Vu, G.T., Chandra, A., Salvi, S., King, C., Gurupur, V. (2026). Predicting Delayed Dental Care Using Machine Learning: A National Health Interview Survey Analysis, International Dental Journal, Vol. 76(2), 10947. DOI: 10.1016/j.identj.2026.109407. Journal Impact Factor: 3.7.

Gurupur, V., Hooshmand, S., Prabhu, D.F., Trader, E., Salvi, S. (2025). Incompleteness of Electronic Health Records: An Impending Process Problem within Healthcare, Healthcare, 2900, DOI: 10.3390/healthcare13222900. Journal Impact Factor: 2.7.

Mayya, V., Vu, G.T., Mandhidi, B., King, C., Gurupur, V., Little, B.B., Singhal, A. (2025). EAT: Explainable Attentive Transformers for Identifying the Factors Influencing Dental Visits to Enhance Dental Data Completeness, BMC Oral Health, DOI: 10.1186/s12903-025-07170-0. Journal Impact Factor: 3.1.

Vu, G.T., Mayya, V., Mandhidi, B., King, C., Little, B.B., Gurupur, V., Singhal, A. (2025). Application of Machine Learning to Predict Periodontal Disease in US Adults: A Cross-Sectional Analysis of NHANES 2009–2014, Health Informatics Journal, Vol. 31(4), pp.1–21, DOI: 0.1177/14604582251394617. Journal Impact Factor: 2.3.

Prabhu, D.F., Gurupur, V., Stone, A., Trader, E. (2025). Integrating Artificial Intelligence, Electronic Health Records, and Wearables for Predictive, Patient-Centered Decision Support in Healthcare, Healthcare, Vol. 13(21), 2753, DOI: 10.3390/healthcare13212753. Journal Impact Factor: 2.7.

Salvi, S., Vu, G., Gurupur, V., King, C., (2025). Classifying Tooth Loss and Assessing Risk Factors in US Adults: A Machine Learning Analysis of BRFSS 2022 Data, Electronics, Vol. 14(17), 3559, DOI: 10.3390/electronics14173559. Journal Impact Factor: 2.6.

Salvi, S., Garg, L., Gurupur, V. (2025). Stage-Wise IoT Solutions for Alzheimer’s Disease: A Systematic Review of Detection, Monitoring, and Assistive Technologies, Sensors, Vol. 25 (17), pp. J5252. DOI: 10.3390/s25175252, Journal Impact Factor: 3.5.

Salvi, S., Vu, G., Gurupur, V., King, C., (2025). Digital Convergence in Dental Informatics: A Structured Narrative Review of Artificial Intelligence, Internet of Things, Digital Twins, and Large Language Models with Security, Privacy, and Ethical Perspectives, Electronics, 14(16), 3278; DOI:10.3390/electronics14163278. Journal Impact Factor: 2.6.

Trader, E., Gurupur, V. (2025). Real-Time Tracking of Diagnostic Discrepancies in Electronic Health Records for Improved Predictive Modeling, IEEE Access, DOI: 10.1109/ACCESS.2025.3573931. Journal Impact Factor: 3.4.

Sikka, V., Saifman, S., King, C., Klinker, S., Mont, T., & Castiglioni, A. (2024). Integrating tele-urgent care in undergraduate medical education: a partnership between the US Department of Veterans Affairs and academia. Education for Health, 37(3), 218-224.

Shang, D., Williams, C., Vu, G., *Joshi, A. (2024).  Teeth, Health, and Mind: Understanding the Interplay of Social Determinants and Cognitive Decline in Older Adults. Journal of Applied Gerontology. (Impact Factor: 2.144. Official journal of the Southern Gerontological Society)

Vu, G.T., King, C. (2024). Food insecurity and periodontitis in US adults. Community Dental Health. (Impact Factor: 1.349. Official journal of the British Association for the Study of Community Dentistry and the European Association of Dental Public Health).

Shanbhag, S.*, Raju, S., Gurupur, V., Kamath, S.S., Kandala, R.N.V.P.S., Trader, E.A.*, Lal, S. (2024). Analyzing Data Incompleteness for MRI Data for Quality Enhancement, IEEE Access, DOI: 0.1109/ACCESS.2024.3511384. Journal Impact Factor: 3.4.

Gurupur, V., Vu, G.T., Mayya, V., King, C. (2024). The Need for Standards in Evaluating the Quality of Electronic Health Records and Dental Records: A Narrative Review, Big Data and Cognitive Computing, DOI: 10.3390/bdcc8120168. Journal Impact Factor: 3.7.

Mayya, V., King, C., Vu, G.T., Gurupur, V. (2024). Empirical Study of Feature Selection Methods in Regression for Large-Scale Healthcare Data: A Case Study on

Estimating Dental Expenditures, IEEE Access, Vol. 12, pp. 153564-153579, DOI: 10.1109/ACCESS.2024.3482192. Journal Impact Factor: 3.4.

Mayya, V., Kandala, R.N.V.P.S., Gurupur, V., King, C., Vu, G., Wan, T.T.H. (2024). Need for an Artificial Intelligence-based Diabetes Care Management System in India and the United States, Health Services Research & Managerial Epidemiology, Vol 11, 1-12, DOI:10.1177/23333928241275292 Journal Impact Factor: 1.5.

Warren, N.A., Maskin, N.L., Gurupur, V., Rector, D.A., Adelman, D., Howell, S., McAree, J., Dibble, R., Carlisano, C., Maconi, D.P., Schrotenboer, D., James, M., Marte, N., Carlisano, T., Toland, C., Chung, J., Cremers, S.L., Corbin, G.S. (2024). Engaging Stakeholders to Develop a Roadmap for Dry Eye and MGD PCORI-Funded Research, Patient Related Outcome Measures, 2024:15 143–186. DOI: 10.2147/PROM.S438290. Journal Impact Factor: 2.1.

Vu, G.T., Shakib, S., King, C., Gurupur, V., Little, B.B. (2023). Association between uncontrolled diabetes and periodontal disease in US adults: NHANES 2009-2014, Scientific Reports, DOI: 10.1038/s41598-023-43827-y. Journal Impact Factor: 3.8.

Gireesh, E., Gurupur, V. (2023). Informational entropy measures for evaluation of reliability of deep neural network results, Entropy, Vol. 25(4) 573. DOI: 3390/e25040573.

Decker, V., King, C., Cassisi, J., & Tofthagen, C. (2023). Usability and Acceptability of a Videoconference Program for the Treatment of Depression in Adults With Peripheral Neuropathy. CIN: Computers, Informatics, Nursing, 10-1097. DOI: 10.1097/CIN.0000000000001008

King, C., and Huang, X. (2023). Neighborhood Violence and Housing Instability: An Exploratory Study of Low-Income Women. Housing Studies. DOI: 10.1080/02673037.2022.2074970

Gurupur, V., Hooshmand, S., Abedin, P., Shelleh, M. (2022). Analyzing the Data Completeness of Patients’ Records Using a Random Variable Approach to Predict the Incompleteness of Electronic Health Records, Applied Sciences, DOI: 2076-3417/12/21/10746.

Gurupur, V. (2022). Can the theories of information and communication channels be used to explain the complexities associated with transformation of data into information, and information to knowledge? Journal of Integrated Design and Process Science, DOI: 10.3233/JID-220010.

Gireesh, E. D., Skinner, H., Seo, J.H., Chen, P-C., Lee, K., Gurupur, V. (2022). Deep neural networks and gradient-weighted class activation mapping to classify and analyse EEG, Intelligent Decision Technologies, Vol. 17(1), pp. 43-53.

Gurupur, V. (2022). Key Observations in terms of Management of Electronic Health Records from a mHealth Perspective, mHealth, DOI: 10.21037/mhealth-21-39.

Li, Y, Li, D. and King, C. (2022). Food Insufficiency among Job-Loss Households during the Pandemic: The Role of Food Assistance Programs. Sustainability, 14(22), 15433. doi.org/10.3390/su142215433

Sikka, V., King, C., Klinker, S., Mont, T., Sommers-Olson, B., Hunt, B. E., Davis, S., and Fonseca, J. (2022). Telemedicine for Veterans in the Setting of the COVID-19 Pandemic: Lessons Learned from a Virtual Urgent Care. Journal of Telemedicine and Telecare. doi.org/10.1177/1357633X211069018

Bernhardt, C., and King, C. (2022). Neighborhood disadvantage and prescription drug misuse in low-income urban mothers. Drug and Alcohol Dependence, 231, 109245. doi.org/10.1016/j.drugalcdep.2021.109245

King, C., Huang, X., and Dewan, N. (2022) Continuity and change in neighborhood disadvantage and adolescent depression and anxiety. Health & Place, 73, 102724. doi.org/10.1016/j.healthplace.2021.102724

King, C., and Mancao, H., J. (2022). Special Supplemental Nutrition Program for Women, Infants, and Children Participation and Unmet Health Care Needs among Young Children. Child: Care, Health and Development. doi.org/10.1111/cch.12959

Bernhardt, C., and King, C. (2022). Telehealth and food insecurity screenings: challenges and lessons learned. mHealth, 8, 10. doi:10.21037/mhealth-21-31

Ramirez Garcia, N., Garcia Sierra, A., M., King, C., Valbuena, A., M., Urina-Triana, M., Quintero Baiz, A. & Acuña, A. (2022). Regional variability of glycemic control among adults with diabetes mellitus in Colombia. Public Health of Mexico, 64(2), 233-235. doi.org/10.21149/13053

Bernhardt, C., Hou, S-I, King, C., and Miller, A. (2022). Identifying barriers to effective patient-provider communication about food insecurity screenings in outpatient clinical settings in Central Florida: A mixed-methods study. Journal of Public Health Management and Practice, 28(2), E595-E602. doi.org/10.1097/PHH.0000000000001449

Gurupur, V., Miao, Z. (2021). A Brief Analysis of Challenges in implementing Telehealth in a Rural Setting, mHealth, DOI: 21037/mhealth-21-38.

Kulkarni, S.A., Gurupur, V., King, C., Koval, A. (2021). Impact of Gaussian Noise for Optimized Support Vector Machine Algorithm Applied to Medicare Payment on Raspberry Pi, Informatica, Vol. 12(2), pp. 57 – 75.

Gurupur, V., Shelleh, M.(2021). Machine Learning Analysis for Data Incompleteness (MADI): Analyzing the Data Completeness of Patient Records Using a Random Variable Approach to Predict the Incompleteness of Electronic Health Records, IEEE Access, Vol. 9, pp. 95994-96001. DOI: 1109/ACCESS.2021.3095240.

Gurupur, V. (2021). A Review on Advances in Design and Development of Complex Adaptive Systems for Healthcare Using Concept Maps, Health Technology, 5(2021), pp. 1-6. DOI: 10.21037/ht-21-12.

Wan, T.T.H., Gurupur, V., Wang, B.L., Mathews, S. (2021). A Patient-Centric Care Approach to Facilitate the Design of an Artificial Intelligence Application in Geriatric Care Management of Heart Failure Readmissions, Biomedical Research and Clinical Reviews, DOI: 10.31579/2692-9406/056.

Kulkarni, S.A., Pannu, J.S.*, Koval, A.V., Merrin, G.J., Gurupur, V., Nasir, A., King, C., Wan, T.T.H. (2021). A Brief Analysis of Key Machine Learning Methods for Predicting Medicare Payments Related to Physical Therapy Practices in the United States, Information, Vol 12(2), 57. https://doi.org/10.3390/info12020057.

Wan, T.T.H., Gurupur, V. (2020). Understanding the Difference between Healthcare Informatics and Healthcare Data Analytics in the Present State of Health Care Management, Health Services Research & Managerial Epidemiology, 7, pp. 1-3.

Gurupur, V., Wan, T.T.H. (2020). Inherent Bias in Artificial Intelligence-Based Decision Support Systems for Healthcare, Medicina, 2020 56(3), 141.

McAtee, J. R., Tao, M. H., King, C., & Chai, W. (2020). Association of Home Food Availability with Prediabetes and Diabetes among Adults in the United States. Nutrients, 12(5), 1209. doi.org/10.3390/nu12051209

King, C. and Liu, X. (2020). Racial and Ethnic Disparities in Opioid Use among US Adults with Back Pain. Spine, 45(15), 1062-1066. DOI: 10.1097/BRS.0000000000003466

King, C., and Khanijahani, A. (2020). Unmet Health Care Needs among Children of Mothers Exposed to Violence. Child Abuse & Neglect. doi.org/10.1016/j.chiabu.2020.104363

Asha C.S., Lal, S., Gurupur, V., Saxena, P.U. (2019). Multimodal Medical Image Fusion with Adaptive Weighted Combination of NSST Bands using Chaotic Grey Wolf Optimization, IEEE Access, DOI: 10.1109/ACCESS.2019.2908076.

Srinivasagopalan, S., Barry, J., Gurupur, V., Thankachan, S.V. (2019). A Deep Learning Approach for Diagnosing Schizophrenic Patients, Journal of Experimental & Theoretical Artificial Intelligence, DOI: 1080/0952813X.2018.1563636.

Raffenaud, A., Gurupur, V., Fernandes, S.L., Yeung, T. (2019). Utilizing Telemedicine in Oncology Settings: Patient Favourability Rates and Perceptions of use Analysis Using Chi-Square and Neural Networks, Technology and Health Care, DOI: 3233/THC-181293.

Steis, M., Unruh, L., Gurupur, V., Shettian, E., Rowe, M., Golden, A. (2019). Family caregivers faced with new acute symptoms: What to do?, American Journal of Nursing, Vol. 119(3), pp. 22-29.

Wan, T.T.H., Gurupur, V., Patel, A. (2019). A Longitudinal Analysis of Total Pain Scores for a Panel of Patients Treated by Pain Clinics, Health Services Research & Managerial Epidemiology, Vol. 6:1-7, DOI: 10.1177/2333392818788420.

McAtee, J., King, C., and Chai, W. (2019). Food Insecurity is Inversely Associated with Healthy Food Availability among Adults in the United States. Diabesity, 5(1), 17-22. DOI:10.15562/diabesity.2019.XX17

Gurupur, V., Kulkarni, S.A., Liu, X., Desai, U., Nasir, A*. (2018). Analysing the Power of Deep Learning Techniques Over the Traditional Methods Using Medicare Utilization and Provider Data, Journal of Experimental & Theoretical Artificial Intelligence, 31(1), pp. 99 -115.

Trader, E., Jayaraman, A., Luong, T., Gurupur, V. (2024). Legal AI for Tracking of Diagnostic Discrepancy Data for Predictive Modeling, Proceedings of SDPS 2024 Conference, October 6-9, 2024, Bologna, Italy, In Press.

Trader, E., Joshi, A., Gurupur, V., Vu, G. (2024). Facial Tilt Detection and Correction in Panoramic X-rays Using Depth Maps from 2D Stereo Images: A Novel Approach to Minimize Positioning Errors in Dental Imaging, Proceedings of the 10th International Conference on Biomedical Engineering & Sciences, July 22 – 25, 2024, Las Vegas, NV, In Press.

Trader, E., Joshi, A., Gurupur, V. (2024). Landmark Facial Feature Detection to Reduce Positioning Error in Panoramic X-Rays, Proceedings of the 24th Annual IEEE International Conference on Electro Information Technology (eit2024), May 30 – June 1, 2024, Eau Claire, Wisconsin.

Trader, E., Gurupur, V. (2024). Real-Time Tracking of Misdiagnosis in Electronic

Health Records for Improved Predictive Modeling, Proceedings of the IEEE SoutheastCon 2024, March 21 – 24, 2024, Atlanta, GA. DOI: 10.1109/SoutheastCon52093.2024.10500025.

Gurupur, V., Shelleh, M., Leone, C., Schupp-Omid, D., Azevedo, R., Dubey, S. (2023). THNN – A Neural Network Model for Telehealth Data Incompleteness Prediction, Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’23), July 24 – 28, 2023, Sydney, Australia. DOI: 10.1109/EMBC40787.2023.10340989.

Gurupur, V., Shelleh, M., Leone, C., Schupp-Omid, D., Azevedo, R., Dubey, S. (2023). THNN – A Neural Network Model for Telehealth Data Incompleteness Prediction, Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’23), July 24 – 28, 2023, Sydney, Australia. In Press

Shelleh, M., and Gurupur, V. (2022). PC-LSTM: Ontology-based Long Short-Term Memory State Model for Data Incompleteness Prediction, Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’22), July 11 – 15, 2022, Glasgow, UK.

Kulkarni, S.A., Gurupur, V., King. C. (2022). Impact Analysis of Stacked Machine Learning Algorithms Based Feature Selections for Deep Learning Algorithm Applied to Regression Analysis, Proceedings of the IEEE Southeast Conference 2022, March 31 – April 3, Mobile, AL.

Kulkarni, S. A., Gurupur, V., and King, C. (2021). Time Series Data Modelling of COVID-19 Positive Data applying popular Ensemble and Deep Learning Algorithm, 43rd IEEE International Conference of Engineering in Medicine and Biology Society (EMBC), November 1-5, 2021, EMBS Virtual Conference, USA

Renduchintala, C., Gurupur, V., Wan, T.T.H. (2020). Data Architecture for Motivation Measurement in a Game-based Rehabilitation System, Proceedings of the IEEE Southeast Conference 2020, March 12 -15, Raleigh, NC.

Kulkarni, S.A., Gurupur, V. (2019). A Case study for Comparing the Difference Between Logistic Regression and K-Nearest Neighbour Using Raspberry Pi for the Purpose of Machine Learning, Proceedings of SDPS 2019 Conference, July 28 – August 1, 2019, Taichung, Taiwan.

Nasir, A., Gurupur, V., Mumtaz, S.U., (2020). Method and System for Managing Chronic Illness Health Care Records, US 11,887,707 B2, Date Awarded: January 30, 2024.

Wan, T.T.H., Gurupur, V., (2021). Identifying the Significance of Patient-Centric Factors Leading to Risk Reduction for Hospital Readmission of Heart Failure, Patent No: US 11,017,903 B2, Date Awarded: May 25, 2021

Gurupur, V., Nasir, A., Liu, X., (2020). Method and system for managing health care patient record data, US 10,790,049 B2, Date Awarded: September 29, 2020.