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Publications

2020

Gatwood K. Chisholm-Burns M, Davis R, Thomas F, Potukuchi P, Hung A, Kovesdy C. Disease Management, Resource Utilization and Health Outcomes Related to Initial Oral Diabetic Medication Adherence among Veterans with Incident Diabetes J Gen Intern Med, in press

Carroll K, Gardner K, Wright R, Tylavsky FA, Adgent M, Gebretsadik T, Hartman T, Rosa MP, Bush N, Davis RL, LeWinn, K, Kocak, M Prenatal Omega-3 and Omega-6 Polyunsaturated Fatty Acids and Childhood Atopic Dermatitis J Allergy Clin Immunol, in press

Rosa MP, Hartman T, Adgent M, Gentry K, Gebretsadik T, Moore P, Bush N, Davis RL, LeWinn, K, Tylavsky F Prenatal polyunsaturated fatty acids and child asthma: effect modification by maternal asthma and child sex J Allergy Clin Immunol, in press

Mohammed A, Podila P, Davis R, Ataga K, Hankins J, Kamaleswaran R. (2020) Using Machine Learning to Predict Early Onset Acute Organ Failure in Critically Ill Intensive Care Unit Patients With Sickle Cell Disease: Retrospective Study. Journal of Medical Internet Research

Shaban-Nejad, A., Michalowski, M., Peek, N., Brownstein, J. C., Buckeridge, D. L. (in press). Seven Pillars of Precision Digital Health and Medicine. Artificial Intelligence in Medicine. https://www.sciencedirect.com/science/article/pii/S093336571931231X?via%3Dihub.

Shaban-Nejad, A., Brenas, J. H. (2020). Health Intervention Evaluation Using Semantic Explainability and Causal Reasoning. IEEE ACCESS. https://ieeexplore.ieee.org/document/8952710.

2019

Khojandi A, Van Wyk F, Begoli E, Davis RL, Kamaleswaran R A Minimal Set of Physiomarkers in High Frequency Real-Time Physiological Data Streams Predict Adult Sepsis Onset Earlier Than Clinical Practice International Journal of Medical Informatics, 2019 Feb; 122:55-62

Akbilgic O, Homayouni R, Heindrich K, Langham M, Davis RL. Unstructured text improves Prediction of death after surgery in children. Informatics. 2019; 6(1):4.

Hu Z, Tylavsky F, Han J, Kocak M, Fowke J, Davis R, LeWinn K, Bush N, Zhao Q  Maternal Metabolic Factors during Pregnancy Predict Early Childhood Growth Trajectories and Obesity Risk: the CANDLE Study" International Journal of Obesity, 2019 Jan 31. doi: 10.1038/s41366-019-0326-z.

Zahr R, Rampersaud E, Kang G, Weiss M, Wu G, Davis RL, Hankins J, Estepp J, Lebensburger J. Children with sickle cell anemia and APOL1 genetic variants develop albuminuria early in life, Blood, 2018 132:2377

Akbilgic O, Davis R. The Promise of Machine Learning: When Will It Be Delivered? J Card Fail, 2019 June; 25(6):484-485.

Hamad R, Batra A, Karasek D, LeWinn KZ, Bush NR, Davis RL, Tylavsky FA. The Impact of the Revised WIC Food Package on Maternal Nutrition during Pregnancy and Postpartum Am J Epidemiol, 2019 May; pii: kwz098. doi: 10.1093

Mohammed A, Cui Y, Mas V, Kamaleswaran R. (2019) Differential gene expression analysis reveals novel genes and pathways in pediatric septic shock patients. Scientific Reports (Nature Publishing Group)

Shin, E. K., Kwon, Y., Shaban-Nejad, A. (2019). Geo-clustered chronic affinity: pathways from socio-economic disadvantages to health disparities. JAMIA Open, 2(3), 317-322. http://dx.doi.org/10.1093/jamiaopen/ooz029.

Brenas, J. H., Shin, E. K., Shaban-Nejad, A. (2019). A Hybrid Recommender System to Guide Assessment and Surveillance of Adverse Childhood Experiences. Studies in health technology and informatics, 262, 332-335. http://ebooks.iospress.nl/publication/51748. PMID: 31349335

Shin, E. K., Shaban-Nejad, A. (2019). Applied Network Science for Relational Chronic Disease Surveillance. Studies in health technology and informatics, 262, 336-339. http://ebooks.iospress.nl/publication/51749. PMID: 31349336

Brenas, J. H., Shin, E. K., Shaban-Nejad, A. (2019). A Semantic Platform for Surveillance of Adverse Childhood Experiences. Online Journal of Public Health Informatics, 11(1). http://dx.doi.org/10.5210/ojphi.v11i1.9694. PMCID: PMC6606087

Shin, E. K., Kwon, Y., Shaban-Nejad, A. (2019). Multimorbidity Network Surveillance: Chronic Disease Clusters and Social Disparities. Online Journal of Public Health Informatics, 11(1). http://dx.doi.org/10.5210/ojphi.v11i1.9801. PMCID: PMC6606304

Brenas, J. H., Shin, E. K., Shaban-Nejad, A. (2019). Adverse Childhood Experiences Ontology for Mental Health Surveillance, Research, and Evaluation: Advanced Knowledge Representation and Semantic Web Techniques. JMIR mental health, 6(5), e13498. https://mental.jmir.org/2019/5/e13498/. PMID: 31115344

Shin, E. K., LeWinn, K., Bush, N., Tylavsky, F. A., Davis, R. L., Shaban-Nejad, A. (2019). Association of Maternal Social Relationships With Cognitive Development in Early Childhood. JAMA network open, 2(1), e186963. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2720588. PMID: 30646208, PMCID: PMC6484556

Brenas, J. H., Shin, E. K., Shaban-Nejad, A. (2019). An Ontological Framework to Improve Surveillance of Adverse Childhood Experiences (ACEs). Studies in health technology and informatics, 258, 31-35. http://ebooks.iospress.nl/publication/51346. PMID: 30942708

Precision Health and Medicine: A Digital Revolution in Healthcare. In Shaban-Nejad, A., Michalowski, M. (Eds.), Studies in Computational Intelligence (vol. 843, pp. XIX - 197). Springer - Nature. https://www.springer.com/gp/book/9783030244088.

Shaban-Nejad, A., Michalowski, M. (2019). From Precision Medicine to Precision Health: A Full Angle from Diagnosis to Treatment and Prevention. Precision Health and Medicine (pp. 1-7). Springer International Publishing. http://dx.doi.org/10.1007/978-3-030-24409-5_1

Shaban-Nejad, A., Kamaleswaran, R., Shin, E. K., Akbilgic, O. (2019). Health Intelligence. Biomedical Information Technology (2nd Edition ed., pp. 197-215). Elsevier. https://www.sciencedirect.com/science/article/pii/B9780128160343000067

2018
  1. Gatwood J, Davis RL, Kovesdy C Evidence of chronic kidney disease in veterans with incident diabetes mellitus. PLOS One (2018 Feb)
  2. White KD, Ab R, Ardern-Jones M, Beachkofsky T et al. SJS/TEN 2017: Building Multidisciplinary Networks to Drive Science and Translation J Allergy Clin Immunol Pract. 2018 Jan - Feb;6(1):38-69
  3. Christensen ML, Davis RL Identifying the “Blip on the Radar Screen”: Leveraging Big Data in Defining Drug Safety and Efficacy in Pediatric Practice J Clin Pharmacol (2018 Sept; 58 (s10))
  4. Kamaleswaran R, Shah S, Davis RL, Akbilgic O, Hallman M, West N Applying Artificial Intelligence to Identify Physiomarkers Predicting Severe Sepsis in the Pediatric Intensive Care Unit. Pediatr Crit Care Med (2018 Oct;19(10):e495-e503)
  5. Gatwood JB, Chishold-Burns MA, Davis RL, Thomas F, Potuku P, Hung A, Kovesdy CP Differences in Health Outcomes associated with Initial Adherence to Oral Antidiabetic Medications among Veterans with Uncomplicated Type 2 Diabetes: A Five-Year Survival Analysis Diabet Med 35,15711579(2018).
  6. Jose R, Rooney RJ, Nagisetty R, Davis RL, Hains DS Biorepository and Integrative Genomics Initiative: Designing and implementing a preliminary platform for predictive, preventive and personalized medicine at a pediatric hospital in a historically disadvantaged community in the United States EPMA J (2018 Sept; 9(3):225-234)
  7. Reidy K, Hjorten R, Simpson CL, Rosenberg AZ, Rosenblum SD, Kovesdy CP, Tylavsky FA, Myrie J, Ruiz BL, Mozhui K, Haque S, Suzuki M, Jacob J, Reznik SE, Kaskel FJ, Kopp JB, Winkler CA, Davis RL. Fetal and Maternal APOL1 Genotype in Preeclampsia. Am J Hum Genet, 2018 Aug.
  8. Shin E, LeWinn K, Bush N, Tylavsky FA, Davis R, Shaban-Nejad A Sociomarkers and Biomarkers: Predictive Modeling in Identifying Pediatric Asthma Patients at Risk of Hospital Revisits. NPJ Digital Med (2018 Oct; 1:50)
  9. Rigdon J, Rovnaghi CR, Qin F, Tembulkar S, Bush N, LeWinn K, Tylavsky FA, Davis RL, Barr BA,
  10. Gotlib IH, Anand KJS. Measuring socioeconomic adversity in early life. Acta Paediatrica (2019 Jan; 108(7).
  11. van Wyk F, Khojandi A, Williams B, MacMillan D, Davis RL, Jacobson D, Kamaleswaran R. A Cost-Benefit Analysis of Automated Physiological Data Acquisition Systems Using Data-Driven Modeling. Journal of Healthcare Informatics Research (2019 June; 3 (2):245-263)
  12. Mahajaran R, Shin EK, Shaban-Nejad A, Langham MR, Martin MY, Davis RL and Akbilgic O Disparities in Population-Level Socioconomic Factors re Associated with Disparities in Preoperative Clinical Risk Factors in Children Decision Support Systems and Education doi: 10.3233/978-1-61499-921-8-80
  13. Gatwood K. Chisholm-Burns M, Davis R, Thomas F, Potukuchi P, Hung A, Kovesdy C. Impact of Pharmacy Services on Initial Clinical Outcomes and Medication Adherence among Veterans with Uncontrolled Diabetes. BMC Health Serv Res (2018 Nov; 18: 855)
  14. Shin EK, Tylavsky F, Bush N, LeWinn K, Davis RL, Shaban-Nejad A. Association of Social Network Exposure with Cognitive Development in Early Childhood. JAMA Network Open, 2019;2(1):e186963. doi:10.1001/jamanetworkopen.2018.6963
  15. Zahr R, Rampersaud E, Kang G, Weiss M, Wu G, Davis RL, Hankins J, Estepp J, Lebensburger J. Children with sickle cell anemia and APOL1 genetic variants develop albuminuria early in life, Blood, 2018 132:2377
  16. Wyko FV, Khojandi A, Mohammed A, Begoli E, Davis RL, Maslove D, Kamaleswaran R. (2018) Physiomarkers in High-Frequency Real-Time Physiological Data Streams Predict Adult Sepsis Onset Earlier. International Journal of Medical Informatics122.
  17. Puniya, BL, Todd RG, Mohammed A, Brown DM, Barberis, M and Helikar T. (2018) A mechanistic computational model reveals that plasticity of CD4+ T cell differentiation is a function of cytokine composition and dosage Frontiers in physiology
  18. Mohammed A, Biegert G, Adamec J, Helikar T. (2018) CancerDiscover: An integrated pipeline for cancer biomarker and cancer class prediction from high-throughput sequencing data Oncotarget 9:2565-2573.
  19. Mahajan, R., Shin, E. K., Shaban-Nejad, A., Langham, M. R., Martin, M. Y., Davis, R. L., Akbilgic, O. (2018). Disparities in Population-Level Socio-Economic Factors Are Associated with Disparities in Preoperative Clinical Risk Factors in Children. Studies in Health Technology and Informatics, 255, 80-84. http://ebooks.iospress.nl/publication/50477. PMID: 30942708
  20. Brenas, J. H., Strecker, M., Echahed, R., Shaban-Nejad, A. (2018). Applied Graph Transformation and Verification With Use Cases in Malaria Surveillance. IEEE ACCESS, 6, 64728-64741. https://ieeexplore.ieee.org/document/8513828.
  21. Shin, E. K., Mahajan, R., Akbilgic, O., Shaban-Nejad, A. (2018). Sociomarkers and biomarkers: predictive modeling in identifying pediatric asthma patients at risk of hospital revisits. NPJ digital medicine, 1, 50. https://www.nature.com/articles/s41746-018-0056-y. PMID: 31304329, PMCID: PMC6550159
  22. Shin, E. K., Shaban-Nejad, A. (2018). Urban Decay and Pediatric Asthma Prevalence in Memphis, Tennessee: Urban Data Integration for Efficient Population Health Surveillance. IEEE Access, 6, 46281-46289. https://ieeexplore.ieee.org/document/8439928.
  23. Al Manir, M. S., Brenas, J. H., Baker, C. J., Shaban-Nejad, A. (2018). A Surveillance Infrastructure for Malaria Analytics: Provisioning Data Access and Preservation of Interoperability. JMIR public health and surveillance, 4(2), e10218. https://publichealth.jmir.org/2018/2/e10218/. PMID: 29907554, PMCID: PMC6026300
  24. Brenas, J. H., Al Manir, S., Zinszer, K., Baker, C. J.O., Shaban-Nejad, A. (2018). A Semantic Framework to Improve Interoperability of Malaria Surveillance Systems. Online Journal of Public Health Informatics, 10(1), e90. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6087909/. PMCID: PMC6087909
  25. Brenas, J. H., Al Manir, M. S., Zinszer, K., Baker CJO, Shaban-Nejad, A. (2018). Exploring Semantic Data Federation to Enable Malaria Surveillance Queries. Studies in health technology and informatics, 247, 6-10. http://ebooks.iospress.nl/publication/48743. PMID: 29677912
  26. Shin, E. K., Shaban-Nejad, A. (2018). Geo-Distinctive Comorbidity Networks of Pediatric Asthma. Studies in health technology and informatics, 247, 436-440. http://ebooks.iospress.nl/publication/48829. PMID: 29677998

Last Published: Sep 1, 2020