Project details
AI For Nutrition
AI-assisted food tracking to revolutionise nutritional research
The problem
Poor quality nutritional data
The important role of food intake on health outcomes, both for disease prevention and treatment, remains poorly understood.
Skepticism about nutritional science is widespread both in academia and in the public. A key contributor to the problem is how food intake is measured in the first place: food-frequency questionnaires (FFQs) and diet recalls are still the standards, despite their well-known weaknesses such as imprecision, dependence on human memory, lack of associated data such as the timing of food intake, etc.
While other aspects of health and behaviour measurements have evolved and improved steadily over the past decades (genomics, metagenomics, sensors, etc.), nutrition measurement has been stuck in time: it is still done the same way it was done decades ago.
The solution
Introducing the AI for Nutrition project
The AI for Nutrition project provides a comprehensive, scalable, and demonstrated solution to digital diet logging suitable for the use in research settings.
Developed in the Digital Epidemiology Lab at EPFL, it combines three essential parts:
MyFoodRepo
A mobile app (Android and iOS) for individuals to track food by picture taking or barcode scanning.
The Open Food Repo
An open database of barcoded food products, and an open, extensible categorization of food items.
MyFoodRepo AI Benchmark
An annotation framework combining artificial intelligence (AI) algorithms and human expertise.
The AI for Nutrition project provides a comprehensive, scalable, and demonstrated solution to digital diet logging suitable for the use in research settings.
Developed in the Digital Epidemiology Lab at EPFL, it combines three essential parts:
MyFoodRepo
A mobile app (Android and iOS) for individuals to track food by picture taking or barcode scanning.
The Open Food Repo
An open database of barcoded food products, and an open, extensible categorization of food items.
MyFoodRepo AI Benchmark
An annotation framework combining artificial intelligence (AI) algorithms and human expertise.
Feasibility
Proof of principle
Early stage clinical trials have been established in Switzerland.
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Ongoing trials
3 ongoing; 2 in the pipeline
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App usage
Used by study participants daily
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Barcode database
40k+ products (foodrepo.org)
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Image recognition algorhytm
Trained on 50k+ images
The future
Project goals
Set milestones for 2020 — 2023.
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Improve accuracy
Steady development of the MyFoodRepo AI Benchmark for best possible food image recognition.
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Enhance ease of use
Further development of the mobile application to provide a user-friendly experience.
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Scale up internationally
Establish MyFoodRepo in at least 6 new geographies.
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Reach self-sustaniability
Ensure MyFoodRepo will become a non-profit service platform able to sustain itself.
The team
Involved grantees
The Santorio Foundation is a pooled non-profit Swiss foundation fund hosted by the umbrella foundation Fondations des Fondateurs.
Coordination of the digital infrastructure
Rolling out for specific clinical trials
Roll out into new countries
Improve user friendlyness
Key aims
Coordination of the digital infrastructure
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Improve food recognition AI algorithms
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Enhance ease-of-use of MyFoodRepo application
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Provide the MyFoodRepo platform to cohorts internationally
Key aims
Roll out into new countries
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Improve food recognition AI algorithms
Technion
Main Investigator
John Doe
Key aims
Improve user friendlyness
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Improve food recognition AI algorithms
Gustave Raussy
Main Investigator
Jane Jones
Accelerate
How can you help create impact?
With more resources, AI For Nutrition can be accelerated in different ways:
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Roll out into new countries
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Rolling out for specific clinical trials
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Improve the digital infrastructure
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Improve user friendlyness
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Improve AI algorhytms
is currently on this stage
Our partners
Project co-impactors
Santorio co-impactors
Project supporter
Grant supporter
Coordination of the digital infrastructure
Project supporter
Independent co-impactors
Project supporter
Project supporter
More information
Links and documentation
If you want to know more about this project, you can refer to the links and documents below.
Santorio Project Steward
Sandra Suiser, PhD
Senior Scientific Project Manager,
Seerave Foundation
Support this project
Contact Sandra to learn more about AI for nutrition and become a co-impactor.