lsi_model: LSI model with enhanced biomedical term filtering and NLP...
In LBDiscover: Literature-Based Discovery Tools for Biomedical Research

lsi_model

R Documentation

LSI model with enhanced biomedical term filtering and NLP verification

Description

This function implements an improved LSI model that more rigorously filters out non-biomedical terms from the results to ensure clinical relevance. It adds NLP-based validation as an additional layer of filtering.

Usage

lsi_model(
  term_doc_matrix,
  a_term,
  n_factors = 100,
  n_results = 100,
  enforce_biomedical_terms = TRUE,
  c_term_types = NULL,
  entity_types = NULL,
  validation_function = is_valid_biomedical_entity,
  min_word_length = 3,
  use_nlp = TRUE,
  nlp_threshold = 0.7
)

Arguments

`term_doc_matrix`	A term-document matrix.
`a_term`	Character string, the source term (A).
`n_factors`	Number of factors to use in LSI.
`n_results`	Maximum number of results to return.
`enforce_biomedical_terms`	Logical. If TRUE, enforces strict biomedical term filtering.
`c_term_types`	Character vector of entity types allowed for C terms.
`entity_types`	Named vector of entity types (if NULL, will try to detect).
`validation_function`	Function to validate biomedical terms.
`min_word_length`	Minimum word length to include.
`use_nlp`	Logical. If TRUE, uses NLP-based validation for biomedical terms.
`nlp_threshold`	Numeric between 0 and 1. Minimum confidence for NLP validation.