AgeTopicModels
0.3.0Inferring Age-Dependent Disease Topic from Diagnosis Data
Overview
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.
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- OK2026-04-2512 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-03-1012 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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2 releases. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 0.3.0Latest
- 0.1.02025-10-21
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2025-10-21
- Total releases
- 2 / 1 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 4.7 MB
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- not tracked yet
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