Introduction: Nutrition — a key health issue

In healthcare facilities — hospitals, nursing homes, senior living communities — food is not just a matter of logistics: it’s a true lever of public health.

Proper nutrition helps prevent malnutrition, accelerate recovery, reduce length of stay, and limit complications.

And yet, as of 2026, most facilities still lack any automated or daily measurement of patients’ actual intake. Tools remain artisanal, based on human observation or hand-filled tracking sheets.

This is where artificial intelligence (AI) steps in.

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1. Why is nutrition so hard to track on a daily basis?

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Several structural obstacles make tracking ingesta (consumed amounts) difficult:

• Meals are eaten in different places (room, dining hall, cafeteria)
• Trays include multiple components (starter, main dish, dessert, supplements)
• Staff are under pressure and lack time to observe plates
• Food intake varies widely from one day to the next
  

The result? Nutritional decisions are made blindly — or too late — when malnutrition has already set in.

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2. Visual AI: a technological breakthrough for patient care

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AI can now automatically analyze photos of meals taken before and after consumption to estimate how much was truly eaten.

How does it work?

• A tablet or smartphone takes a picture of the served tray with minimal interaction
• A second photo is taken after the meal, if food remains
• The AI compares before/after images, recognizes the food, measures leftovers
• It automatically calculates nutritional intake (kcal, proteins, etc.) using integrated menus
  

This technology is non-intrusive, fast (under 20 seconds), and fully adapted to the workflow of care units — validated in 4 pilots across geriatrics, nursing homes, and school cafeterias.

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3. What are the benefits for care teams and dietitians?

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AI doesn’t replace professionals — it enhances them:

• Time-saving for caregivers (no manual entry)
• Decision support tool for dietitians
• Alerts in case of intake drop or non-compliance with dietary prescriptions
• Improved communication with the kitchen (textures, portion sizes, fortification)
  

Nutrition finally becomes a manageable and traceable indicator.

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4. Clinical, economic, and environmental impact

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According to the Health Care Without Harm Europe report, up to 50% of hospital food is thrown away. Meanwhile, malnutrition increases length of stay, readmissions, and can cost up to €5,000 per affected patient.

With an AI solution like Skeal:

• Food waste can drop by 30–50%
• At-risk residents are identified earlier (prevention)
• Menus are better adapted to real preferences and needs
• ROI is visible in less than a year

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5. AI and compassionate care: a compatible alliance

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AI is sometimes met with skepticism. But when applied to nutrition, it strengthens:

• Respect for patient choices and preferences
• Early prevention of malnutrition
• Transparency between care teams, kitchen staff, and families
  

The goal isn’t to replace humans — it’s to give them back the means to act.

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💡 Did you know manual ingesta records are only accurate about 60% of the time, according to a 2014 study by Barton et al. across 5 UK hospitals?

As a result, actual food intake is often underestimated or overestimated, making it difficult to make reliable clinical decisions.

We’ve also observed that less than 30% of at-risk patients actually receive a food intake form — and not every day!

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Conclusion: a strategic opportunity for healthcare systems

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The technology is mature. The stakes are clinical, economic, and human.

It’s time to make nutrition a verifiable and personalized pillar of patient care — using AI tools that are fast, simple, and designed for real-world environments.

At Skeal, we believe that what gets measured can be improved.

And in nutrition, as in medicine, every detail counts.

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🤝 Book a demo and test Skeal in your facility!

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