Description
This pretrained pipeline is built on the top of ner_covid_trials model.
Predicted Entities
Physiological_reaction, N_Patients, Treatment, Biological_molecules, Death_Entity, Route, Admission_Discharge, Drug_Ingredient, Statistical_Indicator, Cellular_component, Date, Heart_Disease, Viral_components, Virus, Respiration, VS_Finding, Age, Vaccine_Name, BMI, Trial_Design, Institution, Section_Header, Vaccine, Disease_Syndrome_Disorder, Gender, Pulse, Total_Cholesterol, Cerebrovascular_Disease, Diabetes, Stage, Employment, Cell_Type, Frequency, Time, Obesity, Dosage, Trial_Phase, Severity, Race_Ethnicity, Hypertension, Smoking
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("ner_covid_trials_pipeline", "en", "clinical/models")
text = '''In December 2019 , a group of patients with the acute respiratory disease was detected in Wuhan , Hubei Province of China . A month later , a new beta-coronavirus was identified as the cause of the 2019 coronavirus infection . SARS-CoV-2 is a coronavirus that belongs to the group of β-coronaviruses of the subgenus Coronaviridae . The SARS-CoV-2 is the third known zoonotic coronavirus disease after severe acute respiratory syndrome ( SARS ) and Middle Eastern respiratory syndrome ( MERS ). The diagnosis of SARS-CoV-2 recommended by the WHO , CDC is the collection of a sample from the upper respiratory tract ( nasal and oropharyngeal exudate ) or from the lower respiratory tractsuch as expectoration of endotracheal aspirate and bronchioloalveolar lavage and its analysis using the test of real-time polymerase chain reaction ( qRT-PCR ).In 2020, the first COVID‑19 vaccine was developed and made available to the public through emergency authorizations and conditional approvals.'''
result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("ner_covid_trials_pipeline", "en", "clinical/models")
val text = "In December 2019 , a group of patients with the acute respiratory disease was detected in Wuhan , Hubei Province of China . A month later , a new beta-coronavirus was identified as the cause of the 2019 coronavirus infection . SARS-CoV-2 is a coronavirus that belongs to the group of β-coronaviruses of the subgenus Coronaviridae . The SARS-CoV-2 is the third known zoonotic coronavirus disease after severe acute respiratory syndrome ( SARS ) and Middle Eastern respiratory syndrome ( MERS ). The diagnosis of SARS-CoV-2 recommended by the WHO , CDC is the collection of a sample from the upper respiratory tract ( nasal and oropharyngeal exudate ) or from the lower respiratory tractsuch as expectoration of endotracheal aspirate and bronchioloalveolar lavage and its analysis using the test of real-time polymerase chain reaction ( qRT-PCR ).In 2020, the first COVID‑19 vaccine was developed and made available to the public through emergency authorizations and conditional approvals."
val result = pipeline.fullAnnotate(text)
Results
| | ner_chunks | begin | end | ner_label | confidence |
|---:|:------------------------------------|--------:|------:|:--------------------------|-------------:|
| 0 | December 2019 | 3 | 15 | Date | 0.99655 |
| 1 | acute respiratory disease | 48 | 72 | Disease_Syndrome_Disorder | 0.8597 |
| 2 | beta-coronavirus | 146 | 161 | Virus | 0.6381 |
| 3 | 2019 | 198 | 201 | Date | 0.8117 |
| 4 | coronavirus infection | 203 | 223 | Disease_Syndrome_Disorder | 0.68335 |
| 5 | SARS-CoV-2 | 227 | 236 | Virus | 0.9605 |
| 6 | coronavirus | 243 | 253 | Virus | 0.9814 |
| 7 | β-coronaviruses | 284 | 298 | Virus | 0.9564 |
| 8 | subgenus Coronaviridae | 307 | 328 | Virus | 0.71465 |
| 9 | SARS-CoV-2 | 336 | 345 | Virus | 0.9442 |
| 10 | zoonotic coronavirus disease | 366 | 393 | Disease_Syndrome_Disorder | 0.922833 |
| 11 | severe acute respiratory syndrome | 401 | 433 | Disease_Syndrome_Disorder | 0.959725 |
| 12 | SARS | 437 | 440 | Disease_Syndrome_Disorder | 0.9959 |
| 13 | Middle Eastern respiratory syndrome | 448 | 482 | Disease_Syndrome_Disorder | 0.9673 |
| 14 | MERS | 486 | 489 | Disease_Syndrome_Disorder | 0.9759 |
| 15 | SARS-CoV-2 | 511 | 520 | Virus | 0.9027 |
| 16 | WHO | 541 | 543 | Institution | 0.9917 |
| 17 | CDC | 547 | 549 | Institution | 0.8296 |
| 18 | 2020 | 848 | 851 | Date | 0.9997 |
| 19 | COVID‑19 vaccine | 864 | 879 | Vaccine_Name | 0.87505 |
Model Information
| Model Name: | ner_covid_trials_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 4.3.0+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.7 GB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverterInternalModel