# GluPredKit: Development and User Evaluation of a Standardization Software for Blood Glucose Prediction

arXiv: https://arxiv.org/abs/2406.08915 · HTML: https://mlsanity.com/paper/2406.08915/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Jun 2024.

## Built on by (most cited first, 1 of 1)

- [GlucoTune: A Unified Framework for Blood Glucose Preprocessing, Forecasting, and Benchmarking in Diabetes](https://mlsanity.com/paper/2607.21117/) (2026)

## Abstract (arXiv)

Blood glucose prediction is an important component of biomedical technology for managing diabetes with automated insulin delivery systems. Machine learning and deep learning algorithms hold the potential to advance this technology. However, the lack of standardized methodologies impedes direct comparisons of emerging algorithms. This study addresses this challenge by developing GluPredKit, a software platform designed to standardize the training, testing, and comparison of blood glucose prediction algorithms. GluPredKit features a modular, open-source architecture, complemented by a command-line interface, comprehensive documentation, and a video tutorial to enhance usability. To ensure the platform's effectiveness and user-friendliness, we conducted preliminary testing and a user study. In this study, four participants interacted with GluPredKit and provided feedback through the System Usability Scale (SUS) and open-ended questions. The findings indicate that GluPredKit effectively addresses the standardization challenge and offers high usability, facilitating direct comparisons between different algorithms. Additionally, it serves an educational purpose by making advanced methodologies more accessible. Future directions include continuously enhancing the software based on user feedback. We also invite community contributions to further expand GluPredKit with state-of-the-art components and foster a collaborative effort in standardizing blood glucose prediction research, leading to more comparable studies.