Peer Reviewed and Accepted Paper and Platform Presentations

2020

Peer Reviewed Papers:

  1. DeForte, S., Huang, Y., Bourgeois, T., Hussain, A., & Lin, S. (n.d.). The Association between App Administered Depression Assessments and Suicidal Ideation in the User Comments: An Observational Study (Preprint).
  2. DeForte, S., Sezgin, E., Huefner, J., Lucius, S., Luna, J., Satyapriya, A. A., & Malhotra, P. (2020). Usability of a Mobile App for Improving Literacy in Children With Hearing Impairment: Focus Group Study. JMIR Human Factors, 7(2), e16310.
  3. Gorham, T. J., Rust, S., Rust, L., Kuehn, S., Yang, J., Lin, J. S., Hoffman, J., Huang, Y., Lin, S., McClead, R., Brilli, R., Bode, R., & Maa, T. (2020). The Vitals Risk Index-Retrospective Performance Analysis of an Automated and Objective Pediatric Early Warning System. Pediatric Quality & Safety, 5(2), e271.
  4. Hammersmith, K. J., DePalo, J. R., Casamassimo, P. S., MacLean, J. K., & Peng, J. (2020). Silver Diamine Fluoride and Fluoride Varnish May Halt Interproximal Caries Progression in the Primary Dentition. The Journal of Clinical Pediatric Dentistry, 44(2), 79–83.
  5. Madden, A., Vajda, J., Llamocca, E. N., Campo, J. V., Gorham, T. J., Lin, S., & Fontanella, C. A. (2020). Factors associated with psychiatric readmission of children and adolescents in the U.S.: A systematic review of the literature. General Hospital Psychiatry, 65, 33–42.
  6. Miller, K., Hoyt, R., Rust, S., Doerschuk, R., Huang, Y., & Lin, S. M. (n.d.). The Financial Impact of Genetic Diseases in a Pediatric Accountable Care Organization.
  7. O’Donovan, R., Sezgin, E., Bambach, S., Butter, E., & Lin, S. (2020). Detecting Screams From Home Audio Recordings to Identify Tantrums: Exploratory Study Using Transfer Machine Learning. JMIR Formative Research, 4(6), e18279.
  8. Pope, C. N., Sezgin, E., Lin, S., Morris, N. L., & Zhu, M. (2020). Adolescents’ attitudes and intentions to use a smartphone app to promote safe driving. In Transportation Research Interdisciplinary Perspectives (Vol. 4, p. 100090).
  9. Sezgin, E., Militello, L., Huang, Y., & Lin, S. (n.d.). A Scoping Review of Patient-Facing, Behavioral Health Interventions with Voice Assistant Technology Targeting Self-management and Healthy Lifestyle Behaviors. In SSRN Electronic Journal.
  10. Sezgin, E., Noritz, G., Elek, A., Conkol, K., Rust, S., Bailey, M., Strouse, R., Chandawarkar, A., von Sadovszky, V., Lin, S., & Huang, Y. (2020). Capturing At-Home Health and Care Information for Children With Medical Complexity Using Voice Interactive Technologies: Multi-Stakeholder Viewpoint. Journal of Medical Internet Research, 22(2), e14202.
  11. Sezgin, E., Weiler, M., Weiler, A., Lin, S., & Hart, L. (2020). It Is a Life Journey: A Roadmap of Teens With Chronic Diseases in Transitioning to Independence. Journal of Pediatric Health Care: Official Publication of National Association of Pediatric Nurse Associates & Practitioners, 34(4), 346–355.
  12. Shen, J., Xiang, H., Luna, J., Grishchenko, A., Patterson, J., Strouse, R. V., Roland, M., Lundine, J. P., Koterba, C. H., Lever, K., Groner, J. I., Huang, Y., & Lin, E.-J. D. (2020). Designing a Virtual Reality-based Executive Function Rehabilitation System for Children with Traumatic Brain Injuries. JMIR Serious Games.
  13. Zeng, X., Feng, Y., Moosavinasab, S., Lin, D., Lin, S., & Liu, C. (2020). Multilevel Self-Attention Model and its Use on Medical Risk Prediction. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 25, 115–126.
  14. Yue, X., Wang, Z., Huang, J., Parthasarathy, S., Moosavinasab, S., Huang, Y., Lin, S. M., Zhang, W., Zhang, P., & Sun, H. (2020). Graph embedding on biomedical networks: methods, applications and evaluations. Bioinformatics , 36(4), 1241–1251.
  15. Ramtekkar, U., Bridge, J., Thomas, G., Butter, E., Reese, J., Logan, E., Lin, S., & Axelson, D. (2020). Pediatric Telebehavioral Health: A Transformational Shift in Care Delivery in the Era of COVID-19 (Preprint). In JMIR Mental Health.
  16. Ramtekkar, U., Bridge, J., Thomas, G., Butter, E., Reese, J., Logan, E., Lin, S., & Axelson, D. (2020). Pediatric Telebehavioral Health: A Transformational Shift in Care Delivery in the Era of COVID-19 (Preprint). In JMIR Mental Health.

2019

Peer Reviewed Papers:

  1. Attipoe, S., Huang, Y., Schweikhart, S., Rust, S., Hoffman, J., & Lin, S. (2019). Factors Associated With Electronic Health Record Usage Among Primary Care Physicians After Hours: Retrospective Cohort Study. JMIR Human Factors, 6(3), e13779.
  2. Dunn, A., Patterson, J., Biega, C. F., Grishchenko, A., Luna, J., Stanek, J. R., & Strouse, R. (2019). A Novel Clinician-Orchestrated Virtual Reality Platform for Distraction During Pediatric Intravenous Procedures in Children With Hemophilia: Randomized Controlled Trial. JMIR Serious Games, 7(1), e10902.
  3. Feng, Y., Lin, S., Lin, E.-J., Farley, L., Huang, Y., & Liu, C. (2019). Identifying Candidates for Medical Coding Audits: Demonstration of a Data Driven Approach to Improve Medicare Severity Diagnosis-Related Group Coding Compliance. In Health Information Science (pp. 47–57).
  4. Gasior, A. C., Reck, C., Lane, V., Wood, R. J., Patterson, J., Strouse, R., Lin, S., Cooper, J., Gregory Bates, D., & Levitt, M. A. (2019). Transcending Dimensions: a Comparative Analysis of Cloaca Imaging in Advancing the Surgeon’s Understanding of Complex Anatomy. Journal of Digital Imaging, 32(5), 761–765.
  5. Hu, Z., Sezgin, E., Lin, S., Zhang, P., Noh, H. Y., & Pan, S. (2019). Device-free Sleep Stage Recognition through Bed Frame Vibration Sensing. In Proceedings of the 1st ACM International Workshop on Device-Free Human Sensing - DFHS’19.
  6. Kamimura-Nishimura, K. I., Epstein, J. N., Froehlich, T. E., Peugh, J., Brinkman, W. B., Baum, R., Gardner, W., Langberg, J. M., Lichtenstein, P., Chen, D., & Kelleher, K. J. (2019). Factors Associated with Attention Deficit Hyperactivity Disorder Medication Use in Community Care Settings. The Journal of Pediatrics, 213, 155–162.e1.
  7. Khare, R., Utidjian, L. H., Razzaghi, H., Soucek, V., Burrows, E., Eckrich, D., Hoyt, R., Weinstein, H., Miller, M. W., Soler, D., Tucker, J., & Bailey, L. C. (2019). Design and Refinement of a Data Quality Assessment Workflow for a Large Pediatric Research Network. EGEMS (Washington, DC), 7(1), 36.
  8. Krebs, B., Sanderson, D., Moreland, P., Kavanaugh, J., Roeder, R., Hoyt, R., Wedel, K., Chovanec, T., Chen, D., Rust, S., & Auletta, J. J. (2019). Nationwide Children’s Hospital BMT Smart Forms. In Biology of Blood and Marrow Transplantation (Vol. 25, Issue 3, pp. S96–S97).
  9. Lin, E.-J. D., Hefner, J. L., Zeng, X., Moosavinasab, S., Huber, T., Klima, J., Liu, C., & Lin, S. M. (2019). A deep learning model for pediatric patient risk stratification. The American Journal of Managed Care, 25(10), e310–e315.
  10. Lundine, J. P., Peng, J., Chen, D., Lever, K., Wheeler, K., Groner, J. I., Shen, J., Lu, B., & Xiang, H. (2020). The impact of driving time on pediatric TBI follow-up visit attendance. Brain Injury: [BI], 34(2), 262–268.
  11. Mezoff, E. A., Minneci, P. C., Hoyt, R. R., & Hoffman, J. M. (2019). Toward an Electronic Health Record Leveraged to Learn from Every Complex Patient Encounter: Health Informatics Considerations with Pediatric Intestinal Rehabilitation as a Model. The Journal of Pediatrics, 215, 257–263.
  12. Nunley, S., Glynn, P., Rust, S., Vidaurre, J., Albert, D. V. F., & Patel, A. D. (2019). A hospital-based study on caregiver preferences on acute seizure rescue medications in pediatric patients with epilepsy: Intranasal midazolam versus rectal diazepam. In Epilepsy & Behavior (Vol. 92, pp. 53–56).
  13. Patel, A. D., Glynn, P., Falke, A. M., Reynolds, M., Hoyt, R., Hoynes, A., Moore-Clingenpeel, M., Salvator, A., & Moreland, J. J. (2019). Impact of a Make-A-Wish experience on healthcare utilization. Pediatric Research, 85(5), 634–638.
  14. Sezgin, E., & Lin, S. (2019). Technology-Based Interventions, Assessments, and Solutions for Safe Driving Training for Adolescents: Rapid Review. JMIR mHealth and uHealth, 7(1), e11942.
  15. Townsend, J. A., Peng, J., Miller, M., Yu, Q., Babin, V., & Fournier, S. E. (2019). Characteristics of Pediatric Dentists Who Work When Sick. Pediatric Dentistry, 41(6), 464–471.
  16. Yang, J., Yeates, K., Sullivan, L., Singichetti, B., Newton, A., Xun, P., Taylor, H. G., MacDonald, J., Pommering, T., Tiso, M., Cohen, D., Huang, Y., Patterson, J., & Lu, Z.-L. (2019). Rest Evaluation for Active Concussion Treatment (ReAct) Protocol: a prospective cohort study of levels of physical and cognitive rest after youth sports-related concussion. BMJ Open, 9(4), e028386.
  17. Yue, X., Wang, Z., Huang, J., Parthasarathy, S., Moosavinasab, S., Huang, Y., Lin, S. M., Zhang, W., Zhang, P., & Sun, H. (2019). Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations. Bioinformatics .

Platform Presentations:

  1. Soheil Moosavinasab, David Chen, Yungui Huang, Simon Lin. Text Analytics in a Pediatric Hospital: What we learned at Nationwide Children’s Hospital. Advancing Analytics in Children’s Hospitals Conference. June 2019
  2. Lindsay Alfano, David Chen, Steve Rust, Linda Lowes. Pre-symptomatic spinal muscular atrophy: reality or myth? 23rd Annual Spinal Muscular Atrophy Researcher Meeting. June 2019
  3. Tyler Gorham, Laura Rust, Richard Hoyt, Steve Rust. Analytics is a team Sport.  Advancing Analytics in Children’s Hospitals Conference. June 2019
  4. Yang JZ; Baily M; Strouse R; Bambach S, Singichetti B; Newton A; Asa N. Society for Advancement of Violence and Injury Research (SAVIR) Conference. May 2019

2018

Peer Reviewed Papers:

  1. Chen, D., Rust, S., Lin, E.-J. D., Lin, S., Nelson, L., Alfano, L., & Lowes, L. P. (2018). Prediction of Clinical Outcomes of Spinal Muscular Atrophy Using Motion Tracking Data and Elastic Net Regression. In Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics - BCB ’18.
  2. Das, M., Fosler-Lussier, E., Lin, S., Moosavinasab, S., Chen, D., Rust, S., Huang, Y., & Ramnath, R. (2018). Phrase2VecGLM: Neural generalized language model–based semantic tagging for complex query reformulation in medical IR. In Proceedings of the BioNLP 2018 workshop.
  3. Lundine, J. P., Harnish, S. M., McCauley, R. J., Blackett, D. S., Zezinka, A., Chen, W., & Fox, R. A. (2018). Adolescent Summaries of Narrative and Expository Discourse: Differences and Predictors. Language, Speech, and Hearing Services in Schools, 49(3), 551–568.
  4. Nunley, S., Glynn, P., Rust, S., Vidaurre, J., Albert, D. V. F., & Patel, A. D. (2018). Healthcare Utilization Characteristics for Intranasal Midazolam Versus Rectal Diazepam. Journal of Child Neurology, 33(2), 158–163.
  5. Oliver, E. A., Klebanoff, M., Yossef-Salameh, L., Oza-Frank, R., Moosavinasab, S., Reagan, P., Muglia, L., Buhimschi, C. S., & Buhimschi, I. A. (2018). Preterm Birth and Gestational Length in Four Race–Nativity Groups, Including Somali Americans. In Obstetrics & Gynecology (Vol. 131, Issue 2, pp. 281–289).
  6. Prinzbach, A., Moosavinasab, S., Rust, S., Boyle, B., Barnard, J. A., Huang, Y., & Lin, S. (2018). Comorbidities in Childhood Celiac Disease: A Phenome Wide Association Study Using the Electronic Health Record. Journal of Pediatric Gastroenterology and Nutrition, 67(4), 488–493.
  7. Sezgin, E., Weiler, M., Weiler, A., & Lin, S. (2018). Proposing an Ecosystem of Digital Health Solutions for Teens With Chronic Conditions Transitioning to Self-Management and Independence: Exploratory Qualitative Study. In Journal of Medical Internet Research (Vol. 20, Issue 9, p. e10285).
  8. Swaminathan, R., Huang, Y., Miller, K., Pastore, M., Hashimoto, S., Jacobson, T., Mouhlas, D., & Lin, S. (2018). Transferring Exome Sequencing Data from Clinical Laboratories to Healthcare Providers: Lessons Learned at a Pediatric Hospital. Frontiers in Genetics, 9, 54.
  9. Walawender, L., Patterson, J., Strouse, R., Ketz, J., Saxena, V., Alexy, E., & Schwaderer, A. (2018). Mobile Technology Application for Improved Urine Concentration Measurement Pilot Study. Frontiers in Pediatrics, 6, 160.
  10. Nowak A., Dooley D., Royston L., Rust S., Chen D., Merryman B.,Mathew T., Hoffman J., Wright R., & Casamassimo P. (2018) Predictive Model for Caries Risk Based on Determinants of Health Available to Primary Care Providers. In AADP.

Platform Presentations:

  1. Rust L, Gorham T. Optimizing Predictors of Pediatric Inpatient Deterioration: Transforming Anecdotes to Data-Driven Evidence. American Academy of Pediatrics National Conference, Orlando, FL. November 2018.
  2. Nelson L, Alfano L, Chen D, Miller N, Dugan M, Rust S, Lin E, Lin S, Wang-Price S, Swank C, Thompson M, LowesL. Use of the ACTIVE-mini for quantifying movement in infants with Spinal Muscular Atrophy. 23rd International Congress of the Muscle Society. October 2018
  3. Royston LK, Nowak A, Dooley D, Rust S, Chen D, Mathew T, Hoffman J, Wright R, Casamassimo P.  Early Childhood Caries: A Predictive Model Using Variables Regularly Documented During Well-Child Visit.  Pediatrics Aug 2019, 144 (2 MeetingAbstract) 717; DOI: 10.1542/peds.144.2_MeetingAbstract.717

2017

  1. Chen, W., Durkin, C., Huang, Y., Adler, B., Rust, S., & Lin, S. (2017). Simplified Readability Metric Drives Improvement of Radiology Reports: an Experiment on Ultrasound Reports at a Pediatric Hospital. Journal of Digital Imaging, 30(6), 710–717.
  2. Khare, R., Utidjian, L., Ruth, B. J., Kahn, M. G., Burrows, E., Marsolo, K., Patibandla, N., Razzaghi, H., Colvin, R., Ranade, D., Kitzmiller, M., Eckrich, D., & Bailey, L. C. (2017). A longitudinal analysis of data quality in a large pediatric data research network. Journal of the American Medical Informatics Association: JAMIA, 24(6), 1072–1079.
  3. Miller, K. E., & Lin, S. M. (2017). Addressing a patient-controlled approach for genomic data sharing [Review of Addressing a patient-controlled approach for genomic data sharing]. Genetics in Medicine: Official Journal of the American College of Medical Genetics, 19(11), 1280–1281.
  4. Swaminathan, R., Huang, Y., Astbury, C., Fitzgerald-Butt, S., Miller, K., Cole, J., Bartlett, C., & Lin, S. (2017). Clinical exome sequencing reports: current informatics practice and future opportunities. Journal of the American Medical Informatics Association: JAMIA, 24(6), 1184–1191.

2016

  1. Backes, C. H., Bonachea, E. M., Rivera, B. K., Reynolds, M. M., Kovalchin, C. E., Reber, K. M., Ball, M. K., Sutsko, R., Guntupalli, S. R., Smith, C. V., Mahan, J. D., & Carbajal, M. M. (2016). Preparedness of pediatric residents for fellowship: a survey of US neonatal-perinatal fellowship program directors. Journal of Perinatology: Official Journal of the California Perinatal Association, 36(12), 1132–1137.
  2. Chen, W., Huang, Y., Boyle, B., & Lin, S. (2016). The utility of including pathology reports in improving the computational identification of patients. Journal of Pathology Informatics, 7, 46.
  3. Chen, W., Wheeler, K. K., Lin, S., Huang, Y., & Xiang, H. (2016). Computerized “Learn-As-You-Go” classification of traumatic brain injuries using NEISS narrative data. Accident; Analysis and Prevention, 89, 111–117.
  4. Moosavinasab, S., Patterson, J., Strouse, R., Rastegar-Mojarad, M., Regan, K., Payne, P. R. O., Huang, Y., & Lin, S. M. (2016). “RE:fine drugs”: an interactive dashboard to access drug repurposing opportunities. Database: The Journal of Biological Databases and Curation, 2016.
  5. Patel, A. D., Moss, R., Rust, S. W., Patterson, J., Strouse, R., Gedela, S., Haines, J., & Lin, S. M. (2016). Patient-centered design criteria for wearable seizure detection devices. Epilepsy & Behavior: E&B, 64(Pt A), 116–121.
  6. Regan, K., Moosavinasab, S., Payne, P., & Lin, S. (2016). Drug Repurposing Hypothesis Generation Using the “RE:fine Drugs” System. Journal of Visualized Experiments: JoVE, 118.
  7. Swaminathan, R., Huang, Y., Moosavinasab, S., Buckley, R., Bartlett, C. W., & Lin, S. M. (2016). A Review on Genomics APIs. Computational and Structural Biotechnology Journal, 14, 8–15.
  8. Moosavinasab S, Patterson J, Wheeler KK, Strouse R, Xiang H, Huang Y., Lin SM. (2016) Re:fine NEISS: a real-time interaction search system for consumer product-related injury ed visits in United States. Injury Prevention 22:A129.
  9. Grishchenko, A., Luna, J., & Patterson, J. (2016). Voxel bay. In ACM SIGGRAPH 2016 Talks on - SIGGRAPH ’16.
  10. Chen D., Moosavinasab S., Zemke A., Prinzbach A., Rust S., Huang Y., & Lin S. (2016). Evaluation of a Machine Learning Method to Rank PubMed Central Articles For Clinical Relevancy: NCH at TREC 2016 Clinical Decision Support Track.

2015

  1. Chen, W., Kowatch, R., Lin, S., Splaingard, M., & Huang, Y. (2015). Interactive Cohort Identification of Sleep Disorder Patients Using Natural Language Processing and i2b2. Applied Clinical Informatics, 6(2), 345–363.
  2. Chen, W., Wheeler, K., Huang, Y., Lin, S., Sui, D., & Xiang, H. (2015). Evaluation of Spatial Accessibility to Ohio Trauma Centers Using a GIS-Based Gravity Model. In British Journal of Medicine and Medical Research (Vol. 10, Issue 7, pp. 1–12).