Pipeline for Healthcare Common Procedure Coding System (HCPCS)

Description

This pipeline extracts PROCEDURE entities and maps them to their corresponding Healthcare Common Procedure Coding System (HCPCS) codes using ‘sbiobert_base_cased_mli’ sentence embeddings.

Copy S3 URI

How to use


from sparknlp.pretrained import PretrainedPipeline

hcpcs_pipeline = PretrainedPipeline("hcpcs_resolver_pipeline", "en", "clinical/models")

text = """Mary received a mechanical prosthetic heart valve in June 2020, and the results were successful. Diabetes screening test performed, revealing abnormal result. She uses infusion pump for diabetes and a CPAP machine for sleep apnea. In 2021, She received a breast prosthesis implant."""

result = hcpcs_pipeline.fullAnnotate(text)


import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline

val hcpcs_pipeline = PretrainedPipeline("hcpcs_resolver_pipeline", "en", "clinical/models")

val text = """Mary received a mechanical prosthetic heart valve in June 2020, and the results were successful. Diabetes screening test performed, revealing abnormal result. She uses infusion pump for diabetes and a CPAP machine for sleep apnea. In 2021, She received a breast prosthesis implant."""

val result = hcpcs_pipeline.fullAnnotate(text)

Results


+-----------------------------------+-----+---+-----+-----------------------------------------------------------------+-----------------------------------------------------------------+-----------------------------------------------------------------+
|                             chunks|begin|end| code|                                                        all_codes|                                                      resolutions|                                                    all_distances|
+-----------------------------------+-----+---+-----+-----------------------------------------------------------------+-----------------------------------------------------------------+-----------------------------------------------------------------+
|a mechanical prosthetic heart valve|   14| 48|G0043|[G0043, C1824, L8698, Q0508, C1764, C1883,    AV, V5095, L8699...|[Patients with mechanical prosthetic heart valve, Generator, c...|[0.0384, 0.2283, 0.2375, 0.2393, 0.2434, 0.2587, 0.2515, 0.262...|
|                      infusion pump|  169|181|C1772|[C1772,    JA, C1754, A4220,    SH, B9004, S9007, B9002, C1887...|[Infusion pump, programmable (implantable), Administered intra...|[0.1408, 0.1777, 0.1990, 0.2107, 0.2175, 0.2166, 0.2214, 0.221...|
|                     a CPAP machine|  200|213|E0601|[E0601, Q4246, E0570, E0860, E0942, E0457, C1880, L0972, L0970...|[Continuous positive airway pressure (cpap) device, Coretext o...|[0.1952, 0.2380, 0.2519, 0.2630, 0.2775, 0.2791, 0.2832, 0.304...|
|        a breast prosthesis implant|  254|280|C1789|[C1789, L8600, L8010, L8020, L8031, L8039, A4282, A4281, G9829...|[Prosthesis, breast (implantable), Implantable breast prosthes...|[0.0798, 0.1202, 0.1495, 0.1604, 0.1704, 0.1712, 0.1984, 0.226...|
+-----------------------------------+-----+---+-----+-----------------------------------------------------------------+-----------------------------------------------------------------+-----------------------------------------------------------------+

Model Information

Model Name: hcpcs_resolver_pipeline
Type: pipeline
Compatibility: Healthcare NLP 5.2.1+
License: Licensed
Edition: Official
Language: en
Size: 2.2 GB

Included Models

  • DocumentAssembler
  • SentenceDetectorDLModel
  • TokenizerModel
  • WordEmbeddingsModel
  • MedicalNerModel
  • NerConverterInternalModel
  • MedicalNerModel
  • NerConverterInternalModel
  • ChunkMergeModel
  • Chunk2Doc
  • BertSentenceEmbeddings
  • SentenceEntityResolverModel