Skip to content
ApplyGive

Other ways to search: Events Calendar | UTHSC News

Publications

2022
Chad A. Melton, Brianna M. White, Robert L. Davis, Robert A. Bednarczyk, and Arash Shaban-
Nejad. “Fine-Tuned Sentiment Analysis of COVID-19 Vaccines: A Comparative Study of Twitter and
Reddit Social Media Platforms”. Submitted to LANCET eClinicalMedicine. (Under Review)
 
David L. Schwartz, Altha Stewart, Laura Harris, Esra Ozdenerol, Fridtjof Thomas, Karen C. Johnson, Robert Davis, and Arash Shaban-Nejad. “The Memphis Pandemic Health Informatics System (MEMPHI-SYS) — Creating a Metropolitan COVID-19 Data Registry Linked Directly to Community Testing to Enhance Population Health Surveillance”. Submitted to Disaster Medicine and Public Health Preparedness – Cambridge University Press. (Under Review)
 
David L. Schwartz, Neil Hayes, Robert L. Davis, Arash Shaban-Nejad. “Independent Predictors for Hospitalization-Associated Radiotherapy Interruptions”. Submitted to Advances in Radiation Oncology.(Under Review)
 
Elizabeth Gaudio, Nariman Ammar, Fatma Gunturkun, Cem Akkus, Whitney S. Brakefield, DanielWakefield, Maria Pisu, Robert L Davis, Arash Shaban-Nejad, David L. Schwartz. “Defining Radiation Treatment Interruption Rates in the COVID-19 Era—Findings from an Academic Center in an Underserved Urban Setting”. Submitted to International Journal of Radiation Oncology, Biology, Physics – Elsevier. (Under Review)
 
Whitney S. Brakefield, Nariman Ammar, and Arash Shaban-Nejad. " An Urban Population Health Observatory for Disease Causal Pathway Analysis and Decision Support: The Underlying Explainable AI Model". to appear in JMIR Formative Research.
 
Olufunto A. Olusanya, Brianna White, Fauzia Malik, Kyra A. Hester, Robert L. Davis, Robert A. Bednarczyk, and Arash Shaban-Nejad. “Healthcare Professionals’ Perceptions and Recommendations regarding Adolescent Vaccinations in Georgia and Tennessee during the COVID-19 Pandemic: A Qualitative Research”. Submitted to PLOS One. (Under Review)
 
A Hubler, DV Wakefield, L Makepeace, M Carnell, AM Sharma, B Jiang, AP Dove, WB Garne, DEdmonston, JG Little, E Ozdenerol, RB Hanson, MY Martin, Arash Shaban-Nejad, M Pisu, and DL Schwartz. “Identifying Independent Predictors for Hospitalization-Associated Radiotherapy Interruptions”. Submitted to International Journal of Radiation Oncology, Biology, Physics - Elsevier.(Under Review)
 
Hyo Young Choi, Ilana Graetz, Arash Shaban-Nejad, Lee Schwartzberg, Gregory Vidal, Robert L Davis, Eun Kyong Shin. “Sociomarkers of Pain and Pain Intensity among Women Diagnosed with Early Stage Breast Cancer”. Frontiers in Oncology, 12:759272. doi: 10.3389/fonc.2022.759272.16. Eun Kyong Shin, Kaja LeWinn, Nicole Bush, Frances A Tylavsky, Robert Lowell Davis, and Arash Shaban-Nejad. “Association of Growing Up in Distressed Neighborhoods with Early Childhood Cognitive Performance”, Submitted to Frontiers in Public Health. (Under Revision & Resubmission).
 
Whitney S. Brakefield, Olufunto A. Olusanya, and Arash Shaban-Nejad. “A Machine-Learning Approach to Study Association between Neighborhood Factors and Adult Obesity in Shelby County, Tennessee”. Submitted to JMIR Public Health and Surveillance. (Under Revision & Resubmission)
 
Khalid Alghatani, Nariman Ammar, Abdelmounaam Rezgui, and Arash Shaban-Nejad. “Precision Clinical Medicine through Machine Learning: Using High and Low Quantile Ranges of Vital Signs for Risk Stratification of ICU Patients”. IEEE ACCESS, 16 May 2022. (13 pages) Doi: 10.1109/ACCESS.2022.3175304.
 
Grace McCarthy, Sarah Shore, Esra Ozdenerol, Altha Stewart, Arash Shaban-Nejad, and David L Schwartz. “History Repeating—How Pandemics Collide with Health Disparities in the United States”. To appear in Journal of Racial and Ethnic Health Disparities, June 2022.
 
Olufunto A. Olusanya, Brianna White, Chad Melton, and Arash Shaban-Nejad. “Examining the Implementation of Digital Health to Strengthen COVID-19 Pandemic Response and Recovery and Page 20 of 37 Scale up Equitable Vaccine Access in African Countries”. Journal of Medical Internet Research (JMIR)– Formative Research. 2022;6(5):e34363. doi:10.2196/34363, PMID: 35512271.
 
Anna M Cushing, Masrur A Khan, Lynn Kysh, Whitney S Brakefield, Nariman Ammar, Danica B Liberman, John Wilson, Arash Shaban-Nejad, Juan Espinoza. “Geospatial Data in Pediatric Asthma: A Scoping Review Protocol.” To appear in JBI Evidence Synthesis. 2022.
 
Whitney S. Brakefield, Olufunto A. Olusanya, Brianna White, Nariman Ammar, Arash Shaban-Nejad. “Social Determinants and Indicators of COVID-19: A Literature Review and Call to Action”. To appearin Disaster Medicine and Public Health Preparedness – Cambridge University Press. April 2022.
 
Hunter Hamilton, Alina Nico West, Nariman Ammar, Lokesh Chinthala, Fatma Gunturkun, Tamekia Jones, Arash Shaban-Nejad, and Samir H Shah. “Analyzing Relationships Between Economic and Neighborhood-Related Social Determinants of Health and Intensive Care Unit Length of Stay for Critically Ill Children with Medical Complexity Presenting with Severe Sepsis”. Frontiers in Public Health, 29 April 2022 doi: 10.3389/fpubh.2022.789999.
 
Karabayir I, Butler L, Goldman SM, Kamaleswaran R, Gunturkun F, Davis RL, Ross GW, Petrovitch H, Masaki K, Tanner CM, Tsivgoulis G, Alexandrov AV, Chinthala LK, Akbilgic O. Predicting Parkinson’s Disease and its Pathology via Simple Clinical Variables, J Parkinsons Dis, 2022;12(1):341-351. 
 
Choi HY, Graetz I, Shaban-Nejad A, Schwartzberg L, Vidal G, Davis RL, Shin EY Social Disparities of  Pain and Pain Intensity among Women Diagnosed with Early Stage Breast Cancer  Front. Oncol. 2022. 
 
Khojandi A, Liu Z, Li X, Davis RL, Kamaleswaran R A Machine Learning-Enabled Partially Observable Markov Decision Process Prediction Framework INFORMS J Comput, 2022. 
2021

Champlin G, Hwang S,Heitzer A,DingJ, Jacola L, Estepp J, Wang W, Ataga K, Owens C, Newman J, King A, Davis R, Kang G, Hankins J Progression of Central Nervous System Disease from Pediatric to Young Adulthood in Sickle Cell Anemia. Experimental Biology and Medicine, 2021; 246: 1-7.

Singhal L, Garg Y, Yang P, Tabaie A, Wong A, Mohammed A, Chinthala L, Sodhi A, Kadaria D, Holder A, Esper A, Blum J, Davis RL, Clifford G, Martin G, Kamaleswaran R. eARDS: A multi-center validation of an interpretable machine learning algorithm of early onset Acute Respiratory Distress Syndrome (ARDS) among critically ill adults with COVID-19 PLOS ONE, 2021; 16(9): e0257056. https://doi.org/10.1371/journal.pone.0257056

Smeltzer MP, Hodges TP, Whartenby J, Hankins JS, Davis RL, Cooper WO. Three Wishes for Sickle Cell Disease: Results from a multi-stakeholder vision-casting project in Tennessee. ClinHealthPromot, 2021. 

Alvarez, Marcus A., Kiyah Anderson, Jeremiah L. Deneve, Paxton V. Dickson, Danny Yakoub, Martin D. Fleming, Lokesh K. Chinthala, et al. “Traveling for Pancreatic Cancer Care Is Worth the Trip.” The American Surgeon 87, no. 4 (April 2021): 549–56. https://doi.org/10.1177/0003134820951484.

Chad Melton, Olufunto A Olusanya, Nariman Ammar, Arash Shaban-Nejad. “Public sentiment analysis and topic modeling regarding COVID-19 vaccines on the Reddit social media platform: A call to action for strengthening vaccine confidence”. J Infect Public Health. 2021 Aug 14: S1876-0341(21)00228-8. doi: 10.1016/j.jiph.2021.08.010. PMID: 34426095.

Arash Shaban-Nejad, Martin Michalowski, John S Brownstein, and David L. Buckeridge. “Explainable AI: Towards Fairness, Accountability, Transparency and Trust in Healthcare”, IEEE Journal of Biomedical and Health Informatics, 2021, pp. 2374-2375. doi:10.1109/JBHI.2021.3088832

Olufunto A Olusanya, Nariman Ammar, Robert L Davis, Robert A Bednarczyk and Arash Shaban-Nejad. “A Digital Personal Health Library for Enabling Precision Health Promotion to Prevent Human Papilloma Virus-Associated Cancers”. Front. Digit. Health 2021. doi: 10.3389/fdgth.2021.683161.

Whitney S Brakefield, Nariman Ammar, Olufunto Olusanya, and Arash Shaban-Nejad. " An Urban Population Health Observatory System to Support COVID-19 Pandemic Preparedness, Response, and Management: Design and Development Study". JMIR Public Health Surveillance. 2021 May 17. doi: 10.2196/28269. Online ahead of print.  PMID: 34081605.

Khalid Alghatani, Nariman Ammar, Abdelmounaam Rezgui, and ArashShaban-Nejad. “Predicting Intensive Care Unit Length of Stay and Mortality Using Patient Vital Signs: Machine Learning Model Development and Validation” JMIR Med Inform. 2021 May 5;9(5):e21347. doi: 10.2196/21347. PMID: 33949961.

Jon Brenas and Arash Shaban-Nejad. “Proving the correctness of Knowledge Graph Update: A Scenario from Surveillance of Adverse Childhood Experiences”. Front Big Data. 2021 May 3;4:660101. doi: 10.3389/fdata.2021.660101. PMID: 34013202; PMCID: PMC8126660.

Nariman Ammar, James E. Bailey, Robert L. Davis, and Arash Shaban-Nejad. “Using a Personal Health Library-Enabled mHealth Recommender System for Self-Management of Diabetes Among Underserved Populations: Use Case for Knowledge Graphs and Linked Data”. JMIR Form Res. 2021 Mar 16;5(3):e24738. doi: 10.2196/24738. PMID: 33724197.

Olufunto Olusanya, Robert A Bednarczyk, Robert L Davis and Arash Shaban-Nejad.  “Addressing Parental Vaccine Hesitancy and Other Barriers to Childhood/Adolescent Vaccination Uptake during the Coronavirus (COVID-19) Pandemic”. Front. Immunol. 2021, Mar 18;12:663074. doi: 10.3389/fimmu.2021.663074. PMID: 33815424; PMCID: PMC8012526.

Oguz Akbilgic, Eun Kyong Shin, Arash Shaban-Nejad. “A Data Science Approach to Analyze the Association of Socioeconomic and Environmental Conditions with Disparities in Pediatric Surgery”. Front. Pediatr. 2021, Mar 12;9:620848. doi: 10.3389/fped.2021.620848. PMID: 33777865; PMCID: PMC7994338.

Christopher J.O. Baker, Mohammad Sadnan Al Manir, Jon Hael Brenas, Kate Zinszer, Arash Shaban-Nejad. “Applied Ontologies for Global Health Surveillance and Pandemic Intelligence”, Journal of Washington Academy of Sciences 2021,106(4):67-80.

Arash Shaban-Nejad, Martin Michalowski, David L. Buckeridge (eds). “Explainable AI in Healthcare and Medicine: Building a Culture of Transparency and Accountability”, Studies in Computational Intelligence series, Springer, 2021. DOI:10.1007/978-3-030-53352-6.

Ammar N, Bailey J, Davis RL, AarshShaban-Nejad. “Implementation of a Personal Health Library (PHL) To Support Self-Management of Chronic Diseases”. in Explainable AI in Healthcare and Medicine. Studies in Computational Intelligence, Springer/ Nature, Switzerland AG, 2021. DOI: 10.1007/978-3-030-53352-6_20

AarshShaban-Nejad, Michalowski M, and Buckeridge DL. “Explainability and Interpretability: Keys to Deep Medicine”, in Explainable AI in Healthcare and Medicine. Studies in Computational Intelligence, Springer/ Nature, Switzerland AG, 2021. DOI: 10.1007/978-3-030-53352-6_1

Olufunto A. Olusanya, Nariman Ammar, Whitney S. Brakefield, Mabel Crescioni, Janet Chupka, Debran Tarver and Arash Shaban-Nejad. “HemPHL: A Personal Health Library and mHealth Recommender to Promote Self-Management of Hemophilia”. Stud Health Technol Inform. 2021 May 27;281:550-554. doi: 10.3233/SHTI210231. PMID: 34042636.

Nariman Ammar, Olufunto Olusanya, Chad Melton, Lokesh Chinthala, Xiaolei Huang, and Arash Shaban-Nejad. “From Personal Health Coaches to Digital Personal Health Librarians: HPV Vaccine Education and Promotion”. in Proc. of International Workshop on AI in Health: Transferring and Integrating Knowledge for Better Health (AIHEALTH-WWW-2021) workshop at Web Conference 2021, April 2021.

Nariman Ammar, Oshani Seneviratne, James E. Bailey, Robert L. Davis, Deborah McGuinness and Arash Shaban-Nejad. “The Personal Health Library: Taking EHR design to the Next Level”. The Personal Health Knowledge Graph (PHKG 2021) Workshop 2021. May 4, 2021, Virtual.

Kuscu C, Kiran M, Mohammed A, Kuscu C, Satpathy S, Wolen A, Bardhi E, Bajwa A, Eason JD, Maluf D, Mas V, Akalin E. (2021) Integrative analyses of circulating small RNAs and kidney graft transcriptome in transplant glomerulopathy. Int. J. Mol. Sci. 2021, 22(12), 6218; https://doi.org/10.3390/ijms22126218

Banerjee S, Mohammed A, Wang H, Palaniyar N, Kamaleswaran R. (2021) Machine Learning Identifies Complicated Sepsis Course and Subsequent Mortality Based on 20 Genes in Peripheral Blood Immune Cells at 24 H Post-ICU Admission, Frontiers in Immunology, 12:592303. doi: 10.3389/fimmu.2021.592303

Liu Z, Khojandi A, Mohammed A, Li X, Chinthala LK, Davis RL, Kamaleswaran R. (2021) HeMA: A Hierarchically Enriched Machine Learning Approach for Managing False Alarms in Real Time: A Sepsis Prediction Case Study, Computers in Biology and Medicine, 131:104255. doi: 10.1016/j.compbiomed.2021.104255

2020

Nariman Ammar, and Arash Shaban-Nejad. “Explainable Artificial Intelligence Recommendation System by Leveraging the Semantics of Adverse Childhood Experiences: Proof-of-Concept Prototype Development”. JMIR Med Inform. 2020 Nov 4;8(11):e18752.doi: 10.2196/18752. PMID: 33146623. [Named among the “Top Milestones on Explainable AI In 2020” by AIM Analytics Magazine, Dec 2020 issue]

Arash Shaban-Nejad, Martin Michalowski, Niels Peek, John S. Brownstein, and David L. Buckeridge. “Seven Pillars of Precision Digital Health and Medicine”. Journal of Artificial Intelligence in Medicine, 2020;103:101793. doi: 10.1016/j.artmed.2020.101793. PMID: 32143798.

Jon Hael Brenas, and Arash Shaban-Nejad. “Health Intervention Evaluation Using Semantic Explainability and Causal Reasoning”. IEEE ACCESS, Vol. 8, pp. 9942 - 9952.  doi: 10.1109/ACCESS.2020.2964802.

Arash Shaban-Nejad, and Martin Michalowski (eds.), “Precision Health and Medicine: A Digital Revolution in Healthcare”, Studies in Computational Intelligence Series, vol. 843- Springer Nature Switzerland AG. 2020. DOI: 10.1007/978-3-030-24409-5.

Arash Shaban-Nejad, and Martin Michalowski, “From Precision Medicine to Precision Health: A Full Angle from Diagnosis to Treatment and Prevention”, in Precision Health and Medicine. Studies in Computational Intelligence, vol 843, 00. 1-7. Springer, Cham, 2020. DOI: DOI: 10.1007/978-3-030-24409-5_1

Arash Shaban-Nejad, Oguz Akbilgic, Rishikesan Kamaleswaran, Eun Kyong Shin, “Health Intelligence” In David Dagan Feng (ed.) Biomedical Information Technology. 2nd Edition, Chapter 6, 2020, Pages 197-215. Elsevier. 2020. ISBN: 9780128160343.

Bang G, Barash G, Bea R, Cali J, Castillo-Effen M, Chen XC, Chhaya N, Cummings R, Dhoopar R, Dumanci S, Espinoza H, Farchi E, Fioretto F, Fuentetaja R, Geib C, Gundersen OE, Hernández-Orallo J, Huang X, Jaidka K, Keren S, Kim S, Galley M, Liu X, Lu T, Ma Z, Mallah R, McDermid J, Michalowski M, Mirsky R, hÉigeartaigh EO, Ramachandran D, Segovia-Aguas J, Shehory O, Arash Shaban-Nejad, Shwartz V, Srivastava S, Talamadupula K, Tang J, Van Hentenryck P, Zhang D, and Zhang J. “The Association for the Advancement of Artificial Intelligence 2020 Workshop Program”. AI Magazine, 41(4), 100-114. https://doi.org/10.1609/aimag.v41i4.7398. (2020).

Whitney S Brakefield, Nariman Ammar, Olufunto Olusanya, Esra Ozdenerol, Fridtjof Thomas, Altha J Stewart, Karen C Johnson, Robert Davis, David L Schwartz, and Arash Shaban-Nejad.  “Implementing an Urban Public Health Observatory for (Near) Real-Time Surveillance for the COVID-19 Pandemic”. Stud Health Technol Inform. 2020 Nov 23;275:22-26. doi: 10.3233/SHTI200687. PMID: 33227733. (Citation: 1)

Arash Shaban-Nejad, Jon Hael Brenas, Mohammad Sadnan Al Manir, Kate Zinszer, Christopher J.O. Baker.  “Semantic Web of Things (SWoT) for Global Infectious Disease Control and Prevention”. Studies in health technology and informatics. 2020 Jun 26; 272:425-428. doi:10.3233/SHTI200586. PMID: 32604693.

Nariman Ammar, Jim Bailey, Robert L. Davis, Arash Shaban-Nejad. “The Personal Health Library: A Single Point of Secure Access to Patient Digital Health”. Studies in health technology and informatics, 2020 Jun 16;270:448-452. doi: 10.3233/SHTI200200. PMID: 32570424.

Hamda Khan, Nariman Ammar, Jerlym Porter, Juan Ding, Jeremie H. Estepp, Jason R. Hodges, Arash Shaban-Nejad, Winfred C. Wang, James G. Gurney, Guolian Kang, Robert L Davis, Jane S. Hankins. “Food Deserts Are Associated with Acute Care Utilization Among Preschool Children with Sickle Cell Disease". Blood (2020) 136 (Supplement 1): 19. https://doi.org/10.1182/blood-2020-138802.

Olufunto Olusanya, Yusuf A., Tomar, A., Karaye I., Onoriode K., Wells J., Arash Shaban-Nejad, Wigfall, L. “Biobehavioral correlates of high-grade, precancerous cervical lesions and invasive cervical cancer among women living with HIV: A systematic review”. Presented at International Cancer Education Conference. Oct 2020.

Olufunto Olusanya, Thomas, J., Tomar, A., Alonge, O., Aarsh Shaban-Nejad, Wigfall, L. “Application of the Integrated Behavior Model to non-theory-based studies to identify determinants influencing catch-up HPV vaccination outcomes”. Presented at International Cancer Education Conference. Oct 2020.

Olufunto Olusanya, Thomas J., Olokunlade T., & Chikwendu C., Arash Shaban-Nejad. “A content analysis on alcohol-related messages disseminated to pregnant women by midwives in a southwestern state”.  American Public Health Association (APHA) 2020 Annual Meeting & Expo, San Francisco, Oct 24-28, 2020.

Mohammed A, Van Wyk F, Chinthala LK, Khojandi A, Davis RL, Coopersmith CM, Kamaleswaran R. (2020) Temporal Differential Expression of Physiomarkers Predicts Sepsis in Critically Ill Adults. Shock: Injury, Inflammation, and Sepsis: Laboratory and Clinical Approaches, DOI: 10.1097/SHK.0000000000001670.

Akbilgic O*, Kamaleswaran R*, Mohammed A*, Ross W, Masaki K, Petrovitch H, Tanner CM, Davis RL, Goldman SM. (2020) Electrocardiographic Changes Predate Parkinson's Disease Onset. Scientific Reports, 10:11319. https://doi.org/10.1038/s41598-020-68241-6

2019

Van Wyk F, Khojandi A, Mohammed A, Begoli E, Davis RL, Kamaleswaran R. (2019) A minimal set of physiomarkers in continuous high frequency data streams predict adult sepsis onset earlier. Int J Med Inform. 122:55-62. doi: 10.1016/j.ijmedinf.2018.12.002

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

Gatwood J, Davis RL, Kovesdy C Evidence of chronic kidney disease in veterans with incident diabetes mellitus. PLOS One (2018 Feb)

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

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))

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)

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 35,1571–1579(2018).

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)

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.

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)

Rigdon J, Rovnaghi CR, Qin F, Tembulkar S, Bush N, LeWinn K, Tylavsky FA, Davis RL, Barr BA,

Gotlib IH, Anand KJS. Measuring socioeconomic adversity in early life. Acta Paediatrica (2019 Jan; 108(7).

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)

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

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)

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

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

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.

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

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.

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

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.

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

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.

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

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

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

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

 

 

Nov 11, 2022