Description
This pipeline extracts Test entities from clinical texts and maps them to their corresponding Logical Observation Identifiers Names and Codes (LOINC) codes using sbiobert_base_cased_mli Sentence Bert Embeddings.
How to use
from sparknlp.pretrained import PretrainedPipeline
ner_pipeline = PretrainedPipeline("loinc_resolver_pipeline", "en", "clinical/models")
result = ner_pipeline.annotate("""A 65-year-old woman presents to the office with generalized fatigue for the last 4 months.
She used to walk 1 mile each evening but now gets tired after 1-2 blocks. She has a history of Crohn disease and hypertension
for which she receives appropriate medications. She is married and lives with her husband. She eats a balanced diet that
includes chicken, fish, pork, fruits, and vegetables. She rarely drinks alcohol and denies tobacco use. Vital signs are
within normal limits. A physical examination is unremarkable. Laboratory studies show the following: Hemoglobin: 9.8g/dL, Hematocrit: 32%, Mean Corpuscular Volume: 110 μm3""")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val ner_pipeline = PretrainedPipeline("loinc_resolver_pipeline", "en", "clinical/models")
val result = ner_pipeline.annotate("""A 65-year-old woman presents to the office with generalized fatigue for the last 4 months.
She used to walk 1 mile each evening but now gets tired after 1-2 blocks. She has a history of Crohn disease and hypertension
for which she receives appropriate medications. She is married and lives with her husband. She eats a balanced diet that
includes chicken, fish, pork, fruits, and vegetables. She rarely drinks alcohol and denies tobacco use. Vital signs are
within normal limits. A physical examination is unremarkable. Laboratory studies show the following: Hemoglobin: 9.8g/dL, Hematocrit: 32%, Mean Corpuscular Volume: 110 μm3""")
Results
+-----------------------+-----+----------+----------------------------------------------------------------------+----------------------------------------------------------------------+----------------------------------------------------------------------+
| chunk|label|loinc_code| resolution| all_codes| all_resolutions|
+-----------------------+-----+----------+----------------------------------------------------------------------+----------------------------------------------------------------------+----------------------------------------------------------------------+
| Vital signs| Test| 8716-3| Vital signs [Vital signs]|8716-3:::67801-1:::80339-5:::34566-0:::29274-8:::95634-2:::31210-8:...|Vital signs [Vital signs]:::EMS vital signs [EMS vital signs]:::Vit...|
| A physical examination| Test| LP7801-6| Physical exam [Physical exam]|LP7801-6:::55286-9:::11384-5:::67668-4:::100223-7:::29545-1:::79897...|Physical exam [Physical exam]:::Physical examination by body areas ...|
| Laboratory studies| Test| 26436-6| Laboratory studies [Laboratory studies]|26436-6:::LP36394-2:::52482-7:::ATTACH.LAB:::11502-2:::LA7451-3:::3...|Laboratory studies [Laboratory studies]:::Laboratory device [Labora...|
| Hemoglobin| Test| 14775-1| Hemoglobin [Hemoglobin]|14775-1:::LP30929-1:::34663-5:::18277-4:::10346-5:::LP30932-5:::532...|Hemoglobin [Hemoglobin]:::Hemoglobin G [Hemoglobin G]:::Hemoglobin ...|
| Hematocrit| Test| 11151-8| Hematocrit [Hematocrit]|11151-8:::16931-8:::32354-3:::20570-8:::11153-4:::39227-4:::42908-4...|Hematocrit [Hematocrit]:::Hematocrit/Hemoglobin [Hematocrit/Hemoglo...|
|Mean Corpuscular Volume| Test| 11272-2|Erythrocyte mean corpuscular volume [Erythrocyte mean corpuscular v...|11272-2:::30386-7:::48706-6:::30899-9:::51641-9:::33878-0:::LP15006...|Erythrocyte mean corpuscular volume [Erythrocyte mean corpuscular v...|
+-----------------------+-----+----------+----------------------------------------------------------------------+----------------------------------------------------------------------+----------------------------------------------------------------------+
Model Information
| Model Name: | loinc_resolver_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 5.2.1+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 3.0 GB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverterInternalModel
- MedicalNerModel
- NerConverterInternalModel
- ChunkMergeModel
- Chunk2Doc
- BertSentenceEmbeddings
- SentenceEntityResolverModel