R/comprehendmedical_service.R

In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

# This file is generated by make.paws. Please do not edit here.
#' @importFrom paws.common new_handlers new_service set_config merge_config
NULL

#' AWS Comprehend Medical
#'
#' @description
#' Amazon Comprehend Medical extracts structured information from
#' unstructured clinical text. Use these actions to gain insight in your
#' documents. Amazon Comprehend Medical only detects entities in English
#' language texts. Amazon Comprehend Medical places limits on the sizes of
#' files allowed for different API operations. To learn more, see
#' [Guidelines and
#' quotas](https://docs.aws.amazon.com/comprehend-medical/latest/dev/comprehendmedical-quotas.html)
#' in the *Amazon Comprehend Medical Developer Guide*.
#'
#' @param
#' config
#' Optional configuration of credentials, endpoint, and/or region.
#' \itemize{
#' \item{\strong{credentials}:} {\itemize{
#' \item{\strong{creds}:} {\itemize{
#' \item{\strong{access_key_id}:} {AWS access key ID}
#' \item{\strong{secret_access_key}:} {AWS secret access key}
#' \item{\strong{session_token}:} {AWS temporary session token}
#' }}
#' \item{\strong{profile}:} {The name of a profile to use. If not given, then the default profile is used.}
#' \item{\strong{anonymous}:} {Set anonymous credentials.}
#' \item{\strong{endpoint}:} {The complete URL to use for the constructed client.}
#' \item{\strong{region}:} {The AWS Region used in instantiating the client.}
#' }}
#' \item{\strong{close_connection}:} {Immediately close all HTTP connections.}
#' \item{\strong{timeout}:} {The time in seconds till a timeout exception is thrown when attempting to make a connection. The default is 60 seconds.}
#' \item{\strong{s3_force_path_style}:} {Set this to `true` to force the request to use path-style addressing, i.e. `http://s3.amazonaws.com/BUCKET/KEY`.}
#' \item{\strong{sts_regional_endpoint}:} {Set sts regional endpoint resolver to regional or legacy \url{https://docs.aws.amazon.com/sdkref/latest/guide/feature-sts-regionalized-endpoints.html}}
#' }
#' @param
#' credentials
#' Optional credentials shorthand for the config parameter
#' \itemize{
#' \item{\strong{creds}:} {\itemize{
#' \item{\strong{access_key_id}:} {AWS access key ID}
#' \item{\strong{secret_access_key}:} {AWS secret access key}
#' \item{\strong{session_token}:} {AWS temporary session token}
#' }}
#' \item{\strong{profile}:} {The name of a profile to use. If not given, then the default profile is used.}
#' \item{\strong{anonymous}:} {Set anonymous credentials.}
#' }
#' @param
#' endpoint
#' Optional shorthand for complete URL to use for the constructed client.
#' @param
#' region
#' Optional shorthand for AWS Region used in instantiating the client.
#'
#' @section Service syntax:
#' ```
#' svc <- comprehendmedical(
#'   config = list(
#'     credentials = list(
#'       creds = list(
#'         access_key_id = "string",
#'         secret_access_key = "string",
#'         session_token = "string"
#'       ),
#'       profile = "string",
#'       anonymous = "logical"
#'     ),
#'     endpoint = "string",
#'     region = "string",
#'     close_connection = "logical",
#'     timeout = "numeric",
#'     s3_force_path_style = "logical",
#'     sts_regional_endpoint = "string"
#'   ),
#'   credentials = list(
#'     creds = list(
#'       access_key_id = "string",
#'       secret_access_key = "string",
#'       session_token = "string"
#'     ),
#'     profile = "string",
#'     anonymous = "logical"
#'   ),
#'   endpoint = "string",
#'   region = "string"
#' )
#' ```
#'
#' @examples
#' \dontrun{
#' svc <- comprehendmedical()
#' svc$describe_entities_detection_v2_job(
#'   Foo = 123
#' )
#' }
#'
#' @section Operations:
#' \tabular{ll}{
#'  \link[=comprehendmedical_describe_entities_detection_v2_job]{describe_entities_detection_v2_job} \tab Gets the properties associated with a medical entities detection job\cr
#'  \link[=comprehendmedical_describe_icd10cm_inference_job]{describe_icd10cm_inference_job} \tab Gets the properties associated with an InferICD10CM job\cr
#'  \link[=comprehendmedical_describe_phi_detection_job]{describe_phi_detection_job} \tab Gets the properties associated with a protected health information (PHI) detection job\cr
#'  \link[=comprehendmedical_describe_rx_norm_inference_job]{describe_rx_norm_inference_job} \tab Gets the properties associated with an InferRxNorm job\cr
#'  \link[=comprehendmedical_describe_snomedct_inference_job]{describe_snomedct_inference_job} \tab Gets the properties associated with an InferSNOMEDCT job\cr
#'  \link[=comprehendmedical_detect_entities]{detect_entities} \tab The DetectEntities operation is deprecated\cr
#'  \link[=comprehendmedical_detect_entities_v2]{detect_entities_v2} \tab Inspects the clinical text for a variety of medical entities and returns specific information about them such as entity category, location, and confidence score on that information\cr
#'  \link[=comprehendmedical_detect_phi]{detect_phi} \tab Inspects the clinical text for protected health information (PHI) entities and returns the entity category, location, and confidence score for each entity\cr
#'  \link[=comprehendmedical_infer_icd10cm]{infer_icd10cm} \tab InferICD10CM detects medical conditions as entities listed in a patient record and links those entities to normalized concept identifiers in the ICD-10-CM knowledge base from the Centers for Disease Control\cr
#'  \link[=comprehendmedical_infer_rx_norm]{infer_rx_norm} \tab InferRxNorm detects medications as entities listed in a patient record and links to the normalized concept identifiers in the RxNorm database from the National Library of Medicine\cr
#'  \link[=comprehendmedical_infer_snomedct]{infer_snomedct} \tab InferSNOMEDCT detects possible medical concepts as entities and links them to codes from the Systematized Nomenclature of Medicine, Clinical Terms (SNOMED-CT) ontology\cr
#'  \link[=comprehendmedical_list_entities_detection_v2_jobs]{list_entities_detection_v2_jobs} \tab Gets a list of medical entity detection jobs that you have submitted\cr
#'  \link[=comprehendmedical_list_icd10cm_inference_jobs]{list_icd10cm_inference_jobs} \tab Gets a list of InferICD10CM jobs that you have submitted\cr
#'  \link[=comprehendmedical_list_phi_detection_jobs]{list_phi_detection_jobs} \tab Gets a list of protected health information (PHI) detection jobs you have submitted\cr
#'  \link[=comprehendmedical_list_rx_norm_inference_jobs]{list_rx_norm_inference_jobs} \tab Gets a list of InferRxNorm jobs that you have submitted\cr
#'  \link[=comprehendmedical_list_snomedct_inference_jobs]{list_snomedct_inference_jobs} \tab Gets a list of InferSNOMEDCT jobs a user has submitted\cr
#'  \link[=comprehendmedical_start_entities_detection_v2_job]{start_entities_detection_v2_job} \tab Starts an asynchronous medical entity detection job for a collection of documents\cr
#'  \link[=comprehendmedical_start_icd10cm_inference_job]{start_icd10cm_inference_job} \tab Starts an asynchronous job to detect medical conditions and link them to the ICD-10-CM ontology\cr
#'  \link[=comprehendmedical_start_phi_detection_job]{start_phi_detection_job} \tab Starts an asynchronous job to detect protected health information (PHI)\cr
#'  \link[=comprehendmedical_start_rx_norm_inference_job]{start_rx_norm_inference_job} \tab Starts an asynchronous job to detect medication entities and link them to the RxNorm ontology\cr
#'  \link[=comprehendmedical_start_snomedct_inference_job]{start_snomedct_inference_job} \tab Starts an asynchronous job to detect medical concepts and link them to the SNOMED-CT ontology\cr
#'  \link[=comprehendmedical_stop_entities_detection_v2_job]{stop_entities_detection_v2_job} \tab Stops a medical entities detection job in progress\cr
#'  \link[=comprehendmedical_stop_icd10cm_inference_job]{stop_icd10cm_inference_job} \tab Stops an InferICD10CM inference job in progress\cr
#'  \link[=comprehendmedical_stop_phi_detection_job]{stop_phi_detection_job} \tab Stops a protected health information (PHI) detection job in progress\cr
#'  \link[=comprehendmedical_stop_rx_norm_inference_job]{stop_rx_norm_inference_job} \tab Stops an InferRxNorm inference job in progress\cr
#'  \link[=comprehendmedical_stop_snomedct_inference_job]{stop_snomedct_inference_job} \tab Stops an InferSNOMEDCT inference job in progress
#' }
#'
#' @return
#' A client for the service. You can call the service's operations using
#' syntax like `svc$operation(...)`, where `svc` is the name you've assigned
#' to the client. The available operations are listed in the
#' Operations section.
#'
#' @rdname comprehendmedical
#' @export
comprehendmedical <- function(config = list(), credentials = list(), endpoint = NULL, region = NULL) {
  config <- merge_config(
    config,
    list(
      credentials = credentials,
      endpoint = endpoint,
      region = region
    )
  )
  svc <- .comprehendmedical$operations
  svc <- set_config(svc, config)
  return(svc)
}

# Private API objects: metadata, handlers, interfaces, etc.
.comprehendmedical <- list()

.comprehendmedical$operations <- list()

.comprehendmedical$metadata <- list(
  service_name = "comprehendmedical",
  endpoints = list("*" = list(endpoint = "comprehendmedical.{region}.amazonaws.com", global = FALSE), "cn-*" = list(endpoint = "comprehendmedical.{region}.amazonaws.com.cn", global = FALSE), "us-iso-*" = list(endpoint = "comprehendmedical.{region}.c2s.ic.gov", global = FALSE), "us-isob-*" = list(endpoint = "comprehendmedical.{region}.sc2s.sgov.gov", global = FALSE)),
  service_id = "ComprehendMedical",
  api_version = "2018-10-30",
  signing_name = "comprehendmedical",
  json_version = "1.1",
  target_prefix = "ComprehendMedical_20181030"
)

.comprehendmedical$service <- function(config = list()) {
  handlers <- new_handlers("jsonrpc", "v4")
  new_service(.comprehendmedical$metadata, handlers, config)
}