Recent Bibliography

During an eight-year stint with UnitedHealth Group, as Senior Medical Director for Informatics and Data Science, I was on the ground with AI teams developing applications based on machine learning algorithms and large language models/generative AI. I’m a former practicing board-certified Internal Medicine physician with NIH/NLM medical informatics research fellowship training, and have developed predictive models for opioid use disorder, chronic kidney disease, ischemic heart disease, atrial fibrillation, and hyperlipidemia. My approach for the progression of heart failure is now patent pending with USPTO (categorical and ML-based). I have deep experience…
  • … as a change agent and presenter on topics related to adult chronic disease and data systems to manage population health. This has been a powerful part of my client’s sales presentations.
  • … in clinical workflow analysis and the data it generates in electronic health records
  • … with episode-based modeling of care pathways
  • … developing categorical models of health and disease based on administrative data, EHR, labs, and free-text data
  • … as a presenter at the university and physician-CME level on these topics (University of Minnesota, University of  St. Thomas, Pri-Med Primary Care CME conferences)
  • … and have published widely on these topics 

Hlynsson, HD, Ong, JC, Day J, Kauss T, Montazeri K, Hertzberg, J, et al. The Impact of Comorbid Sleep-Disordered Breathing on Hospitalization Risk Related to Diabetes and Atherosclerotic Disease: A Retrospective Cohort Analysis. Journal of Clinical Medicine 2024;13(24):7715

Bali V, Weaver J, Turzhitsky V, Schelfhout J, Paudel M, Hulbert E, Peterson-Brandt J, Hertzberg J, et al. Machine learning to identify chronic cough from administrative claims data. Nature Portfolio Scientific Reports 2024;14:2449

Patel RH, Fan L, Kelly NR, Gelsey F, Hertzberg JK et al. A machine learning-based algorithm to identify U-500R insulin candidates among adults with type 2 diabetes mellitus in US retrospective databases. Current Medical Research and Opinion 2024: https://doi.org/10.1080/03007995.2023.2293116
Stremmel J, Saeedi A, Hassanzadeh H, Batra S, Hertzberg J et al. XAIQA: Explainer-based data augmentation for extractive question answering. Machine Learning for Health Proceedings (ML4H 2023)Vodrahalli K, Lyng G, Karkkainen K, Hertzberg J. Understanding and predicting the effect of environmental factors on people with Type 2 diabetes. Conference on Health, Inference, and Learning (CHIL 2023). Cambridge MA, June 22, 2023 https://proceedings.mlr.press/v209/vodrahalli23a.html
Stremmel J, Hill BL, Hertzberg J, et al. Extend and explain: interpreting very long language models. Machine Learning for Health Proceedings (ML4H 2022), New Orleans LA, November 28, 2022
Karkkainen K, Lyng G, Hill BL, Vodrahalli K, Hertzberg J et al. Sleep and activity prediction for type 2 diabetes management using continuous glucose monitoring. Poster presentation, Machine Learning for Health Proceedings (ML4H 2022), New Orleans LA, December 2, 2022
Eby E, Kelly N, Hertzberg J, et al. Predicting response to bolus insulin therapy in patients with type 2 diabetes. J Diab Sci Tech, May 2022. doi:10.1177/19322968221098057
Hertzberg JK et al. Ischemic heart disease and Type 2 diabetes complications are associated with glycemic variability measured by continuous glucose monitoring. Abstract and poster, American Heart Association Scientific Sessions 2021. Circulation 2021;144(Supp_1)
Bali V, Weaver J, Turzhitsky V, Schelfhout J, Paudel M, Hulbert E, Peterson-Brandt J, Hertzberg J, et al. Development of a claims-based algorithm to identify patients with chronic cough. Poster presentation, ATS 2021—International Conference of the American Thoracic Society. Am J Respir Crit Care Med 2021;203:A3146
Eby LE, Kelly NR, Hertzberg J et al. Predicting response to bolus insulin. Poster presentation for the American Diabetes Association 80th Annual Scientific Sessions, June 2020
Hertzberg J, Forni A. The use of machine learning to boost identification of atrial fibrillation and increase appropriate utilization of anticoagulant drugs. Value in Health, the Journal of the International Society for Pharmacoeconomics and Outcomes Research, 2018;21 Supp 1:S8
Olson C, Nelson S, Newell J, Toensing P, Hertzberg J. Physical activity trackers and their impact on health care costs, utilization and member engagement. Value in Health, the Journal of the International Society for Pharmacoeconomics and Outcomes Research, 2017;20(5)