Review a clinical modelling pipeline for common pitfalls

Runs a series of rule-based checks for common clinical-ML pitfalls (class imbalance or low event rate, low events-per-variable, possible leakage, near-zero variance predictors), then optionally asks an LLM to summarize the findings in plain language. Works with both binary classification models (triageR_model) and survival models (triageR_survival_model).

Usage

tr_agent_review(data, model, use_agent = TRUE)

Arguments

data

The data frame used to fit the model.

model

A fitted triageR_model or triageR_survival_model object.

use_agent

Logical. If TRUE (default), also generates an AI-written plain-language summary of the findings via ellmer.

Value

A triageR_review object (list) containing a tibble of flags and, if use_agent = TRUE, an AI-generated summary.

Examples

if (FALSE) { # \dontrun{
tr_agent_review(data, model)
} # }