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From Traditional Medical Patterns to Artificial Intelligence: The Applicability of Digital Biomarkers in Reinventing Personalised Nutrition

Lucia Blendea; Ancuta Andreea Miler; Judit Csabai; Anca Trifan; Irina-Luciana Gurzu; Bogdan Novac; Otilia Novac; Antoneta Dacia Petroaie; Ioana-Miruna Balmus; Daniel Vasile Timofte
2025 · Volume 16 · Special Issue 1 Pages 179–192 Mixed-methods, cross-sectional study
Article overview

Explore how digital biomarkers, behavioural data, metabolic indicators, and AI-style reasoning can support personalised nutrition. The application combines an evidence dashboard, correlation explorer, transparent recommendation logic, and a short knowledge quiz.

📊

Interactive dashboard

Turn lifestyle and metabolic inputs into a digital biomarker profile with dynamic scores.

↔

Correlation explorer

Inspect the study relationships between biomarker use, dietary adherence, weight loss, and HbA1c change.

🧠

AI-style reasoning

See educational recommendations generated transparently from the user profile and article logic.

❓

Short article quiz

Test your understanding of the study with a short interactive quiz and instant feedback.

100participants
3 monthstracking period
4.2/weekfood logs
60 → 75dietary adherence
Educational use only: this application is inspired by the article and does not provide diagnosis or treatment.
Step 1

Profile builder + interactive dashboard

Enter values and watch the profile update automatically. This section combines the guided explorer with the original dashboard view.

Participant inputs

Reflective profile

Live results
Digital engagement0/100
Dietary adherence0/100
Metabolic balance0/100
Personalisation readiness0/100
Engagement class –

Adherence class –

Metabolic class –

Readiness class –

Step 2

Correlation explorer

Choose any two variables from the article and explore the direction and strength of the reported relationship.

Select variables

This educational prototype uses the published article values for the displayed associations.
Usage ↔ Adherencer = 0.45
Usage ↔ Weight lossr = 0.32
Usage ↔ HbA1c changer = -0.25
Adherence ↔ Weight lossr = 0.58
Adherence ↔ HbA1c changer = -0.41
Weight loss ↔ HbA1c changer = -0.63
↔

Digital Biomarker Usage ↔ Dietary Adherence Score

r = 0.45
Positive relationship

Step 3

AI-style personalised nutrition reasoning

This transparent reasoning block transforms your data into educational recommendations.

1

Data inputs

→
2

Biomarker signals

→
3

Interpretation

Suggested actions

Educational only

    Step 4

    Quick article quiz

    A short quiz to reinforce the main findings and methodology of the article.

    1. How many participants were included in the study?

    2. For how long were digital biomarkers tracked?

    3. What was the average number of food logs per week?

    4. Which change in dietary adherence was reported?

    5. Which pair showed the strongest inverse correlation?

    Your quiz result

    0 / 5

    Complete the quiz to see your score and feedback.

    This short quiz covers study design, engagement data, adherence change, and the published correlation matrix.
    Final step

    Your personalised nutrition reflection

    This final screen combines your dashboard profile, AI-style reasoning, and quiz result into one compact summary.

    Profile snapshot

    Learning snapshot

    Closing message

    Disclaimer: This prototype is for educational and research communication purposes only.