Department of Biomedical Informatics

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Long, A., Finer, J., Hartman, H., Hartzel, D., Jing, L., Kelsey, C., Rocha, D., Ruhl, J., vanMaanen, D., Elnabawi, Y., Metser, G., Duffy, E., Mawson, T., Tat, E., Haggerty, C. M., Maurer, M., Einstein, A. J., Beecy, A. N., Kumaraiah, D., … Poterucha, T. J. (2025). Deep learning for echocardiographic assessment and risk stratification of aortic, mitral, and tricuspid regurgitation: the DELINEATE-Regurgitation study. European Heart Journal. https://doi.org/10.1093/eurheartj/ehaf248
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Mosialou, I., Ali, A. M., Labella, R., Bisikirska, B., Cuesta-Dominguez, A., Vgenopoulou, P., Reyes, I., Rao, S. M., Wang, A., Luo, N., Galan-Diez, M., Zhao, J., Chernak, B. J., Bewersdorf, J. P., Fukasawa, K., Su, J., Higa, J., Adams, R. A., Corper, A. L., … Kousteni, S. (2025). A niche driven mechanism determines response and a mutation-independent therapeutic approach for myeloid malignancies. Cancer Cell. https://doi.org/10.1016/j.ccell.2025.03.007
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Austin, G. I., Brown Kav, A., ElNaggar, S., Park, H., Biermann, J., Uhlemann, A.-C., Pe’er, I., & Korem, T. (2025). Processing-bias correction with DEBIAS-M improves cross-study generalization of microbiome-based prediction models. Nature Microbiology. https://doi.org/10.1038/s41564-025-01954-4
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Baumeister, T., Proaño-Vasco, A., Metwaly, A., Kleigrewe, K., Kuznetsov, A., Schömig, L., Borgmann, M., Khiat, M., Anand, A., Strangmann, J., Böttcher, K., Haller, D., Dunkel, A., Somoza, V., Reiter, S., Meng, C., Thimme, R., Schmid, R. M., Patil, D. T., … Quante, M. (2025). Loss of FXR or Bile Acid-dependent Inhibition accelerate carcinogenesis of Gastroesophageal Adenocarcinoma. Cellular and Molecular Gastroenterology and Hepatology, 101505. https://doi.org/10.1016/j.jcmgh.2025.101505
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Kwon, S. B., Weinerman, B., Nametz, D., Alalqum, T., Lee, I. S., Megjhani, M., McLaren, S. H., Ranard, B., Ku, Y., Geneslaw, A., & Park, S. (2025). Pulse rate variability as a predictor for length of stay for patients with bronchiolitis in the pediatric intensive care unit. Journal of Clinical Monitoring and Computing. https://doi.org/10.1007/s10877-025-01287-x
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Sierant, M. C., Jin, S. C., Bilguvar, K., Morton, S. U., Dong, W., Jiang, W., Lu, Z., Li, B., López-Giráldez, F., Tikhonova, I., Zeng, X., Lu, Q., Choi, J., Zhang, J., Nelson-Williams, C., Knight, J. R., Zhao, H., Cao, J., Mane, S., … Lifton, R. P. (2025). Genomic analysis of 11,555 probands identifies 60 dominant congenital heart disease genes. Proceedings of the National Academy of Sciences, 122(13). https://doi.org/10.1073/pnas.2420343122
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Lee, R., Thate, J. A., Withall, J., Yen, P.-Y., Cato, K., & Rossetti, S. C. (2025). Relationship between additional required nursing documentation and patient outcomes: A Scoping Review. Applied Clinical Informatics. CLOCKSS. https://doi.org/10.1055/a-2561-3960
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Matentzoglu, N., Bello, S. M., Stefancsik, R., Alghamdi, S. M., Anagnostopoulos, A. V., Balhoff, J. P., Balk, M. A., Bradford, Y. M., Bridges, Y., Callahan, T. J., Caufield, H., Cuzick, A., Carmody, L. C., Caron, A. R., de Souza, V., Engel, S. R., Fey, P., Fisher, M., Gehrke, S., … Osumi-Sutherland, D. (2025). The Unified Phenotype Ontology : a framework for cross-species integrative phenomics. GENETICS, 229(3). https://doi.org/10.1093/genetics/iyaf027
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Carroll, E. E., Shen, Q., Kansara, V., Casson, N., Michalak, A., Niesvizky-Kogan, I., Lim, J., Postelnik, A., Viereck, M. J., Egawa, S., Kahan, J., Carmona, J. C., Kruger, L., Song, Y. L., Velazquez, A., Schevon, C. A., Connolly, E. S., Ghoshal, S., Agarwal, S., … Claassen, J. (2025). Sleep spindles as a predictor of cognitive motor dissociation and recovery of consciousness after acute brain injury. Nature Medicine. https://doi.org/10.1038/s41591-025-03578-x
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Joshi, S., Urteaga, I., van Amsterdam, W. A. C., Hripcsak, G., Elias, P., Recht, B., Elhadad, N., Fackler, J., Sendak, M. P., Wiens, J., Deshpande, K., Wald, Y., Fiterau, M., Lipton, Z., Malinsky, D., Nayan, M., Namkoong, H., Park, S., Vogt, J. E., & Ranganath, R. (2025). AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation. Journal of the American Medical Informatics Association, 32(3), 589–594. https://doi.org/10.1093/jamia/ocae301
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Lee, R. Y., Landau, A. Y., Heider, P. M., Hanson, R. F., Espeleta, H. C., Cato, K. D., & Topaz, M. (2025). Estimating the Prevalence of Child Abuse and Neglect Among Adolescents in Primary Care Through Diagnoses Codes and Free-Text EHR Clinical Notes. Journal of Pediatric Health Care, 39(2), 189–197. https://doi.org/10.1016/j.pedhc.2024.10.016
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Papadopoulou, A., Litkowski, E. M., Graff, M., Wang, Z., Smit, R. A. J., Chittoor, G., Dinsmore, I., Josyula, N. S., Lin, M., Shortt, J., Zhu, W., Vedantam, S. L., Yengo, L., Wood, A. R., Berndt, S. I., Holm, I. A., Mentch, F. D., Hakonarson, H., Kiryluk, K., … Marouli, E. (2025). Insights from the largest diverse ancestry sex-specific disease map for genetically predicted height. Npj Genomic Medicine, 10(1). https://doi.org/10.1038/s41525-025-00464-w
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Link-Gelles, R., Chickery, S., Webber, A., Ong, T. C., Rowley, E. A. K., DeSilva, M. B., Dascomb, K., Irving, S. A., Klein, N. P., Grannis, S. J., Barron, M. A., Reese, S. E., McEvoy, C., Sheffield, T., Naleway, A. L., Zerbo, O., Rogerson, C., Self, W. H., Zhu, Y., … Zepeski, A. (2025). Interim Estimates of 2024–2025 COVID-19 Vaccine Effectiveness Among Adults Aged ≥18 Years — VISION and IVY Networks, September 2024–January 2025. MMWR. Morbidity and Mortality Weekly Report, 74(6), 73–82. https://doi.org/10.15585/mmwr.mm7406a1
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Carruth, E. D., Murray, B., Tichnell, C., Young, K., Calkins, H., James, C. A., & Haggerty, C. M. (2025). Predicted Risk of Ventricular Arrhythmias in a Genome-First Population With Genetic Risk for Arrhythmogenic Right Ventricular Cardiomyopathy. Circulation: Arrhythmia and Electrophysiology. https://doi.org/10.1161/circep.124.013231
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Kars, M. E., Stein, D., Stenson, P. D., Cooper, D. N., Chung, W. K., Gruber, P. J., Seidman, C. E., Shen, Y., Tristani-Firouzi, M., Gelb, B. D., & Itan, Y. (2025). Deciphering the digenic architecture of congenital heart disease using trio exome sequencing data. The American Journal of Human Genetics. https://doi.org/10.1016/j.ajhg.2025.01.024
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Armaignac, D. L., Heavner, S. F., Rausen, M., Zhang, X. T., Al-Hakim, T., Strekalova, Y. L., Shah, N., Remy, K. E., Manion, S., Haendel, M., Kramer, A. A., Scruth, E. A., Rincon, T. A., Park, S., Evans, L. E., Ozrazgat-Baslanti, T., Herasevich, V., Laudanski, K., Murphy, D. J., … Clermont, G. (2025). Guiding Principles for Data Sharing and Harmonization: Results of a Systematic Review and Modified Delphi From the Society of Critical Care Medicine Data Science Campaign. Critical Care Medicine. https://doi.org/10.1097/ccm.0000000000006578
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Cai, C. X., Hribar, M., Baxter, S., Goetz, K., Swaminathan, S. S., Flowers, A., Brown, E. N., Toy, B., Xu, B., Chen, J., Chen, A., Wang, S., Lee, C., Leng, T., Ehrlich, J. R., Barkmeier, A., Armbrust, K. R., Boland, M. V., Dorr, D., … Ryan, P. B. (2025). Semaglutide and Nonarteritic Anterior Ischemic Optic Neuropathy. JAMA Ophthalmology. https://doi.org/10.1001/jamaophthalmol.2024.6555
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Liu, H., Abedini, A., Ha, E., Ma, Z., Sheng, X., Dumoulin, B., Qiu, C., Aranyi, T., Li, S., Dittrich, N., Chen, H.-C., Tao, R., Tarng, D.-C., Hsieh, F.-J., Chen, S.-A., Yang, S.-F., Lee, M.-Y., Kwok, P.-Y., Wu, J.-Y., … Drivas, T. G. (2025). Kidney multiome-based genetic scorecard reveals convergent coding and regulatory variants. Science, 387(6734). https://doi.org/10.1126/science.adp4753
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Leventhal, E., Nukavarapu, N., Elhadad, N., Bakken, S., Elovitz, M., Hirten, R., Rodrigues, J., Danieletto, M., Landell, K., & Ensari, I. (2025). Trajectories of mHealth-Tracked Mental Health and Their Predictors in Female Chronic Pelvic Pain Disorders. Journal of Pain Research, Volume 18, 899–913. https://doi.org/10.2147/jpr.s499102
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Campbell, E. A., Holl, F., Marwah, H. K., Fraser, H. S., & Craig, S. S. (2025). The impact of climate change on vulnerable populations in pediatrics: opportunities for AI, digital health, and beyond—a scoping review and selected case studies. Pediatric Research. https://doi.org/10.1038/s41390-024-03719-x
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Rowley, E. A., Mitchell, P. K., Yang, D.-H., Lewis, N., Dixon, B. E., Vazquez-Benitez, G., Fadel, W. F., Essien, I. J., Naleway, A. L., Stenehjem, E., Ong, T. C., Gaglani, M., Natarajan, K., Embi, P., Wiegand, R. E., Link-Gelles, R., Tenforde, M. W., & Fireman, B. (2025). Methods to Adjust for Confounding in Test-Negative Design COVID-19 Effectiveness Studies: Simulation Study. JMIR Formative Research, 9, e58981. https://doi.org/10.2196/58981
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Idnay, B., Xu, Z., Adams, W. G., Adibuzzaman, M., Anderson, N. R., Bahroos, N., Bell, D. S., Bumgardner, C., Campion, T., Castro, M., Cimino, J. J., Cohen, I. G., Dorr, D., Elkin, P. L., Fan, J. W., Ferris, T., Foran, D. J., Hanauer, D., Hogarth, M., … Peng, Y. (2025). Environment scan of generative AI infrastructure for clinical and translational science. Npj Health Systems, 2(1). https://doi.org/10.1038/s44401-024-00009-w
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Hui, D., Dudek, S., Kiryluk, K., Walunas, T. L., Kullo, I. J., Wei, W.-Q., Tiwari, H., Peterson, J. F., Chung, W. K., Davis, B. H., Khan, A., Kottyan, L. C., Limdi, N. A., Feng, Q., Puckelwartz, M. J., Weng, C., Smith, J. L., Karlson, E. W., … Ritchie, M. D. (2025). Risk factors affecting polygenic score performance across diverse cohorts. ELife, 12. CLOCKSS. https://doi.org/10.7554/elife.88149
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Fu, X., Mo, S., Buendia, A., Laurent, A. P., Shao, A., Alvarez-Torres, M. del M., Yu, T., Tan, J., Su, J., Sagatelian, R., Ferrando, A. A., Ciccia, A., Lan, Y., Owens, D. M., Palomero, T., Xing, E. P., & Rabadan, R. (2025). A foundation model of transcription across human cell types. Nature, 637(8047), 965–973. https://doi.org/10.1038/s41586-024-08391-z
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Aparicio, L., Crowley, L., Christin, J. R., Laplaca, C. J., Hibshoosh, H., Rabadan, R., & Shen, M. M. (2025). Meta-analyses of mouse and human prostate single-cell transcriptomes reveal widespread epithelial plasticity in tissue regression, regeneration, and cancer. Genome Medicine, 17(1). https://doi.org/10.1186/s13073-025-01432-w
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Campbell, E., Bear Don’t Walk, O. J., Fraser, H., Gichoya, J., Wagholikar, K. B., Kanter, A. S., Holl, F., & Craig, S. (2025). Principles and implementation strategies for equitable and representative academic partnerships in global health informatics research. Journal of the American Medical Informatics Association. https://doi.org/10.1093/jamia/ocaf015
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Tran, A. T., Karam, G. A., Zeevi, D., Qureshi, A. I., Malhotra, A., Majidi, S., Murthy, S. B., Park, S., Kontos, D., Falcone, G. J., Sheth, K. N., & Payabvash, S. (2025). Improving the Robustness of Deep-Learning Models in Predicting Hematoma Expansion from Admission Head CT. American Journal of Neuroradiology, ajnr.A8650. https://doi.org/10.3174/ajnr.a8650
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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
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Elias, P., Bhave, S., & Poterucha, T. J. (2025). Novel technology, novel challenges: How do we compare the performance of artificial intelligence to human experts? European Heart Journal. https://doi.org/10.1093/eurheartj/ehae760
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Vaynrub, A., Salazar, B., Feng, Y. E., West, H., Michel, A., Umakanth, S., Crew, K. D., & Kukafka, R. (2025). The breast cancer genetic testing experience: probing the potential utility of an online decision aid in risk perception and decision making. BMC Cancer, 25(1). https://doi.org/10.1186/s12885-024-13408-x
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Acitores Cortina, J. M., Fatapour, Y., Brown, K. L., Gisladottir, U., Zietz, M., Bear Don’t Walk IV, O. J., Peter, D., Berkowitz, J. S., Friedrich, N. A., Kivelson, S., Kuchi, A., Liu, H., Srinivasan, A., Tsang, K. K., & Tatonetti, N. P. (2025). Biases in Race and Ethnicity Introduced by Filtering Electronic Health Records for “Complete Data”: Observational Clinical Data Analysis. JMIR Medical Informatics, 13, e67591–e67591. https://doi.org/10.2196/67591
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Basile, A. O., Verma, A., Tang, L. A., Serper, M., Scanga, A., Farrell, A., Destin, B., Carr, R. M., Anyanwu‐Ofili, A., Rajagopal, G., Krikhely, A., Bessler, M., Reilly, M. P., Ritchie, M. D., Tatonetti, N. P., & Wattacheril, J. (2024). Rapid identification and phenotyping of nonalcoholic fatty liver disease patients using a machine‐based approach in diverse healthcare systems. Clinical and Translational Science, 18(1). Portico. https://doi.org/10.1111/cts.70105
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Yanover, C., Magen-Rimon, R., Voss, E. A., Swerdel, J., Sheahan, A., Hall, N., Park, J., Park, R. W., Lee, K. J., Shin, S. J., Seo, S. I., Lee, K.-J., Falconer, T., Haas, L., Nagy, P., Bowring, M. G., Cook, M., Miller, S., El-Hay, T., … Weisshof, R. (2024). Characteristics and Outcomes of Over a Million Patients with Inflammatory Bowel Disease in Seven Countries: Multinational Cohort Study and Open Data Resource. Digestive Diseases and Sciences. https://doi.org/10.1007/s10620-024-08787-x
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Villa, C. H., Biondich, P., Draper, N. L., Dores, G. M., Storch, E., Chada, K., Wong, H., Whitaker, B., Obidi, J., Vossoughi, S., Soares, A., Schilling, L. M., Natarajan, K., Goodman, M., Purkayastha, S., Zucker, R., Falconer, T., Williams, N., Reich, C., … Shoaibi, A. (2024). Patterns of platelet use evaluated in EHR networks of the Biologics Effectiveness and Safety Initiative, 2012–2018. Transfusion. Portico. https://doi.org/10.1111/trf.18114
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Orouji, S., Liu, M. C., Korem, T., & Peters, M. A. K. (2024). Domain adaptation in small-scale and heterogeneous biological datasets. Science Advances, 10(51). https://doi.org/10.1126/sciadv.adp6040
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Stear, B. J., Mohseni Ahooyi, T., Simmons, J. A., Kollar, C., Hartman, L., Beigel, K., Lahiri, A., Vasisht, S., Callahan, T. J., Nemarich, C. M., Silverstein, J. C., & Taylor, D. M. (2024). Petagraph: A large-scale unifying knowledge graph framework for integrating biomolecular and biomedical data. Scientific Data, 11(1). https://doi.org/10.1038/s41597-024-04070-w
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Topaz, M., Davoudi, A., Evans, L., Sridharan, S., Song, J., Chae, S., Barrón, Y., Hobensack, M., Scharp, D., Cato, K., Rossetti, S. C., Kapela, P., Xu, Z., Gupta, P., Zhang, Z., Mcdonald, M. V., & Bowles, K. H. (2025). Building a Time-Series Model to Predict Hospitalization Risks in Home Health Care: Insights Into Development, Accuracy, and Fairness. Journal of the American Medical Directors Association, 26(2), 105417. https://doi.org/10.1016/j.jamda.2024.105417
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Patiño-Galindo, J., García-Sastre, A., Kuhn, J. H., Rabadan, R., & Palacios, G. (2024). Recombination across distant coronavirid species and genera is a rare event with distinct genomic features. Journal of Virology, 98(12). https://doi.org/10.1128/jvi.01100-24
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Conover, M. M., Ryan, P. B., Chen, Y., Suchard, M. A., Hripcsak, G., & Schuemie, M. J. (2025). Objective study validity diagnostics: a framework requiring pre-specified, empirical verification to increase trust in the reliability of real-world evidence. Journal of the American Medical Informatics Association. https://doi.org/10.1093/jamia/ocae317
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Dierksen, F., Sommer, J. K., Tran, A. T., Lin, H., Haider, S. P., Maier, I. L., Aneja, S., Sanelli, P. C., Malhotra, A., Qureshi, A. I., Claassen, J., Park, S., Murthy, S. B., Falcone, G. J., Sheth, K. N., & Payabvash, S. (2024). Machine Learning Models for 3-Month Outcome Prediction Using Radiomics of Intracerebral Hemorrhage and Perihematomal Edema from Admission Head Computed Tomography (CT). Diagnostics, 14(24), 2827. https://doi.org/10.3390/diagnostics14242827
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Reading Turchioe, M., Desai, P., Harkins, S., Kim, J., Kumar, S., Zhang, Y., Joly, R., Pathak, J., Hermann, A., & Benda, N. (2024). Differing perspectives on artificial intelligence in mental healthcare among patients: a cross-sectional survey study. Frontiers in Digital Health, 6. https://doi.org/10.3389/fdgth.2024.1410758
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Ryan, C. P., Corcoran, D. L., Banskota, N., Eckstein Indik, C., Floratos, A., Friedman, R., Kobor, M. S., Kraus, V. B., Kraus, W. E., MacIsaac, J. L., Orenduff, M. C., Pieper, C. F., White, J. P., Ferrucci, L., Horvath, S., Huffman, K. M., & Belsky, D. W. (2024). The CALERIE Genomic Data Resource. Nature Aging. https://doi.org/10.1038/s43587-024-00775-0
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Bunne, C., Roohani, Y., Rosen, Y., Gupta, A., Zhang, X., Roed, M., Alexandrov, T., AlQuraishi, M., Brennan, P., Burkhardt, D. B., Califano, A., Cool, J., Dernburg, A. F., Ewing, K., Fox, E. B., Haury, M., Herr, A. E., Horvitz, E., Hsu, P. D., … Quake, S. R. (2024). How to build the virtual cell with artificial intelligence: Priorities and opportunities. Cell, 187(25), 7045–7063. https://doi.org/10.1016/j.cell.2024.11.015
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Ke, X., van Soldt, B., Vlahos, L., Zhou, Y., Qian, J., George, J., Capdevila, C., Glass, I., Yan, K., Califano, A., & Cardoso, W. V. (2024). Morphogenesis and regeneration share a conserved core transition cell state program that controls lung epithelial cell fate. Developmental Cell. https://doi.org/10.1016/j.devcel.2024.11.017
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Zolnoori, M., Zolnour, A., Vergez, S., Sridharan, S., Spens, I., Topaz, M., Noble, J. M., Bakken, S., Hirschberg, J., Bowles, K., Onorato, N., & McDonald, M. V. (2024). Beyond electronic health record data: leveraging natural language processing and machine learning to uncover cognitive insights from patient-nurse verbal communications. Journal of the American Medical Informatics Association. https://doi.org/10.1093/jamia/ocae300
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Zolnoori, M., Vergez, S., Xu, Z., Esmaeili, E., Zolnour, A., Anne Briggs, K., Scroggins, J. K., Hosseini Ebrahimabad, S. F., Noble, J. M., Topaz, M., Bakken, S., Bowles, K. H., Spens, I., Onorato, N., Sridharan, S., & McDonald, M. V. (2024). Decoding disparities: evaluating automatic speech recognition system performance in transcribing Black and White patient verbal communication with nurses in home healthcare. JAMIA open, 7(4), ooae130. https://doi.org/10.1093/jamiaopen/ooae130

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Bakken, S., Sang, E., & de Brujin, B. (2024). Returning value to communities from the All of Us Research Program through innovative approaches for data use, analysis, dissemination, and research capacity building. Journal of the American Medical Informatics Association, 31(12), 2773–2780. https://doi.org/10.1093/jamia/ocae276
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Ahluwalia, V. S., Doiphode, N., Mankowski, W. C., Cohen, E. A., Pati, S., Pantalone, L., Bakas, S., Brooks, A., Vachon, C. M., Conant, E. F., Gastounioti, A., & Kontos, D. (2024). Volumetric Breast Density Estimation From Three-Dimensional Reconstructed Digital Breast Tomosynthesis Images Using Deep Learning. JCO Clinical Cancer Informatics, 8. https://doi.org/10.1200/cci.24.00103
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