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arXiv AI By Varvara Kondratyeva, Kamilia Zaripova, Nassir Navab, Azade Farshad

Predicting Postprandial Glycemic Response from Meal Images, Clinical Variables, and Gut Microbiome Information

Read the original on arXiv AI →

The study introduces a multimodal framework that predicts postprandial glycemic response (PPGR) by combining image-derived macronutrient estimates with clinical variables and gut microbiome data. It jointly performs macronutrient estimation from meal images and glucose prediction, using an attention-based module to model interactions between dietary and host-specific information. Evaluated on a real-world dataset, the model outperforms existing PPGR baselines that use image-derived inputs and nearly matches methods relying on manually reported macronutrients.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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