EMPIRICAL MODELS FOR LONGITUDINAL POST-NATAL GROWTH

Machine learning models for child growth trajectories

To describe variability in longitudinal grwoth trajectories.

AGE RANGE

0-5000 days

OUTCOMES

Height/length, weight, head circumference

Predictors (other than time)

Maternal parity, duration of breast feeding, gestational age at birth, maternal age, maternal height, maternal weight, maternal BMI, mothers education (years), father's education (years), child's sex, child's Apgar scores (1 and 5 minutes),

Do we have a tool for visualizing model output/predictions? If not, do we plan to?

No tool, and no plans scheduled.

Status

Complete

On-going work

None

Links to content

No links to other content

Documentation / Code / Slides / Tools

Needs updating: https://github.com/HBGDki/anthroboostr

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