Finding Optimal Alphabet for Encoding Daily Continuous Glucose Monitoring Time Series Into Compressed Text
Encoding CGM data into text could enhance the classification of CGM profiles and enable the use of well-established search engines with CGM data. Other potential applications include predictive modeling, anomaly detection, indexing, trend analysis, or future generative artificial intelligence applications for diabetes research and clinical practice.
Authors
- Tobore Igbe (ORCID: https://orcid.org/0000-0002-8216-9576)
- Boris P. Kovatchev (ORCID: https://orcid.org/0000-0003-0495-3901)
Institutions
- University of Virginia (US)
Publication Details
- Journal
- Journal of Diabetes Science and Technology
- Published
- 2025-03-20
- DOI
- https://doi.org/10.1177/19322968251323913
- Citations
- 1
- Primary Topic
- Diabetes Management and Research
- Type
- article
- Field-Weighted Citation Impact
- 1.29