# Dietary guidance for pregnant women using DeepSeek-R1 and ChatGPT-4.0: a comparative analysis

**Authors:** ZeJun Gao, Jie Li, WeiYue Fang

PMC · DOI: 10.3389/fpubh.2026.1728954 · 2026-02-03

## TL;DR

This study compares two AI models, DeepSeek-R1 and ChatGPT-4.0, in generating dietary plans for pregnant women, finding differences in quality and cost.

## Contribution

The study evaluates and compares the performance of two AI models in generating dietary guidance for pregnant women.

## Key findings

- DeepSeek-R1 provided better caloric targets and food adequacy scores compared to ChatGPT-4.0.
- ChatGPT-4.0 performed better in moderation and cost-effectiveness aspects of dietary plans.
- Both models achieved satisfactory DQI-I scores for dietary quality.

## Abstract

Advancements in artificial intelligence (AI) and natural language processing have enabled the widespread application of large language models. However, the ability of AI models to provide dietary guidance for pregnant women remains unclear. This study aims to explore the capabilities of DeepSeek-R1 and ChatGPT-4.0 in generating dietary plans for pregnant women with different activity levels.

Personalized diet plans were generated using DeepSeek-R1 and ChatGPT-4.0. Through calorie calculation, Diet Quality Index-International (DQI-I) assessment, and cost analysis, the dietary quality and cost performance were evaluated.

The requested caloric targets in DeepSeek’s diet plans were superior to those of ChatGPT. All plans achieved a satisfactory DQI-I score (≥ 70). The “adequacy” score of DeepSeek-R1 was much higher (DeepSeek-R1 35.8 ± 0.7 vs. ChatGPT-4.0 33.9 ± 0.8, p < 0.001), while ChatGPT-4.0 performed better in the “moderation” aspect (ChatGPT-4.0 22.3 ± 2.2 vs. DeepSeek-R1 17.0 ± 3.4, p = 0.004). ChatGPT-4.0 demonstrated better performance in terms of cost-effectiveness (p = 0.017).

This study shows that DeepSeek-R1 and ChatGPT-4.0 can be helpful in providing personalized and reasonable dietary advice for pregnant women. In some aspects, such as food type adequacy, the emerging model “DeepSeek” performs better than ChatGPT.

## Full-text entities

- **Genes:** LRIT1 (leucine rich repeat, Ig-like and transmembrane domains 1) [NCBI Gene 26103] {aka FIGLER9, LRRC21, PAL}
- **Diseases:** scurvy (MESH:D012614), Malnutrition (MESH:D044342), hallucination (MESH:D006212), anemia (MESH:D000740), preterm birth (MESH:D047928), heart disease (MESH:D006331), breast cancer (MESH:D001943), irritable bowel syndrome (MESH:D043183), chronic (MESH:D002908), infectious diseases (MESH:D003141), neurodevelopmental disorders (MESH:D002658), diabetes (MESH:D003920), Cancer (MESH:D009369), stroke (MESH:D020521), non-communicable chronic diseases (MESH:D000073296), obesity (MESH:D009765), AI (MESH:C538142), weight gain (MESH:D015430), iron deficiency anemia (MESH:D018798)
- **Chemicals:** sodium (MESH:D012964), DeepSeek-R1 (-), olive oil (MESH:D000069463), fatty acid (MESH:D005227), Calcium (MESH:D002118), iron (MESH:D007501), cholesterol (MESH:D002784), vitamin C (MESH:D001205)
- **Species:** Daucus carota (carrot, species) [taxon 4039], Ipomoea batatas (batate, species) [taxon 4120], Solanum lycopersicum (tomato, species) [taxon 4081], Homo sapiens (human, species) [taxon 9606], Cucumis sativus (cucumber, species) [taxon 3659], Oryza sativa (Asian cultivated rice, species) [taxon 4530], Brassica oleracea var. italica (asparagus broccoli, varietas) [taxon 36774], Curcuma longa (turmeric, species) [taxon 136217], Gallus gallus (bantam, species) [taxon 9031], Spinacia oleracea (spinach, species) [taxon 3562], Malus domestica (apple, species) [taxon 3750], Zingiber officinale (ginger, species) [taxon 94328], Rubroshorea almon (species) [taxon 292004], Meleagris gallopavo (common turkey, species) [taxon 9103]

## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12909500/full.md

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Source: https://tomesphere.com/paper/PMC12909500