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Write symptom combinations to a JSON file

Source: R/io_combinations.R
write_combinations.Rd

Exports optimized symptom combinations to a human-readable JSON file. This enables sharing of derived combinations across research groups without needing to share raw data, supporting reproducible derivation-validation workflows.

Usage

write_combinations(
  combinations,
  file,
  n_required = 4,
  clusters = NULL,
  n_symptoms = NULL,
  score_by = NULL,
  description = ""
)

Arguments

combinations

A list of integer vectors specifying symptom combinations, or the full result object from optimize_combinations / optimize_combinations_clusters (which contains $best_symptoms).

file

Character string. Path to the output JSON file.

n_required

Integer specifying how many symptoms must be present for a positive diagnosis (default: 4). This value is stored in the file so that read_combinations can retrieve it.

clusters

NULL (default) for non-hierarchical combinations, or a named list of integer vectors defining the cluster structure for hierarchical combinations. Stored in the file for use with apply_symptom_combinations.

n_symptoms

Integer or NULL. Number of symptoms per combination. If NULL (default), inferred from the length of the first combination.

score_by

Character or NULL. The scoring criterion used during optimization ("false_cases" or "newly_nondiagnosed"). Stored as metadata for reproducibility. If NULL (default), omitted from the file.

description

Character string. Optional free-text description of the derivation context (e.g., sample characteristics, dataset name). Default is an empty string.

Value

The file path (invisibly), following the convention of write.csv.

Details

The JSON file contains the combinations alongside metadata needed to apply them via apply_symptom_combinations: the required symptom threshold (n_required) and optional cluster structure (clusters). Additional fields (score_by, n_symptoms, description) provide context for reproducibility.

The combinations argument can be either:

See also

read_combinations to import combinations from a JSON file.

optimize_combinations and optimize_combinations_clusters for deriving optimal combinations.

apply_symptom_combinations for applying imported combinations to new data.

Examples

# Create example combinations
my_combos <- list(
  c(1, 6, 8, 10, 15, 19),
  c(2, 7, 9, 11, 16, 20)
)

# Write to a temporary file
tmp <- tempfile(fileext = ".json")
write_combinations(my_combos, tmp, n_required = 4,
                   score_by = "false_cases",
                   description = "Example non-hierarchical combinations")
#> Combinations written to /tmp/RtmpGlFb3Z/file1ca2f124738.json

# Can also pass a full optimization result directly:
# write_combinations(optimization_result, tmp, n_required = 4)

# Clean up
unlink(tmp)