Datasets:
Modalities:
Text
Formats:
csv
Languages:
English
Size:
100K - 1M
Tags:
continuous-glucose-monitor
cgm
self-supervised-learning
representation-learning
masked-prediction
biosignal
License:
Update dataset card with paper link, GitHub repository, and citation
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by nielsr HF Staff - opened
README.md
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---
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license: cc-by-4.0
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language:
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- en
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task_categories:
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- feature-extraction
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modalities:
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- Time Series
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- Tabular
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tags:
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- continuous-glucose-monitor
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- cgm
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- time-series
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- pretraining
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- jepa
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size_categories:
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- 100K<n<1M
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configs:
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- config_name: default
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data_files:
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# CGM-JEPA Pretraining Corpus
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Continuous glucose monitor (CGM) time-series corpus used for self-supervised pretraining of **CGM-JEPA**, **X-CGM-JEPA**, **GluFormer**, and **TS2Vec** encoders in the paper
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> Pretraining-only corpus. For the labeled downstream-evaluation cohorts (insulin resistance and β-cell dysfunction classification), see [`CRUISEResearchGroup/CGM-JEPA-Downstream`](https://huggingface.co/datasets/CRUISEResearchGroup/CGM-JEPA-Downstream). For pretrained model weights, see [`CRUISEResearchGroup/CGM-JEPA`](https://huggingface.co/CRUISEResearchGroup/CGM-JEPA).
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## Citation
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---
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language:
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- en
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license: cc-by-4.0
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size_categories:
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- 100K<n<1M
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task_categories:
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- time-series-forecasting
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- feature-extraction
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pretty_name: CGM-JEPA Pretraining Corpus
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tags:
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- continuous-glucose-monitor
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- cgm
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- time-series
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- pretraining
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- jepa
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configs:
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- config_name: default
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data_files:
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# CGM-JEPA Pretraining Corpus
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Continuous glucose monitor (CGM) time-series corpus used for self-supervised pretraining of **CGM-JEPA**, **X-CGM-JEPA**, **GluFormer**, and **TS2Vec** encoders in the paper [CGM-JEPA: Learning Consistent Continuous Glucose Monitor Representations via Predictive Self-Supervised Pretraining](https://huggingface.co/papers/2605.00933).
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**Code:** [https://github.com/cruiseresearchgroup/CGM-JEPA](https://github.com/cruiseresearchgroup/CGM-JEPA)
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> Pretraining-only corpus. For the labeled downstream-evaluation cohorts (insulin resistance and β-cell dysfunction classification), see [`CRUISEResearchGroup/CGM-JEPA-Downstream`](https://huggingface.co/datasets/CRUISEResearchGroup/CGM-JEPA-Downstream). For pretrained model weights, see [`CRUISEResearchGroup/CGM-JEPA`](https://huggingface.co/CRUISEResearchGroup/CGM-JEPA).
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## Citation
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```bibtex
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@article{muhammad2026cgm,
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title = {CGM-JEPA: Learning Consistent Continuous Glucose Monitor Representations via Predictive Self-Supervised Pretraining},
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author = {Muhammad, Hada Melino and Li, Zechen and Salim, Flora and Metwally, Ahmed A},
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journal = {arXiv preprint arXiv:2605.00933},
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year = {2026}
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}
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```
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