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Data Mining of Dietary patterns (Data (Datasets (Start questioneer…
Data Mining of Dietary patterns
Data
MYMeals study
Wellard-Cole 2018 Protocol: Examining the Frequency and Contribution of Foods eaten Away From Home...
EaT App
Databases used
AUSNUT
The George Institute Fast Food
EaT App Design and Development
Wellard-Cole 2018 A Tool to Measure Young Adults Food Intake..
MYMeals results
Wellard-Cole tbp Integrating ubicomp and nutrition research..
Validity of using mobile food logging
Undereporting issues
Validation
Wellard-Cole 2019 Relative Validity of the EaT Smartphone App for Collections of Dietary Intake Data in 18-30 Tear Olds
agreement for nutrient densities :check:
differences in median energy intake :green_cross:
alternatives
FFQ (Food frequency questioneer)
gold standard 24-hour-recall (Thomson)
Datasets
Daily questioneer
Food Intake
Start questioneer
Inclusion? Pre-selection for number of eat-outs
Final questioneer
Cancer Coucil
Interest in Change of Legislation
2014 HSR system :star: voluntary guideline for packaged foods
Extention to fast foods possible (paper E. Dunford
A comparisom of the Health Star Ranking System when used for restaurant fast food and packaged foods 2017
)
algorithm behind HSR :star:
HSR Calculator
KJ Labelling law
National Nutrition Policy
Taxation of Foods
Interest in Australian Health
National Health Survey by ABS (2017-18)
National Nutrition and Physical Activity Survey by ABS (2011-12)
Grech 2016, HEIFA-2013
Data Mining
Supervised Learning :warning: response?
Response variable
BMI (self-reported :warning:)
Take-away (on meal-level) or proportion of take-away meals) (regression problem)
Waist Measurement (not available)
Classifiers
Unsupervised Learning
Clustering
K-means
K-means++
K-merioids
Factor Anaysis
PCA
:warning: linear expression only
Common Factor Analysis (low interpretability)
TNSE (no inference, visualization, complex interactions)
Association Rules
Experiment design choices
Features
Healthiness of Diet
HEI (Healthy Eating Index)
compare normal day to stressed day? within-subject
Macronutrient distribution (Acceptable Macronutrient Distribution Ranges, AMDRs) Protein, Fats, Carbohydrates + Alcohol (not always 100 %), contribution to total Energy
Five Food Model
RND Relative Nutritional Intakes
ADC Average Dietary Contributions (per grams)
Socio-environmental context: Check disadvantage & urban results from National Health Survey
Level of Analysis (Colin)
subject-level :silhouette:
within-subject (bad day good day)
between-subject
day-level :check: done by Colin
meal-level (take away Y/N)
Semi-supervised Learning?
Research Project Output
past students work
Ada Fang
Issue with serving size :red_flag:
does not contain all sociological-context attributes yet :red_flag:
cluser profiling :red_flag:
Colin Cai
:pencil2: no subject-level Analysis
Literature review: ML in Nutrition
Kim
SOURCE: Consider eating out aspect (money, social...)
visualization of basic knowledge (EDA)
Protein leverage?
Veronica
ARC Linkage (Australian Research Council)
USYD
School of Computer Science
CHAI
School of Life and Environmental Science
Stakeholders
Methods
Data