ict to combat nutrition problems? barbara koroušić seljak

TTC’09

ICT to combat nutrition problems?

Barbara Koroušić Seljak

TTC’09

Problem: Overweight

Responsible for:• 10-13% of deaths in

different parts of the WHO European Region

• 2-8% of health costs

A strong risk factor for most prominent chronic diseases (CDs):

• Today, 60% of all deaths are due to CDs.

• By 2020, the contribution of CDs is expected to rise to 73% of all deaths.

TTC’09

Paradox: Undernutrition

One in three patients in general European hospitals is malnourished!

• Reason: Inadequate diet lacking in certain macro- and micronutrients

• Consequences: Higher complication rates (approx. 50% increase in length of stay and costs)

TTC’09

Measures to combat malnutrition

Clinical nutrition:• Nutritional screening & assessment in hospitals

and nursing homes• Artificial nutrition as medical therapy:

• Very expensive• Beyond reach

enteral & parenteral nutrition nutritional

supplements

TTC’09

Our idea

Web application for planning meals with no or minimal artificial nutrition!

TTC’09

Meal planning is an NP-complete problem

Many objectives:• low cost, high seasonal and

high gastronomical quality

Many personal constraints that may be mutually exclusive:

• Energy• Nutrients• Ratio of certain nutrients• Ratio of certain fatty &

amino acids• Non-nutrients (ORAC)• Food pyramid

multimodal search space

TTC’09

Meal planning is an NP-complete problem

Many objectives:• low cost, high seasonal and

high gastronomical quality

Many personal constraints that may be mutually exclusive:

• Energy• Nutrients• Ratio of certain nutrients• Ratio of certain fatty &

amino acids• Non-nutrients (ORAC)• Food pyramid

multimodal search space

It is expected that NO algorithm can be both

correct and fast (polynomial-time) on all cases!

TTC’09

Proposed solution

Problem translation to a knapsack problem:

• CO problem: Given foods of different values and volumes, the MFKP is to find the most valuable combination of foods that fits in a knapsack of fixed volumes!

Evolutionary computation + linear programming for local optimization

Daily meal 1 … Daily meal d

Meal 1 … Meal n

Food 1 … Food m

Food code Food portion

chromosome

TTC’09

Performed research steps

1. Application & publication in the national guidelines and recommendations

2. Publication in a peer-reviewed journal

3. Cooperative research project for SME

4. Presentation to an international group of experts (EuroFIR, ESPEN):

– FP7 project proposal

TTC’09

Performed steps:• Presentation given to a

group of diabetes experts who supported the idea

• The Slovene patent (SI 22693 A)

Looking for an industrial partner!

First extension

Personalized nutrition scale

Web application for meal planning

TTC’09

Second extension

Mobile application for informing consumers about nutritional value of food items:

Performed steps:• National research

project

Looking for a mobile operater and insurance company!

Web application for meal planning

TTC’09

Third extension

Food & physical activity diary for data mining and knowledge discovery

Performed steps:• Bilateral project• Dietary knowledge

ontology Web application for

meal planning

TTC’09

Steps & decisions to be done

Related mandatory activities:• Up-to-date food composition data & reference

values• Research work• Permanent education and training• Human-experts as active participants in the social

network

TTC’09

Steps & decisions to be done

Related mandatory activities:• Up-to-date food composition data & reference

values• Research work• Permanent education and training• Human-experts as active participants in the social

network

Solution: An institute or a company establisment?

TTC’09

Steps & decisions to be done

Related mandatory activities:• Up-to-date food composition data & reference

values• Research work• Permanent education and training• Human-experts as active participants in the social

network

Solution: An institute or a company establisment?

TTC’09

Thank you for hearing me out!