The DOI matches its Crossref record; the references it cites are not checked yet.
IDF21-0598 Remission of T2DM by digital twin technology across Indian and American cohorts–Initial insights from real-world study
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
DT technology was effective in reducing cardiovascular risk and improving non-glycemic factors such as body weight and systolic blood pressure, regardless of differing phenotypes.
“Notably, DT technology proved effective in reducing cardiovascular risk and improving non-glycemic factors such as body weight and systolic blood pressure, demonstrating its efficacy regardless of differing phenotypes.”
From Personalized nutrition in type 2 diabetes remission: application of digital twin technology for predictive glycemic control (2024) · cites this paper as [26]
Over 90 days, both Indian and American cohorts with T2D exhibited significant improvements in key glycemic and metabolic parameters, including HbA1c, HOMA-IR, TyG index, and Framingham Risk Score (FRS), with outcomes comparable between the two groups.
“Over 90 days, both cohorts exhibited significant improvements in key glycemic and metabolic parameters, including HbA1c, HOMA-IR, TyG index, and Framingham Risk Score (FRS), with outcomes comparable between the two groups.”
From Personalized nutrition in type 2 diabetes remission: application of digital twin technology for predictive glycemic control (2024) · cites this paper as [26]
The DT model provides consistent benefits across diverse populations, demonstrating its adaptability and effectiveness across varied clinical and sociodemographic profiles.
“The findings indicate that the DT model provides consistent benefits across diverse populations, demonstrating its adaptability and effectiveness across varied clinical and sociodemographic profiles (26).”
From Personalized nutrition in type 2 diabetes remission: application of digital twin technology for predictive glycemic control (2024) · cites this paper as [26]
Citations
The citation lists haven’t been fetched yet
Cited by 1
Metadata
- Authors
- Shah, L., Joshi, S., Dharmalingam, M., Shamanna, P., Damodaran, S., Mohammed, J., Mohamed, M., Poon, T., Mohamed, T., Keshavamurthy, A., & Willis, B.
- Affiliations
- Lilavati Hospital & Research Centre (IN)
- M.S. Ramaiah Medical College (IN)
- Corresponding author
- Shah, L.
- Venue
- Diabetes Research and Clinical Practice
- Publisher
- Elsevier BV
- Published
- 2022-04
- Volume
- 186
- Pages
- 109579
- ISSN
- 0168-8227 (ISSN-L)
- OpenAlex
- W4281787060
- Cited by
- 1
- References
- 0
- Citations by year
- 2024: 1
- FWCI
- 0.19
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Diabetes Research and Clinical Practice (publishedVersion)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- type 2 diabetes remission, glycemic control, artificial intelligence, Internet of Things, real-world evidence, cross-cohort comparison
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
