# Gluformer: Transformer-Based Personalized Glucose Forecasting with Uncertainty Quantification Source: [Gluformer: Transformer-Based Personalized Glucose Forecasting with Uncertainty Quantification]() Collection index: [llms.txt]() Data updated: 2025-10-26T01:04:50.062Z Authors: Renat Sergazinov, Mohammadreza Armandpour, Irina Gaynanova Published: 2022-09-09T21:03:43.000Z ## Abstract Deep learning models achieve state-of-the art results in predicting blood glucose trajectories, with a wide range of architectures being proposed. However, the adaptation of such models in clinical practice is slow, largely due to the lack of uncertainty quantification of provided predictions. In this work, we propose to model the future glucose trajectory conditioned on the past as an infinite mixture of basis distributions (i.e., Gaussian, Laplace, etc.). This change allows us to learn the uncertainty and predict more accurately in the cases when the trajectory has a heterogeneous or multi-modal distribution. To estimate the parameters of the predictive distribution, we utilize the Transformer architecture. We empirically demonstrate the superiority of our method over existing state-of-the-art techniques both in terms of accuracy and uncertainty on the synthetic and benchmark glucose data sets. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Glucose Forecasting on OhioT1DM PH = 60 minutes](): Glucose forecasting; OhioT1DM PH = 60 minutes; RMSE (PH=60min): 27.14. - [Blood Glucose Forecasting on OhioT1DM Combined (test)](): Blood Glucose Forecasting; OhioT1DM Combined (test); RMSE: 17.27. - [Blood Glucose Forecasting on OhioT1DM 2020 (test)](): Blood Glucose Forecasting; OhioT1DM 2020 (test); RMSE: 27.14. ## Original sources and implementation [Original paper]() [PDF]()