Health Informatics Research Publications | Duke University School of Medicine

2023

Adler-Milstein, J., Aggarwal, N., Ahmed, M., Castner, J., Evans, B. J., Gonzalez, A. A., James, C. A., Lin, S., Mandl, K. D., Matheny, M. E., Sendak, M. P., Shachar, C., & Williams, A. (2022). Meeting the Moment: Addressing Barriers and Facilitating Clinical Adoption of Artificial Intelligence in Medical Diagnosis. NAM perspectives, 2022, 10.31478/202209c. https://doi.org/10.31478/202209c
Burns, C. M., Pung, L., Witt, D., Gao, M., Sendak, M., Balu, S., Krakower, D., Marcus, J. L., Okeke, N. L., & Clement, M. E. (2023). Development of a Human Immunodeficiency Virus Risk Prediction Model Using Electronic Health Record Data From an Academic Health System in the Southern United States. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 76(2), 299–306. https://doi.org/10.1093/cid/ciac775
Byng, D., Thomas, S. M., Rushing, C. N., Lynch, T., McCarthy, A., Francescatti, A. B., Frank, E. S., Partridge, A. H., Thompson, A. M., Retèl, V. P., van Harten, W. H., Grimm, L. J., Hyslop, T., Hwang, E. S., & Ryser, M. D. (2023). Surveillance Imaging after Primary Diagnosis of Ductal Carcinoma in Situ. Radiology, 221210. Advance online publication. https://doi.org/10.1148/radiol.221210
Chang, F., Krishnan, J., Hurst, J. H., Yarrington, M. E., Anderson, D. J., O'Brien, E. C., & Goldstein, B. A. (2023). Comparing Natural Language Processing and Structured Medical Data to Develop a Computable Phenotype for Patients Hospitalized Due to COVID-19: Retrospective Analysis. JMIR medical informatics, 10.2196/46267. Advance online publication. https://doi.org/10.2196/46267
Chen, J., Engelhard, M., Henao, R., Berchuck, S., Eichner, B., Perrin, E. M., Sapiro, G., & Dawson, G. (2023). Enhancing early autism prediction based on electronic records using clinical narratives. Journal of biomedical informatics, 104390. Advance online publication. https://doi.org/10.1016/j.jbi.2023.104390
Chikwetu, L., Miao, Y., Woldetensae, M. K., Bell, D., Goldenholz, D. M., & Dunn, J. (2023). Does deidentification of data from wearable devices give us a false sense of security? A systematic review. The Lancet. Digital health, S2589-7500(22)00234-5. Advance online publication. https://doi.org/10.1016/S2589-7500(22)00234-5
Eisenstein, E. L., Zozus, M. N., Garza, M. Y., Lanham, H. J., Adagarla, B., Walden, A., Benjamin, D. K., Zimmerman, K. O., Kumar, K. R., & Best Pharmaceuticals for Children Act - Pediatric Trials Network Steering Committee (2023). Assessing clinical site readiness for electronic health record (EHR)-to-electronic data capture (EDC) automated data collection. Contemporary clinical trials, 128, 107144. https://doi.org/10.1016/j.cct.2023.107144
Engelhard, M. M., Henao, R., Berchuck, S. I., Chen, J., Eichner, B., Herkert, D., Kollins, S. H., Olson, A., Perrin, E. M., Rogers, U., Sullivan, C., Zhu, Y., Sapiro, G., & Dawson, G. (2023). Predictive Value of Early Autism Detection Models Based on Electronic Health Record Data Collected Before Age 1 Year. JAMA network open, 6(2), e2254303. https://doi.org/10.1001/jamanetworkopen.2022.54303
Fayanju, O. M., Greenup, R. A., Zafar, S. Y., Hyslop, T., Hwang, E. S., & Fish, L. J. (2023). Modifiable Barriers and Facilitators for Breast Cancer Care: A Thematic Analysis of Patient and Provider Perspectives. The Journal of surgical research, 284, 269–279. Advance online publication. https://doi.org/10.1016/j.jss.2022.11.074
Hong, C., Pencina, M. J., Wojdyla, D. M., Hall, J. L., Judd, S. E., Cary, M., Engelhard, M. M., Berchuck, S., Xian, Y., D'Agostino, R., Sr, Howard, G., Kissela, B., & Henao, R. (2023). Predictive Accuracy of Stroke Risk Prediction Models Across Black and White Race, Sex, and Age Groups. JAMA, 329(4), 306–317. https://doi.org/10.1001/jama.2022.24683
Hong, C., Liang, L., Yuan, Q., Cho, K., Liao, K. P., Pencina, M. J., Christiani, D. C., & Cai, T. (2023). Semi-supervised calibration of noisy event risk (SCANER) with electronic health records. Journal of biomedical informatics, 144, 104425. Advance online publication. https://doi.org/10.1016/j.jbi.2023.104425
Hong, J. C., Patel, P., Eclov, N. C. W., Stephens, S. J., Mowery, Y. M., Tenenbaum, J. D., & Palta, M. (2023). Healthcare provider evaluation of machine learning-directed care: reactions to deployment on a randomised controlled study. BMJ health & care informatics, 30(1), e100674. https://doi.org/10.1136/bmjhci-2022-100674
Hughes, A., Shandhi, M. M. H., Master, H., Dunn, J., & Brittain, E. (2023). Wearable Devices in Cardiovascular Medicine. Circulation research, 132(5), 652–670. https://doi.org/10.1161/CIRCRESAHA.122.322389
Hurst, J. H., Brucker, A., Zhao, C., Driscoll, H., Hostetler, H. P., Phillips, M., Rosenberg, B., Samsky, M. D., Smith, I., Reller, M. E., Strouse, J. J., Zhou, C. K., Dores, G. M., Wong, H. L., & Goldstein, B. A. (2023). Use of Structured Electronic Health Records Data Elements for the Development of Computable Phenotypes to Identify Potential Adverse Events Associated with Intravenous Immunoglobulin Infusion. Drug safety, 10.1007/s40264-023-01276-6. Advance online publication. https://doi.org/10.1007/s40264-023-01276-6
Kolls, B. J., Farooqui, I., Arulraja, E., Meek, L. A., & Sahgal, A. K. (2023). Using the ICH score during acute telestroke consults to triage transfer to tertiary centers. Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association, 32(3), 106975. Advance online publication. https://doi.org/10.1016/j.jstrokecerebrovasdis.2022.106975
Konz, N., Buda, M., Gu, H., Saha, A., Yang, J., Chledowski, J., Park, J., Witowski, J., Geras, K. J., Shoshan, Y., Gilboa-Solomon, F., Khapun, D., Ratner, V., Barkan, E., Ozery-Flato, M., Martí, R., Omigbodun, A., Marasinou, C., Nakhaei, N., Hsu, W., … Mazurowski, M. A. (2023). A Competition, Benchmark, Code, and Data for Using Artificial Intelligence to Detect Lesions in Digital Breast Tomosynthesis. JAMA network open, 6(2), e230524. https://doi.org/10.1001/jamanetworkopen.2023.0524
Konz, N., Dong, H., & Mazurowski, M. A. (2023). Unsupervised anomaly localization in high-resolution breast scans using deep pluralistic image completion. Medical image analysis, 87, 102836. https://doi.org/10.1016/j.media.2023.102836
Ma, J. E., Lowe, J., Berkowitz, C., Kim, A., Togo, I., Musser, R. C., Fischer, J., Shah, K., Ibrahim, S., Bosworth, H. B., Totten, A. M., & Dolor, R. (2023). Provider Interaction With an Electronic Health Record Notification to Identify Eligible Patients for a Cluster Randomized Trial of Advance Care Planning in Primary Care: Secondary Analysis. Journal of medical Internet research, 25, e41884. https://doi.org/10.2196/41884
Mariottoni, E. B., Datta, S., Shigueoka, L. S., Jammal, A. A., Tavares, I. M., Henao, R., Carin, L., & Medeiros, F. A. (2023). Deep Learning-Assisted Detection of Glaucoma Progression in Spectral-Domain OCT. Ophthalmology. Glaucoma, 6(3), 228–238. https://doi.org/10.1016/j.ogla.2022.11.004
Marsolo, K. A., Weinfurt, K. P., Staman, K. L., & Hammill, B. G. (2023). Moving From Idealism to Realism With Data Sharing. Annals of internal medicine, 10.7326/M22-2973. Advance online publication. https://doi.org/10.7326/M22-2973
May, J. T., Myers, J., Noonan, D., McConnell, E., & Cary, M. P. (2023). A call to action to improve the completeness of older adult sexual and gender minority data in electronic health records. Journal of the American Medical Informatics Association : JAMIA, ocad130. Advance online publication. https://doi.org/10.1093/jamia/ocad130
Pasquale, D. K., Welsh, W., Olson, A., Yacoub, M., Moody, J., Barajas Gomez, B. A., Bentley-Edwards, K. L., McCall, J., Solis-Guzman, M. L., Dunn, J. P., Woods, C. W., Petzold, E. A., Bowie, A. C., Singh, K., & Huang, E. S. (2023). Scalable Strategies to Increase Efficiency and Augment Public Health Activities During Epidemic Peaks. Journal of public health management and practice : JPHMP, 10.1097/PHH.0000000000001780. Advance online publication. https://doi.org/10.1097/PHH.0000000000001780
Pavon, J. M., Previll, L., Woo, M., Henao, R., Solomon, M., Rogers, U., Olson, A., Fischer, J., Leo, C., Fillenbaum, G., Hoenig, H., & Casarett, D. (2023). Machine learning functional impairment classification with electronic health record data. Journal of the American Geriatrics Society, 10.1111/jgs.18383. Advance online publication. https://doi.org/10.1111/jgs.18383
Perakslis, E. D., Ranney, M. L., & Goldsack, J. C. (2023). Characterizing cyber harms from digital health. Nature medicine, 10.1038/s41591-022-02167-6. Advance online publication. https://doi.org/10.1038/s41591-022-02167-6
Rao, V. N., Cyr, D., Wruck, L., Sanders, G., Hofmann, P., Rössig, L., Siedentop, H., Evers, T., Meyer, M., Paraschin, K., Nkulikiyinka, R., Parikh, K., & Felker, G. M. (2023). Electronic Health Record Characterization and Outcomes of Heart Failure with Preserved Ejection Fraction. American heart journal, S0002-8703(23)00100-X. Advance online publication. https://doi.org/10.1016/j.ahj.2023.04.013
Samsa, G., Colborn, K., Olsen, M., Pomann, G. M., Grambow, S., Neely, M., & Troy, J. (2023). A Visual Tool to Help Develop a Statistical Analysis Plan for Randomized Trials in Palliative Care. Journal of pain and symptom management, 65(1), e87–e95. https://doi.org/10.1016/j.jpainsymman.2022.08.004
Sandhu, S., Sendak, M. P., Ratliff, W., Knechtle, W., Fulkerson, W. J., Jr, & Balu, S. (2023). Accelerating health system innovation: principles and practices from the Duke Institute for Health Innovation. Patterns (New York, N.Y.), 4(4), 100710. https://doi.org/10.1016/j.patter.2023.100710
Tan, A. L. M., Getzen, E. J., Hutch, M. R., Strasser, Z. H., Gutiérrez-Sacristán, A., Le, T. T., Dagliati, A., Morris, M., Hanauer, D. A., Moal, B., Bonzel, C. L., Yuan, W., Chiudinelli, L., Das, P., Zhang, H. G., Aronow, B. J., Avilllach, P., Brat, G. A., Cai, T., Hong, C., … COVID-19 by EHR 4CE Collaborative Group/Consortium (2023). Informative Missingness: What can we learn from patterns in missing laboratory data in the electronic health record?. Journal of biomedical informatics, 104306. Advance online publication. https://doi.org/10.1016/j.jbi.2023.104306
Tanabe, P., Bosworth, H. B., Crawford, R. D., Glassberg, J., Miller, C. N., Paice, J. A., & Silva, S. (2023). Time to pain relief: A randomized controlled trial in the emergency department during vaso-occlusive episodes in sickle cell disease. European journal of haematology, 10.1111/ejh.13924. Advance online publication. https://doi.org/10.1111/ejh.13924
Vassy, J. L., Posner, D. C., Ho, Y. L., Gagnon, D. R., Galloway, A., Tanukonda, V., Houghton, S. C., Madduri, R. K., McMahon, B. H., Tsao, P. S., Damrauer, S. M., O'Donnell, C. J., Assimes, T. L., Casas, J. P., Gaziano, J. M., Pencina, M. J., Sun, Y. V., Cho, K., & Wilson, P. W. F. (2023). Cardiovascular Disease Risk Assessment Using Traditional Risk Factors and Polygenic Risk Scores in the Million Veteran Program. JAMA cardiology, 8(6), 564–574. https://doi.org/10.1001/jamacardio.2023.0857
Weissler, E. H., Hammill, B. G., Armstrong, J. L., Vekstein, A. M., Chodavadia, P., Long, C. A., Roe, M., & Hughes, G. C. (2023). Association Between Device Type and Type IIIb Endoleaks Following Thoracic Endovascular Aortic Repair. European journal of vascular and endovascular surgery: the official journal of the European Society for Vascular Surgery, 65(1), 112–119. https://doi.org/10.1016/j.ejvs.2022.10.005
Wen, J., Zhang, X., Rush, E., Panickan, V. A., Li, X., Cai, T., Zhou, D., Ho, Y. L., Costa, L., Begoli, E., Hong, C., Gaziano, J. M., Cho, K., Lu, J., Liao, K. P., Zitnik, M., & Cai, T. (2023). Multimodal representation learning for predicting molecule-disease relations. Bioinformatics (Oxford, England), 39(2), btad085. https://doi.org/10.1093/bioinformatics/btad085
Weng, J., Wildman-Tobriner, B., Buda, M., Yang, J., Ho, L. M., Allen, B. C., Ehieli, W. L., Miller, C. M., Zhang, J., & Mazurowski, M. A. (2023). Deep learning for classification of thyroid nodules on ultrasound: validation on an independent dataset. Clinical imaging, 99, 60–66. https://doi.org/10.1016/j.clinimag.2023.04.010
Yang, J., Page, L. C., Wagner, L., Wildman-Tobriner, B., Bisset, L., Frush, D., & Mazurowski, M. A. (2023). Thyroid Nodules on Ultrasound in Children and Young Adults: Comparison of Diagnostic Performance of Radiologists' Impressions, ACR TI-RADS, and a Deep Learning Algorithm. AJR. American journal of roentgenology, 220(3), 408–417. https://doi.org/10.2214/AJR.22.28231
Zaribafzadeh, H., Webster, W. L., Vail, C. J., Daigle, T., Kirk, A. D., Allen, P. J., Henao, R., & Buckland, D. M. (2023). Development, Deployment, and Implementation of a Machine Learning Surgical Case Length Prediction Model and Prospective Evaluation. Annals of surgery, 10.1097/SLA.0000000000005936. Advance online publication. https://doi.org/10.1097/SLA.0000000000005936
Zhang, J., Mazurowski, M. A., & Grimm, L. J. (2023). Feasibility of predicting a screening digital breast tomosynthesis recall using features extracted from the electronic medical record. European journal of radiology, 166, 110979. Advance online publication. https://doi.org/10.1016/j.ejrad.2023.110979
Zhang, J., Mazurowski, M. A., Allen, B. C., & Wildman-Tobriner, B. (2023). Multistep Automated Data Labelling Procedure (MADLaP) for thyroid nodules on ultrasound: An artificial intelligence approach for automating image annotation. Artificial intelligence in medicine, 141, 102553. https://doi.org/10.1016/j.artmed.2023.102553

2022

Adil, S. M., Elahi, C., Patel, D. N., Seas, A., Warman, P. I., Fuller, A. T., Haglund, M. M., & Dunn, T. W. (2022). Deep Learning to Predict Traumatic Brain Injury Outcomes in the Low-Resource Setting. World neurosurgery, S1878-8750(22)00244-3. Advance online publication. https://doi.org/10.1016/j.wneu.2022.02.097
Adil, S. M., Charalambous, L. T., Rajkumar, S., Seas, A., Warman, P. I., Murphy, K. R., Rahimpour, S., Parente, B., Dharmapurikar, R., Dunn, T. W., & Lad, S. P. (2022). Machine Learning to Predict Successful Opioid Dose Reduction or Stabilization After Spinal Cord Stimulation. Neurosurgery, 91(2), 272–279. https://doi.org/10.1227/neu.0000000000001969
Barnes, J. A., Eid, M. A., Moore, K., Aryal, S., Gebre, E., Woodard, J. N., Kitpanit, N., Mao, J., Kuwayama, D. P., Suckow, B. D., Schneider, D., Abushaikha, T., Zusterzeel, R., Vemulapalli, S., Shenkman, E. A., Williams, J., Sedrakyan, A., & Goodney, P. (2022). Use of real-world data and clinical registries to identify new uses of existing vascular endografts: combined use of GORE EXCLUDER Iliac Branch Endoprosthesis and GORE VIABAHN VBX Balloon Expandable Endoprosthesis. BMJ surgery, interventions, & health technologies, 4(1), e000085. https://doi.org/10.1136/bmjsit-2021-000085
Basch, E., Schrag, D., Henson, S., Jansen, J., Ginos, B., Stover, A. M., Carr, P., Spears, P. A., Jonsson, M., Deal, A. M., Bennett, A. V., Thanarajasingam, G., Rogak, L. J., Reeve, B. B., Snyder, C., Bruner, D., Cella, D., Kottschade, L. A., Perlmutter, J., Geoghegan, C., … Dueck, A. C. (2022). Effect of Electronic Symptom Monitoring on Patient-Reported Outcomes Among Patients With Metastatic Cancer: A Randomized Clinical Trial. JAMA, 327(24), 2413–2422. https://doi.org/10.1001/jama.2022.9265
Bauman, P. A., Doxey, A. C., Eberini, I., Islamovic, E., Jungo, F., Kessenich, C., Kough, J., Krishan, M., Palazzolo, L., Privalle, L., Rodriguez, C. E., Satchell, K., Silvanovich, A., & Pereira Mouriès, L. (2022). "From Protein Toxins to Applied Toxicological Testing" virtual workshop identifies the need for a bioinformatic framework to assess novel food protein safety. Regulatory toxicology and pharmacology : RTP, 131, 105146. https://doi.org/10.1016/j.yrtph.2022.105146
Bedoya, A. D., Economou-Zavlanos, N. J., Goldstein, B. A., Young, A., Jelovsek, J. E., O'Brien, C., Parrish, A. B., Elengold, S., Lytle, K., Balu, S., Huang, E., Poon, E. G., & Pencina, M. J. (2022). A framework for the oversight and local deployment of safe and high-quality prediction models. Journal of the American Medical Informatics Association : JAMIA, ocac078. Advance online publication. https://doi.org/10.1093/jamia/ocac078
Berchuck, S. I., Jammal, A. A., Page, D., Somers, T. J., & Medeiros, F. A. (2022). A Framework for Automating Psychiatric Distress Screening in Ophthalmology Clinics Using an EHR-Derived AI Algorithm. Translational vision science & technology, 11(10), 6. https://doi.org/10.1167/tvst.11.10.6
Berkowitz, S. J., Kwan, D., Cornish, T. C., Silver, E. L., Thullner, K. S., Aisen, A., Bui, M. M., Clark, S. D., Clunie, D. A., Eid, M., Hartman, D. J., Ho, K., Leontiev, A., Luviano, D. M., O'Toole, P. E., Parwani, A. V., Pereira, N. S., Rotemberg, V., Vining, D. J., Gaskin, C. M., Roth, C. J., Folio, L. R. (2022). Interactive Multimedia Reporting Technical Considerations: HIMSS-SIIM Collaborative White Paper. Journal of digital imaging, 10.1007/s10278-022-00658-z. Advance online publication. https://doi.org/10.1007/s10278-022-00658-z
Bhavsar, N. A., Yang, L. Z., Phelan, M., Shepherd-Banigan, M., Goldstein, B. A., Peskoe, S., Palta, P., Hirsch, J. A., Mitchell, N. S., Hirsch, A. G., Lunyera, J., Mohottige, D., Diamantidis, C. J., Maciejewski, M. L., & Boulware, L. E. (2022). Association between Gentrification and Health and Healthcare Utilization. Journal of urban health : bulletin of the New York Academy of Medicine, 10.1007/s11524-022-00692-w. Advance online publication. https://doi.org/10.1007/s11524-022-00692-w
Bodkin, N., Ross, M., McClain, M. T., Ko, E. R., Woods, C. W., Ginsburg, G. S., Henao, R., & Tsalik, E. L. (2022). Systematic comparison of published host gene expression signatures for bacterial/viral discrimination. Genome medicine, 14(1), 18. https://doi.org/10.1186/s13073-022-01025-x
Burns, L., Kalesnik-Orszulak, R., Spring, R., Zeegers, F., Rutstein, M., Hukkelhoven, M., Wruck, L., & O'Donnell, J. (2022). Real World-Evidence for Regulatory Use Decision Aid: An Interactive Tool To Inform Clinical Development and Regulatory Strategies. Advances in therapy, 1–7. Advance online publication. https://doi.org/10.1007/s12325-022-02257-4
Burns, C. M., Pung, L., Witt, D., Gao, M., Sendak, M., Balu, S., Krakower, D., Marcus, J. L., Okeke, N. L., & Clement, M. E. (2022). Development of an HIV Risk Prediction Model Using Electronic Health Record Data from an Academic Health System in the Southern United States. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, ciac775. Advance online publication. https://doi.org/10.1093/cid/ciac775
Cai, T., He, Z., Hong, C., Zhang, Y., Ho, Y. L., Honerlaw, J., Geva, A., Ayakulangara Panickan, V., King, A., Gagnon, D. R., Gaziano, M., Cho, K., Liao, K., & Cai, T. (2022). Scalable Relevance Ranking Algorithm via Semantic Similarity Assessment Improves Efficiency of Medical Chart Review. Journal of biomedical informatics, 104109. Advance online publication. https://doi.org/10.1016/j.jbi.2022.104109
Califf, R. M., Wong, C., Doraiswamy, P. M., Hong, D. S., Miller, D. P., Mega, J. L., & Baseline Study Group (2022). Biological and clinical correlates of the patient health questionnaire-9: exploratory cross-sectional analyses of the baseline health study. BMJ open, 12(1), e054741. https://doi.org/10.1136/bmjopen-2021-054741
Cao, S., Konz, N., Duncan, J., & Mazurowski, M. A. (2022). Deep Learning for Breast MRI Style Transfer with Limited Training Data. Journal of digital imaging, 10.1007/s10278-022-00755-z. Advance online publication. https://doi.org/10.1007/s10278-022-00755-z
Carrillo, G. A., Cohen-Wolkowiez, M., D'Agostino, E. M., Marsolo, K., Wruck, L. M., Johnson, L., Topping, J., Richmond, A., Corbie, G., & Kibbe, W. A. (2022). Standardizing, Harmonizing, and Protecting Data Collection to Broaden the Impact of COVID-19 Research: The Rapid Acceleration of Diagnostics-Underserved Populations (RADx-up) Initiative. Journal of the American Medical Informatics Association : JAMIA, ocac097. Advance online publication. https://doi.org/10.1093/jamia/ocac097
Chen, W. C., Boreta, L., Braunstein, S. E., Rabow, M. W., Kaplan, L. E., Tenenbaum, J. D., Morin, O., Park, C. C., & Hong, J. C. (2022). Association of mental health diagnosis with race and all-cause mortality after a cancer diagnosis: Large-scale analysis of electronic health record data. Cancer, 128(2), 344–352. https://doi.org/10.1002/cncr.33903
Chen, Z., Zhang, H., George, T. J., Guo, Y., Prosperi, M., Guo, J., Braithwaite, D., Wang, F., Kibbe, W., Wagner, L., & Bian, J. (2022). Simulating Colorectal Cancer Trials Using Real-World Data. JCO clinical cancer informatics, 6, e2100195. https://doi.org/10.1200/CCI.21.00195
Cerrato, P., Halamka, J., & Pencina, M. (2022). A proposal for developing a platform that evaluates algorithmic equity and accuracy. BMJ health & care informatics, 29(1), e100423. https://doi.org/10.1136/bmjhci-2021-100423
Cho, P. J., Yi, J., Ho, E., Shandhi, M., Dinh, Y., Patil, A., Martin, L., Singh, G., Bent, B., Ginsburg, G., Smuck, M., Woods, C., Shaw, R., & Dunn, J. (2022). Demographic Imbalances Resulting From the Bring-Your-Own-Device Study Design. JMIR mHealth and uHealth, 10(4), e29510. https://doi.org/10.2196/29510
Choi, H. H., Kotsenas, A. L., Chen, J. V., Bronsky, C., Roth, C. J., & Kohli, M. D. (2022). Multi-institutional Experience with Patient Image Access Through Electronic Health Record Patient Portals. Journal of digital imaging, 35(2), 320–326. https://doi.org/10.1007/s10278-021-00565-9
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2021

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Zhang O, Ding C, Pereira T, Xiao R, Gadhoumi K, Meisel K, Lee RJ, Chen Y, Hu X. Explainability Metrics of Deep Convolutional Networks for Photoplethysmography Quality Assessment. IEEE Access. 2021;9:29736-29745. doi: 10.1109/access.2021.3054613. Epub 2021 Jan 26. PMID: 33747683; PMCID: PMC7978398.
Zhou M, Wang Q, Zheng C, John Rush A, Volkow ND, Xu R. Drug repurposing for opioid use disorders: integration of computational prediction, clinical corroboration, and mechanism of action analyses. Mol Psychiatry. 2021 Jan 11:1–11. doi: 10.1038/s41380-020-01011-y. Epub ahead of print. PMID: 33432189; PMCID: PMC7797705.
Zullig LL, Shahsahebi M, Neely B, Hyslop T, Avecilla RAV, Griffin BM, Clayton-Stiglbauer K, Coles T, Owen L, Reeve BB, Shah K, Shelby RA, Sutton L, Dinan MA, Zafar SY, Shah NP, Dent S, Oeffinger KC. Low-touch, team-based care for co-morbidity management in cancer patients: the ONE TEAM randomized controlled trial. BMC Fam Pract. 2021 Nov 18;22(1):234. doi: 10.1186/s12875-021-01569-8. PMID: 34794388; PMCID: PMC8600877.

2020

Abdulrahim, J. W., Kwee, L. C., Alenezi, F., Sun, A. Y., Baras, A., Ajayi, T. A., Henao, R., Holley, C. L., McGarrah, R. W., Daubert, J. P., Truby, L. K., Vemulapalli, S., Wang, A., Khouri, M. G., & Shah, S. H. (2020). Identification of Undetected Monogenic Cardiovascular Disorders. Journal of the American College of Cardiology, 76(7), 797–808. https://doi.org/10.1016/j.jacc.2020.06.037
Adil, S. M., Elahi, C., Gramer, R., Spears, C. A., Fuller, A. T., Haglund, M. M., & Dunn, T. W. (2021). Predicting the Individual Treatment Effect of Neurosurgery for Patients with Traumatic Brain Injury in the Low-Resource Setting: A Machine Learning Approach in Uganda. Journal of neurotrauma, 38(7), 928–939. https://doi.org/10.1089/neu.2020.7262
Altunel E, Roghani RS, Chen KY, Kim SY, McCall S, Ware KE, Shen X, Somarelli JA, Hsu DS. Development of a precision medicine pipeline to identify personalized treatments for colorectal cancer. BMC Cancer. 2020 Jun 24;20(1):592. doi: 10.1186/s12885-020-07090-y. PMID: 32580713; PMCID: PMC7313200.
Arges, K., Assimes, T., Bajaj, V., Balu, S., Bashir, M. R., Beskow, L., Blanco, R., Califf, R., Campbell, P., Carin, L., Christian, V., Cousins, S., Das, M., Dockery, M., Douglas, P. S., Dunham, A., Eckstrand, J., Fleischmann, D., Ford, E., Fraulo, E., … Wong, C. A. (2020). The Project Baseline Health Study: a step towards a broader mission to map human health. NPJ digital medicine, 3, 84. https://doi.org/10.1038/s41746-020-0290-y
Armstrong, P. W., Lam, C., Anstrom, K. J., Ezekowitz, J., Hernandez, A. F., O’Connor, C. M., Pieske, B., Ponikowski, P., Shah, S. J., Solomon, S. D., Voors, A. A., She, L., Vlajnic, V., Carvalho, F., Bamber, L., Blaustein, R. O., Roessig, L., Butler, J., & VITALITY-HFpEF Study Group (2020). Effect of Vericiguat vs Placebo on Quality of Life in Patients With Heart Failure and Preserved Ejection Fraction: The VITALITY-HFpEF Randomized Clinical Trial. JAMA, 324(15), 1512–1521. https://doi.org/10.1001/jama.2020.15922
Bachmann, K. N., Roumie, C. L., Wiese, A. D., Grijalva, C. G., Buse, J. B., Bradford, R., Zalimeni, E. O., Knoepp, P., Dard, S., Morris, H. L., Donahoo, W. T., Fanous, N., Fonseca, V., Katalenich, B., Choi, S., Louzao, D., O’Brien, E., Cook, M. M., Rothman, R. L., & Chakkalakal, R. J. (2020). Diabetes medication regimens and patient clinical characteristics in the national patient-centered clinical research network, PCORnet. Pharmacology research & perspectives, 8(5), e00637. https://doi.org/10.1002/prp2.637
Bae JA, Curtis LH, Hernandez AF. National Hospital Quality Rankings: Improving the Value of Information in Hospital Rating Systems [published online ahead of print, 2020 Jul 27]. JAMA. 2020;10.1001/jama.2020.11165. doi:10.1001/jama.2020.11165
Barnholtz-Sloan, J. S., Rollison, D. E., Basu, A., Borowsky, A. D., Bui, A., DiGiovanna, J., Garcia-Closas, M., Genkinger, J. M., Gerke, T., Induni, M., Lacey, J. V., Jr, Mirel, L., Permuth, J. B., Saltz, J., Shenkman, E. A., Ulrich, C. M., Zheng, W. J., Nadaf, S., & Kibbe, W. A. (2020). Cancer Informatics for Cancer Centers (CI4CC): Building a Community Focused on Sharing Ideas and Best Practices to Improve Cancer Care and Patient Outcomes. JCO clinical cancer informatics, 4, 108–116. https://doi.org/10.1200/CCI.19.00166
Bedoya AD, Futoma J, Clement ME, Corey K, Brajer N, Lin A, Simons MG, Gao M, Nichols M, Balu S, Heller K, Sendak M, O’Brien C. Machine learning for early detection of sepsis: an internal and temporal validation study. JAMIA Open. 2020 Apr 11;3(2):252-260. doi: 10.1093/jamiaopen/ooaa006. PMID: 32734166; PMCID: PMC7382639.
Bedoya AD, Bhavsar NA, Adagarla B, Page CB, Goldstein BA, MacIntyre NR. Unanticipated Respiratory Compromise and Unplanned Intubations on General Medical and Surgical Floors. Respir Care. 2020;65(9):1233-40. doi: 10.4187/respcare.07438. Epub 2020 Mar 10. PMID: 32156789.
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Boulware, L. E., Harris, G. B., Harewood, P., Johnson, F. F., Maxson, P., Bhavsar, N., Blackwelder, S. S., Poley, S. S., Arnold, K., Akindele, B., Ferranti, J., & Lyn, M. (2020). Democratizing health system data to impact social and environmental health contexts: a novel collaborative community data-sharing model. Journal of public health (Oxford, England), 42(4), 784–792. https://doi.org/10.1093/pubmed/fdz171
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Brajer N, Cozzi B, Gao M, Nichols M, Revoir M, Balu S, Futoma J, Bae J, Setji N, Hernandez A, Sendak M. Prospective and External Evaluation of a Machine Learning Model to Predict In-Hospital Mortality of Adults at Time of Admission. JAMA Netw Open. 2020 Feb 5;3(2):e1920733. doi: 10.1001/jamanetworkopen.2019.20733. PMID: 32031645.
Califf RM, Hernandez AF, Landray M. Weighing the Benefits and Risks of Proliferating Observational Treatment Assessments: Observational Cacophony, Randomized Harmony [published online ahead of print, 2020 Jul 31]. JAMA. 2020;10.1001/jama.2020.13319. doi:10.1001/jama.2020.13319
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Casanova, R., Saldana, S., Lutz, M. W., Plassman, B. L., Kuchibhatla, M., & Hayden, K. M. (2020). Investigating Predictors of Cognitive Decline Using Machine Learning. The journals of gerontology. Series B, Psychological sciences and social sciences, 75(4), 733–742. https://doi.org/10.1093/geronb/gby054
Chang B, Sun Z, Peiris P, Huang ES, Benrashid E, Dillavou ED. Deep Learning-Based Risk Model for Best Management of Closed Groin Incisions After Vascular Surgery. J Surg Res. 2020;254:408-416. doi:10.1016/j.jss.2020.02.012
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Cho, A.H., Namdari, N.T., Bowlby, L., Zipkin, D.A., Greenblatt, L., Causey, H.E., … Boulware, L.E. (2020). Multiyear Outcomes of a Population-Oriented Care Redesign in an Internal Medicine Residency Continuity Clinic. Journal of Health Care for the Poor and Underserved 31(2), 724-741. doi:10.1353/hpu.2020.0057.
Chowdhury AS, Lofgren ET, Moehring RW, Broschat SL. Identifying predictors of antimicrobial exposure in hospitalized patients using a machine learning approach. Journal of applied microbiology. 2020 Mar;128(3):688-96.
Cieslowski B, Brock L, Richesson RL, Silva S, Kim H. Optimization of Nursing-Specific Flu Alerts. CIN: Computers, Informatics, Nursing. 9000;Publish Ahead of Print. doi: 10.1097/CIN.0000000000000616
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Crowson MG, Witsell D, Eskander A. Using Google Trends to Predict Pediatric Respiratory Syncytial Virus Encounters at a Major Health Care System. J Med Syst. 2020;44(3):57. Published 2020 Jan 30. doi:10.1007/s10916-020-1526-8
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2019

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Banerjee I, Sofela M, Yang J, Chen JH, Shah NH, Ball R, Mushlin AI, Desai M, Bledsoe J, Amrhein T, Rubin DL, Zamanian R, Lungren MP. Development and Performance of the Pulmonary Embolism Result Forecast Model (PERFORM) for Computed Tomography Clinical Decision Support. JAMA Netw Open. 2019 Aug 2;2(8):e198719. doi: 10.1001/jamanetworkopen.2019.8719. PMID: 31390040; PMCID: PMC6686780.
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Biederman DJ, Modarai F, Gamble J, et al. Identifying Patients Experiencing Homelessness in an Electronic Health Record and Assessing Qualification for Medical Respite: A Five-Year Retrospective Review. J Health Care Poor Underserved. 2019;30(1):297-309.
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Blalock DV, Bosworth HB, Reeve BB, Voils CI. Co-occurring reasons for medication nonadherence within subgroups of patients with hyperlipidemia. J Behav Med. 2019;42(2):291-299.
Blaske A, Amanda M, Oates J, Crofford L, Clowse ME, Barnado A. 51 Births to Women with Systemic Lupus Erythematosus can be Identified Accurately in the Electronic Health Record. Lupus Science & Medicine. 2019;6(Suppl 1):A38-A39.
Boulware LE, Lyn M. Who Will Drive the Change? Democratizing Health Data. Am J Public Health. 2019;109(4):547-548.
Cabacungan AN, Diamantidis CJ, St Clair Russell J, Strigo TS, Pounds I, Alkon A, Riley JA, Falkovic M, Pendergast JF, Davenport CA, Ellis MJ, Sudan DL, Hill-Briggs F, Browne T, Ephraim PL, Boulware LE. Development of a Telehealth Intervention to Improve Access to Live Donor Kidney Transplantation. Transplant Proc. 2019;51(3):665-675.
Campbell WS, Carter AB, Cushman-Vokoun AM, Greiner TC, Dash RC, et al. A Model Information Management Plan for Molecular Pathology Sequence Data Using Standards: From Sequencer to Electronic Health Record. The Journal of molecular diagnostics : JMD. 2019;21(3):408-417.
Chang, Y., Lafata, K., Sun, W., Wang, C., Chang, Z., Kirkpatrick, J. P., & Yin, F. F. (2019). An investigation of machine learning methods in delta-radiomics feature analysis. PloS one, 14(12), e0226348. https://doi.org/10.1371/journal.pone.0226348
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Chowdhury, A. S., Lofgren, E. T., Moehring, R. W., & Broschat, S. L. (2020). Identifying predictors of antimicrobial exposure in hospitalized patients using a machine learning approach. Journal of applied microbiology, 128(3), 688–696. https://doi.org/10.1111/jam.14499
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Goldstein BA, Phelan M, Pagidipati NJ, Holman RR, Pencina MJ, Stuart EA. An Outcome Model Approach to Transporting a Randomized Controlled Trial Results to a Target Population. J Am Med Inf Assoc. 2019;26(5):429-437.
Goldstein BA, Rigdon J. Using Machine Learning to Identify Heterogeneous Effects in Randomized Clinical Trials-Moving Beyond the Forest Plot and Into the Forest. JAMA Netw Open. 2019;2(3):e190004.
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2018

Adam, G. P., Springs, S., Trikalinos, T., Williams, J. W., Jr, Eaton, J. L., Von Isenburg, M., Gierisch, J. M., Wilson, L. M., Robinson, K. A., Viswanathan, M., Middleton, J. C., Forman-Hoffman, V. L., Berliner, E., & Kaplan, R. M. (2018). Does information from ClinicalTrials.gov increase transparency and reduce bias? Results from a five-report case series. Systematic reviews, 7(1), 59. https://doi.org/10.1186/s13643-018-0726-5
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Chen X, Gururaj AE, Ozyurt B, Liu R, Soysal E, Cohen T, Tiryaki F, Li Y, Zong N, Jiang M, Rogith D, Salimi M, Kim HE, et al. DataMed – an open source discovery index for finding biomedical datasets. Journal of the American Medical Informatics Association : JAMIA. 2018.
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Cox CE, Jones DM, Reagan W, Key MD, Chow V, McFarlin J, Casarett D, Creutzfeldt CJ, Docherty SL. . Palliative Care Planner: A Pilot Study to Evaluate Acceptability and Usability of an Electronic Health Records System-integrated, Needs-targeted App Platform. Ann Am Thoracic Society. 2018;15(1):59-68.
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Gupta A, Allen LA, Bhatt DL, Cox M, DeVore AD, Heidenreich PA, Hernandez AF, Peterson ED, Matsouaka RA et al. Association of the Hospital Readmissions Reduction Program Implementation With Readmission and Mortality Outcomes in Heart Failure. JAMA Cardiol. 2018;3(1):44-53.
Hammond WE. How do You Know when You have Interoperability? European Journal for Biomedical Informatics. 2018; 24(3):13-20.
Hirschey R, Kimmick G, Hockenberry M, Shaw R, Pan W, Lipkus I. Protocol for Moving On: a randomized controlled trial to increase outcome expectations and exercise among breast cancer survivors. Nurs Open. 2018;5(1):101-108.
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Hong JC, Niedzwiecki D, Palta M, Tenenbaum JD. Predicting Emergency Visits and Hospital Admissions During Radiation and Chemoradiation: An Internally Validated Pretreatment Machine Learning Algorithm. JCO Clinical Cancer Informatics. 2018(2):1-11.
Hull LE, Lynch JA, Berse BB, Kelley MJ, et al. Clinical Impact of 21-Gene Recurrence Score Test Within the Veterans Health Administration: Utilization and Receipt of Guideline-Concordant Care. Clin Breast Cancer. 2018;18(2):135-143.
Jonassaint CR, Rao N, Sciuto A, Switzer GE, De Castro L, Kato GJ, Jonassaint JC, Hammal Z, Shah N, Wasan A. Abstract Animations for the Communication and Assessment of Pain in Adults: Cross-Sectional Feasibility Study. J Med Internet Res. 2018;20(8):e10056.
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