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

arXiv:2609.24453 · cs.AI · Submitted 2026-09-21 · Read on arXiv

cs.AI

Submitted: 2026-09-21

Updated: 2026-09-21

Comments: 11 pages (9 text + 2 references). This is a paper first submitted to MICCAI 2026 MultiTab workshop prior to peer review. The final revised version will be published in Springer LNCS proceedings after the MICCAI 2026 conference

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Ablation — 5× in this paper · explained in 1 episode
• Continuous Glucose Monitoring — 5× in this paper
• Joint Attention — 2× in this paper · explained in 2 episodes
• Multimodal Fusion — 2× in this paper · explained in 3 episodes
• Multimodal Learning — 2× in this paper · explained in 2 episodes
• Vision-Language Models (VLMs) — 2× in this paper · explained in 6 episodes
• Vision-language models — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Multimodal Dataset — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• DPF-Nutrition: Food Nutrition Estimation via Depth Prediction and Fusion
• Use of Continuous Glucose Monitoring with Machine Learning to Identify Metabolic Subphenotypes and Inform Precision Lifestyle Changes
• FiLM: Visual Reasoning with a General Conditioning Layer
• Nutrition5k: Towards Automatic Nutritional Understanding of Generic Food
• STSM-FiLM: A FiLM-Conditioned Neural Architecture for Time-Scale Modification of Speech

Related papers

• MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
• Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
• The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
• MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
• Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems
• VSAL: A Vision Solver with Adaptive Layouts for Graph Property Detection