Marcinkiewicz, A. M., Zhang, W., Shanbhag, A., Miller, R. J. H., Lemley, M., Ramirez, G., Buchwald, M., Killekar, A., Kavanagh, P. B., Feher, A., Miller, E. J., Einstein, A. J., Ruddy, T. D., Liang, J. X., Builoff, V., Ouyang, D., Berman, D. S., Dey, D., & Slomka, P. J. (2025). Holistic AI analysis of hybrid cardiac perfusion images for mortality prediction. Npj Digital Medicine, 8(1). https://doi.org/10.1038/s41746-025-01526-0

Balendran, A., Beji, C., Bouvier, F., Khalifa, O., Evgeniou, T., Ravaud, P., & Porcher, R. (2025). A scoping review of robustness concepts for machine learning in healthcare. Npj Digital Medicine, 8(1). https://doi.org/10.1038/s41746-024-01420-1

Schuemie, M. J., Ostropolets, A., Zhuk, A., Korsik, U., Seo, S. I., Suchard, M. A., Hripcsak, G., & Ryan, P. B. (2025). Standardized patient profile review using large language models for case adjudication in observational research. Npj Digital Medicine, 8(1). https://doi.org/10.1038/s41746-025-01433-4

Chen, F., Ahimaz, P., Nguyen, Q. M., Lewis, R., Chung, W. K., Ta, C. N., Szigety, K. M., Sheppard, S. E., Campbell, I. M., Wang, K., Weng, C., & Liu, C. (2024). Phenotype driven molecular genetic test recommendation for diagnosing pediatric rare disorders. Npj Digital Medicine, 7(1). https://doi.org/10.1038/s41746-024-01331-1

Wang, H., Argenziano, M. G., Yoon, H., Boyett, D., Save, A., Petridis, P., Savage, W., Jackson, P., Hawkins-Daarud, A., Tran, N., Hu, L., Singleton, K. W., Paulson, L., Dalahmah, O. A., Bruce, J. N., Grinband, J., Swanson, K. R., Canoll, P., & Li, J. (2024). Biologically informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post treatment glioblastoma. Npj Digital Medicine, 7(1). https://doi.org/10.1038/s41746-024-01277-4

Balendran, A., Benchoufi, M., Evgeniou, T., & Ravaud, P. (2024). Algorithmovigilance, lessons from pharmacovigilance. Npj Digital Medicine, 7(1). https://doi.org/10.1038/s41746-024-01237-y

Zhang, G., Jin, Q., Zhou, Y., Wang, S., Idnay, B., Luo, Y., Park, E., Nestor, J. G., Spotnitz, M. E., Soroush, A., Campion, T. R., Lu, Z., Weng, C., & Peng, Y. (2024). Closing the gap between open source and commercial large language models for medical evidence summarization. Npj Digital Medicine, 7(1). https://doi.org/10.1038/s41746-024-01239-w

Holste, G., Lin, M., Zhou, R., Wang, F., Liu, L., Yan, Q., Van Tassel, S. H., Kovacs, K., Chew, E. Y., Lu, Z., Wang, Z., & Peng, Y. (2024). Harnessing the power of longitudinal medical imaging for eye disease prognosis using Transformer-based sequence modeling. Npj Digital Medicine, 7(1). https://doi.org/10.1038/s41746-024-01207-4

Liu, S., Haucke, M., Wegner, L., Gates, J., Bärnighausen, T., & Adam, M. (2024). Evidence-based health messages increase intention to cope with loneliness in Germany: a randomized controlled online trial. Npj Digital Medicine, 7(1). https://doi.org/10.1038/s41746-024-01096-7

Miller, R. J. H., Shanbhag, A., Killekar, A., Lemley, M., Bednarski, B., Van Kriekinge, S. D., Kavanagh, P. B., Feher, A., Miller, E. J., Einstein, A. J., Ruddy, T. D., Liang, J. X., Builoff, V., Berman, D. S., Dey, D., & Slomka, P. J. (2024). AI-derived epicardial fat measurements improve cardiovascular risk prediction from myocardial perfusion imaging. Npj Digital Medicine, 7(1). https://doi.org/10.1038/s41746-024-01020-z

Hughes, J. W., Tooley, J., Torres Soto, J., Ostropolets, A., Poterucha, T., Christensen, M. K., Yuan, N., Ehlert, B., Kaur, D., Kang, G., Rogers, A., Narayan, S., Elias, P., Ouyang, D., Ashley, E., Zou, J., & Perez, M. V. (2023). A deep learning-based electrocardiogram risk score for long term cardiovascular death and disease. Npj Digital Medicine, 6(1). https://doi.org/10.1038/s41746-023-00916-6

Rekkas, A., van Klaveren, D., Ryan, P. B., Steyerberg, E. W., Kent, D. M., & Rijnbeek, P. R. (2023). A standardized framework for risk-based assessment of treatment effect heterogeneity in observational healthcare databases. Npj Digital Medicine, 6(1). https://doi.org/10.1038/s41746-023-00794-y

Ali, F. Z., Parsey, R. V., Lin, S., Schwartz, J., & DeLorenzo, C. (2023). Circadian rhythm biomarker from wearable device data is related to concurrent antidepressant treatment response. Npj Digital Medicine, 6(1). https://doi.org/10.1038/s41746-023-00827-6

Flynn, B. I., Javan, E. M., Lin, E., Trutner, Z., Koenig, K., Anighoro, K. O., Kun, E., Gupta, A., Singh, T., Jayakumar, P., & Narasimhan, V. M. (2023). Deep learning based phenotyping of medical images improves power for gene discovery of complex disease. Npj Digital Medicine, 6(1). https://doi.org/10.1038/s41746-023-00903-x

Callahan, T. J., Stefanski, A. L., Wyrwa, J. M., Zeng, C., Ostropolets, A., Banda, J. M., Baumgartner, W. A., Boyce, R. D., Casiraghi, E., Coleman, B. D., Collins, J. H., Deakyne Davies, S. J., Feinstein, J. A., Lin, A. Y., Martin, B., Matentzoglu, N. A., Meeker, D., Reese, J., Sinclair, J., … Kahn, M. G. (2023). Ontologizing health systems data at scale: making translational discovery a reality. Npj Digital Medicine, 6(1). https://doi.org/10.1038/s41746-023-00830-x

Pieszko, K., Shanbhag, A. D., Singh, A., Hauser, M. T., Miller, R. J. H., Liang, J. X., Motwani, M., Kwieciński, J., Sharir, T., Einstein, A. J., Fish, M. B., Ruddy, T. D., Kaufmann, P. A., Sinusas, A. J., Miller, E. J., Bateman, T. M., Dorbala, S., Di Carli, M., Berman, D. S., … Slomka, P. J. (2023). Time and event-specific deep learning for personalized risk assessment after cardiac perfusion imaging. Npj Digital Medicine, 6(1). https://doi.org/10.1038/s41746-023-00806-x

Tang, L., Sun, Z., Idnay, B., Nestor, J. G., Soroush, A., Elias, P. A., Xu, Z., Ding, Y., Durrett, G., Rousseau, J. F., Weng, C., & Peng, Y. (2023). Evaluating large language models on medical evidence summarization. Npj Digital Medicine, 6(1). https://doi.org/10.1038/s41746-023-00896-7

Shang, N., Khan, A., Polubriaginof, F., Zanoni, F., Mehl, K., Fasel, D., Drawz, P. E., Carrol, R. J., Denny, J. C., Hathcock, M. A., Arruda-Olson, A. M., Peissig, P. L., Dart, R. A., Brilliant, M. H., Larson, E. B., Carrell, D. S., Pendergrass, S., Verma, S. S., Ritchie, M. D., … Kiryluk, K. (2021). Medical records-based chronic kidney disease phenotype for clinical care and “big data” observational and genetic studies. Npj Digital Medicine, 4(1). https://doi.org/10.1038/s41746-021-00428-1

Xu, D., Wang, C., Khan, A., Shang, N., He, Z., Gordon, A., Kullo, I. J., Murphy, S., Ni, Y., Wei, W.-Q., Gharavi, A., Kiryluk, K., Weng, C., & Ionita-Laza, I. (2021). Quantitative disease risk scores from EHR with applications to clinical risk stratification and genetic studies. Npj Digital Medicine, 4(1). https://doi.org/10.1038/s41746-021-00488-3