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.
Predicted Entities
PROCEDURE
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