Development of an individualized prediction model for dynamic adaptations in performance and immune function associated with dietary patterns in endurance athletes using machine learning

Yun Hou; Meijia Chen; Gang Qin; Ziyu Wang

doi:10.1080/15502783.2026.2624377

January 31, 2026Journal of the International Society of Sports NutritionOpen Access

Development of an individualized prediction model for dynamic adaptations in performance and immune function associated with dietary patterns in endurance athletes using machine learning

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Key Points

To develop a model predicting how dietary patterns affect performance and immune function in endurance athletes based on psychological resilience.
Utilized machine learning algorithms to analyze data from endurance athletes.
Assessed participants' baseline psychological resilience.
Examined the interplay between dietary patterns and immune function through psychoneuroimmunological pathways.
Identified key psychological factors that influence dietary responsiveness.
Developed a predictive model that tailors nutrition strategies for improved athletic performance and immune health.

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Implication

Demonstrates the role of psychological resilience in dietary responsiveness among endurance athletes, suggesting personalized nutrition strategies.

Abstract

Psychological resilience predicts responsiveness to dietary patterns through psychoneuroimmunological pathways. Baseline psychological assessment should guide personalized nutrition strategies in clinical populations experiencing chronic stress and immune dysfunction.

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Cite This Study

Hou et al. (2026) studied this question.

synapsesocial.com/papers/6980ff26c1c9540dea811e08 https://doi.org/10.1080/15502783.2026.2624377

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Development of an individualized prediction model for dynamic adaptations in performance and immune function associated with dietary patterns in endurance athletes using machine learning

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

Development of an individualized prediction model for dynamic adaptations in performance and immune function associated with dietary patterns in endurance athletes using machine learning

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

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