Description
This pipeline is designed to:
- extract clinical entities
- assign assertion status to the extracted entities
- establish relations between the extracted entities
from clinical texts. In this pipeline, ner_jsl NER model, assertion_jsl assertion model, re_test_result_date, and posology_re relation extraction models were used to achieve those tasks. Here are the NER, assertion, and relation extraction labels this pipeline can extract. Here are the NER, assertion, and relation extraction labels this pipeline can extract.
-
Clinical Entity Labels:
Admission_DischargeAgeAlcoholAllergenBMIBirth_EntityBlood_PressureCerebrovascular_DiseaseClinical_DeptCommunicable_DiseaseDateDeath_EntityDiabetesDietDirectionDisease_Syndrome_DisorderDosageDrug_BrandNameDrug_IngredientDurationEKG_FindingsEmploymentExternal_body_part_or_regionFamily_History_HeaderFetus_NewBornFormFrequencyGenderHDLHeart_DiseaseHeightHyperlipidemiaHypertensionImagingFindingsImaging_TechniqueInjury_or_PoisoningInternal_organ_or_componentKidney_DiseaseLDLLabour_DeliveryMedical_DeviceMedical_History_HeaderModifierO2_SaturationObesityOncologicalOverweightOxygen_TherapyPregnancyProcedurePsychological_ConditionPulseRace_EthnicityRelationship_StatusRelativeDateRelativeTimeRespirationRouteSection_HeaderSexually_Active_or_Sexual_OrientationSmokingSocial_History_HeaderStrengthSubstanceSubstance_QuantitySymptomTemperatureTestTest_ResultTimeTotal_CholesterolTreatmentTriglyceridesVS_FindingVaccineVaccine_NameVital_Signs_HeaderWeight -
Assertion Status Labels:
Hypothetical,Someoneelse,Past,Absent,Family,Planned,Possible,Present -
Relation Extraction Labels:
is_finding_of,is_date_of,is_result_of,Drug_BrandName-Dosage,Drug_BrandName-Frequency,Drug_BrandName-Route,Drug_BrandName-Strength,Drug_Ingredient-Dosage,Drug_Ingredient-Frequency,Drug_Ingredient-Route,Drug_Ingredient-Strength,O
Predicted Entities
Admission_Discharge, Age, Alcohol, Allergen, BMI, Birth_Entity, Blood_Pressure, Cerebrovascular_Disease, Clinical_Dept, Communicable_Disease, Date, Death_Entity, Diabetes, Diet, Direction, Disease_Syndrome_Disorder, Dosage, Drug_BrandName, Drug_Ingredient, Duration, EKG_Findings, Employment, External_body_part_or_region, Family_History_Header, Fetus_NewBorn, Form, Frequency, Gender, HDL, Heart_Disease, Height, Hyperlipidemia, Hypertension, ImagingFindings, Imaging_Technique, Injury_or_Poisoning, Internal_organ_or_component, Kidney_Disease, LDL, Labour_Delivery, Medical_Device, Medical_History_Header, Modifier, O2_Saturation, Obesity, Oncological, Overweight, Oxygen_Therapy, Pregnancy, Procedure, Psychological_Condition, Pulse, Race_Ethnicity, Relationship_Status, RelativeDate, RelativeTime, Respiration, Route, Section_Header, Sexually_Active_or_Sexual_Orientation, Smoking, Social_History_Header, Strength, Substance, Substance_Quantity, Symptom, Temperature, Test, Test_Result, Time, Total_Cholesterol, Treatment, Triglycerides, VS_Finding, Vaccine, Vaccine_Name, Vital_Signs_Header, Weight
How to use
from sparknlp.pretrained import PretrainedPipeline
ner_pipeline = PretrainedPipeline("explain_clinical_doc_granular", "en", "clinical/models")
result = ner_pipeline.annotate("""The patient admitted for gastrointestinal pathology, under working treatment.
History of prior heart murmur with echocardiogram findings as above on March 1998.
According to the latest echocardiogram, basically revealed normal left ventricular function with left atrial enlargement .
Based on the above findings, we will treat her medically with ACE inhibitors 10 mg, p.o, daily. Also we will give Furosemide 40 mg, p.o later and see how she fares.""")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val ner_pipeline = PretrainedPipeline("explain_clinical_doc_granular", "en", "clinical/models")
val result = ner_pipeline.annotate("""The patient admitted for gastrointestinal pathology, under working treatment.
History of prior heart murmur with echocardiogram findings as above on March 1998.
According to the latest echocardiogram, basically revealed normal left ventricular function with left atrial enlargement .
Based on the above findings, we will treat her medically with ACE inhibitors 10 mg, p.o, daily. Also we will give Furosemide 40 mg, p.o later and see how she fares.""")
Results
# ner
+-----------+-----+---+--------------------------+-------------------+
|sentence_id|begin|end|entity |label |
+-----------+-----+---+--------------------------+-------------------+
|0 |12 |19 |admitted |Admission_Discharge|
|0 |25 |50 |gastrointestinal pathology|Clinical_Dept |
|1 |95 |106|heart murmur |Heart_Disease |
|1 |113 |126|echocardiogram |Test |
|1 |149 |158|March 1998 |Date |
|2 |185 |198|echocardiogram |Test |
|2 |220 |225|normal |Test_Result |
|2 |227 |251|left ventricular function |Test |
|2 |258 |280|left atrial enlargement |Heart_Disease |
|3 |327 |329|her |Gender |
|3 |346 |359|ACE inhibitors |Drug_Ingredient |
|3 |361 |365|10 mg |Strength |
|3 |368 |370|p.o |Route |
|3 |373 |377|daily |Frequency |
|4 |398 |407|Furosemide |Drug_Ingredient |
|4 |409 |413|40 mg |Strength |
|4 |416 |418|p.o |Route |
|4 |438 |440|she |Gender |
+-----------+-----+---+--------------------------+-------------------+
# assertion
+-----------+-----+---+-------------------------+---------------+----------------+
|sentence_id|begin|end|entity |label |assertion_status|
+-----------+-----+---+-------------------------+---------------+----------------+
|1 |95 |106|heart murmur |Heart_Disease |Past |
|1 |113 |126|echocardiogram |Test |Past |
|2 |185 |198|echocardiogram |Test |Present |
|2 |220 |225|normal |Test_Result |Present |
|2 |227 |251|left ventricular function|Test |Present |
|2 |258 |280|left atrial enlargement |Heart_Disease |Present |
|3 |346 |359|ACE inhibitors |Drug_Ingredient|Planned |
|4 |398 |407|Furosemide |Drug_Ingredient|Planned |
+-----------+-----+---+-------------------------+---------------+----------------+
# relation
+-----------+-------------------------+---------------------+-------------------------+---------------------+-------------------------+--------------------------+----------------------------------+---------------------------------+----------------------------------+---------------------------------+-------------------------+--------------------------+-------------------------+--------------------------+-------------------------+
|sentence_id|all_relations |all_relations_entity1|all_relations_chunk1 |all_relations_entity2|all_relations_chunk2 |test_result_date_relations|test_result_date_relations_entity1|test_result_date_relations_chunk1|test_result_date_relations_entity2|test_result_date_relations_chunk2|posology_relations |posology_relations_entity1|posology_relations_chunk1|posology_relations_entity2|posology_relations_chunk2|
+-----------+-------------------------+---------------------+-------------------------+---------------------+-------------------------+--------------------------+----------------------------------+---------------------------------+----------------------------------+---------------------------------+-------------------------+--------------------------+-------------------------+--------------------------+-------------------------+
|1 |is_finding_of |Heart_Disease |heart murmur |Test |echocardiogram |is_finding_of |Heart_Disease |heart murmur |Test |echocardiogram |Drug_Ingredient-Strength |Drug_Ingredient |ACE inhibitors |Strength |10 mg |
|1 |is_date_of |Heart_Disease |heart murmur |Date |March 1998 |is_date_of |Heart_Disease |heart murmur |Date |March 1998 |Drug_Ingredient-Route |Drug_Ingredient |ACE inhibitors |Route |p.o |
|1 |is_date_of |Test |echocardiogram |Date |March 1998 |is_date_of |Test |echocardiogram |Date |March 1998 |Drug_Ingredient-Frequency|Drug_Ingredient |ACE inhibitors |Frequency |daily |
|2 |is_finding_of |Test |echocardiogram |Heart_Disease |left atrial enlargement |is_finding_of |Test |echocardiogram |Heart_Disease |left atrial enlargement |Drug_Ingredient-Route |Drug_Ingredient |Furosemide |Route |p.o |
|2 |is_result_of |Test_Result |normal |Test |left ventricular function|is_result_of |Test_Result |normal |Test |left ventricular function |null |null |null |null |null |
|2 |is_finding_of |Test |left ventricular function|Heart_Disease |left atrial enlargement |is_finding_of |Test |left ventricular function |Heart_Disease |left atrial enlargement |null |null |null |null |null |
|3 |Drug_Ingredient-Strength |Drug_Ingredient |ACE inhibitors |Strength |10 mg |null |null |null |null |null |null |null |null |null |null |
|3 |Drug_Ingredient-Route |Drug_Ingredient |ACE inhibitors |Route |p.o |null |null |null |null |null |null |null |null |null |null |
|3 |Drug_Ingredient-Frequency|Drug_Ingredient |ACE inhibitors |Frequency |daily |null |null |null |null |null |null |null |null |null |null |
|4 |Drug_Ingredient-Strength |Drug_Ingredient |Furosemide |Strength |40 mg |null |null |null |null |null |null |null |null |null |null |
|4 |Drug_Ingredient-Route |Drug_Ingredient |Furosemide |Route |p.o |null |null |null |null |null |null |null |null |null |null |
+-----------+-------------------------+---------------------+-------------------------+---------------------+-------------------------+--------------------------+----------------------------------+---------------------------------+----------------------------------+---------------------------------+-------------------------+--------------------------+-------------------------+--------------------------+-------------------------+
Model Information
| Model Name: | explain_clinical_doc_granular |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 5.2.1+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.7 GB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverterInternalModel
- NerConverterInternalModel
- AssertionDLModel
- PerceptronModel
- DependencyParserModel
- RelationExtractionModel
- PosologyREModel
- AnnotationMerger