UKB_HES_10topics

<p>An illustrative result object/table from a 10-topic model fit to UKB HES-like data;
used for examples, plotting, and tests.</p>

datasets

We propose an age-dependent topic modelling (ATM) model,
providing a low-rank representation of longitudinal records of
hundreds of distinct diseases in large electronic health record data sets. The model
assigns to each individual topic weights for several disease topics;
each disease topic reflects a set of diseases that tend to co-occur as
a function of age, quantified by age-dependent topic loadings for each
disease. The model assumes that for each disease diagnosis, a topic is
sampled based on the individual’s topic weights (which sum to 1 across
topics, for a given individual), and a disease is sampled based on the
individual’s age and the age-dependent topic loadings (which sum to 1
across diseases, for a given topic at a given age). The model
generalises the Latent Dirichlet Allocation (LDA) model by allowing
topic loadings for each topic to vary with age.
References: Jiang (2023) <doi:10.1038/s41588-023-01522-8>.

Xilin Jiang

AgeTopicModels

Inferring Age-Dependent Disease Topic from Diagnosis Data

UKB_HES_10topics function

<p>An array for UKB topic loadings.
Dimention is age, disease, topics. the ordering of disease is the same as UKB_349_disease.</p>

UKB_HES_10topics: Example topic model output (10 topics, UKB HES)

Description

Usage

Arguments

Format

Examples