spitzl, D., et al. (2025) · Journal of Imaging Informatics in Medicine

Artificial Intelligence in Healthcare and EducationPatient-Provider Communication in Healthcare

Cited by 10

LongHealth: A Question Answering Benchmark with Long Clinical Documents

Adams, L., Busch, F., Han, T., Excoffier, J.-B., Ortala, M., Löser, A., Aerts, H. J., Kather, J. N., Truhn, D., & Bressem, K. (2024) · arXiv

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 10

Improving Reliability and Explainability of Medical Question Answering through Atomic Fact Checking in Retrieval-Augmented LLMs

Vladika, J., Domres, A., Nguyen, M., Moser, R., Nano, J., Busch, F., Adams, L. C., Bressem, K. K., Bernhardt, D., Combs, S. E., et al. (2025) · arXiv

Artificial Intelligence in Healthcare and EducationTopic Modeling

Cited by 1