batch_processor_db: Batch NLP Annotations for a Cohort

In CEDARS: Simple and Efficient Pipeline for Electronic Health Record Annotation

Description

NLP annotates documents for a cohort of patients, in parallel. Locks each record before proceeding with NLP annotations.

Usage

batch_processor_db(
  patient_vect,
  text_format,
  nlp_engine,
  URL,
  negex_simp,
  umls_selected,
  uri_fun,
  user,
  password,
  host,
  port,
  database,
  max_n_grams_length,
  negex_depth,
  select_cores
)

Arguments

patient_vect	Vector of patient ID's.
text_format	Text format.
nlp_engine	NLP engine, UDPipe only for now.
URL	UDPipe model URL.
negex_simp	Simplifed negex.
umls_selected	Processed UMLS table.
uri_fun	Uniform resource identifier (URI) string generating function for MongoDB credentials.
user	MongoDB user name.
password	MongoDB user password.
host	MongoDB host server.
port	MongoDB port.
database	MongoDB database name.
max_n_grams_length	Maximum length of tokens for matching with UMLS concept unique identifiers (CUI's). Shorter values will result in faster processing. If ) is chosen, UMLS CUI tags will not be provided.
negex_depth	Maximum distance between negation item and token to negate. Shorter distances will result in decreased sensitivity but increased specificity for negation.
select_cores	How many CPU cores should be used for parallel processing? Max allowed is total number of cores minus one. If 1 is entered, parallel processing will not be used.

CEDARS documentation built on Feb. 7, 2021, 5:06 p.m.