Description
This pretrained pipeline is a text-only version built on top of the jsl_meds_ner_vlm_2b_q16_v2 model.
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("jsl_meds_ner_2b_q16_v2_pipeline", "en", "clinical/models")
text = """
# Template:
{
"Patient Name": "string",
"Patient Age": "integer",
"Patient Gender": "string",
"Hospital Number": "string",
"Episode Number": "string",
"Episode Date": "date-time"
}
# Context:
The patient, Johnathan Miller, is a 54-year-old male admitted under hospital number HN382914.
His most recent episode number is EP2024-1178, recorded on 2025-08-10.
The patient presented with chronic knee pain and swelling.
Past medical history includes hypertension and type 2 diabetes.
"""
result = pipeline.fullAnnotate(text)
from johnsnowlabs import nlp, medical
pipeline = nlp.PretrainedPipeline("jsl_meds_ner_2b_q16_v2_pipeline", "en", "clinical/models")
text = """
# Template:
{
"Patient Name": "string",
"Patient Age": "integer",
"Patient Gender": "string",
"Hospital Number": "string",
"Episode Number": "string",
"Episode Date": "date-time"
}
# Context:
The patient, Johnathan Miller, is a 54-year-old male admitted under hospital number HN382914.
His most recent episode number is EP2024-1178, recorded on 2025-08-10.
The patient presented with chronic knee pain and swelling.
Past medical history includes hypertension and type 2 diabetes.
"""
result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("jsl_meds_ner_2b_q16_v2_pipeline", "en", "clinical/models")
val text = """
# Template:
{
"Patient Name": "string",
"Patient Age": "integer",
"Patient Gender": "string",
"Hospital Number": "string",
"Episode Number": "string",
"Episode Date": "date-time"
}
# Context:
The patient, Johnathan Miller, is a 54-year-old male admitted under hospital number HN382914.
His most recent episode number is EP2024-1178, recorded on 2025-08-10.
The patient presented with chronic knee pain and swelling.
Past medical history includes hypertension and type 2 diabetes.
"""
val result = pipeline.fullAnnotate(text)
Results
{
"Patient Name": "Johnathan Miller",
"Patient Age": 54,
"Patient Gender": "male",
"Hospital Number": "HN382914",
"Episode Number": "EP2024-1178",
"Episode Date": "2025-08-10"
}
Model Information
| Model Name: | jsl_meds_ner_2b_q16_v2_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 6.1.0+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 2.5 GB |
Included Models
- DocumentAssembler
- MedicalLLM