Description
This pretrained model maps HPO codes to their associated genes and further maps those genes to related diseases.
How to use
document_assembler = DocumentAssembler()\
.setInputCol("text")\
.setOutputCol("document")
chunk_assembler = Doc2Chunk()\
.setInputCols(["document"])\
.setOutputCol("hpo_code")
mapperModel = ChunkMapperModel.pretrained("hpo_code_gene_disease_mapper", "en", "clinical/models")\
.setInputCols(["hpo_code"])\
.setOutputCol("mappings")\
.setRels(["hpo_gene_disease"])
mapper_pipeline = Pipeline(stages=[
document_assembler,
chunk_assembler,
mapperModel
])
data = spark.createDataFrame([["HP:0000002"],["HP:6001080"],["HP:0009484"]]).toDF("text")
result = mapper_pipeline.fit(data).transform(data)
document_assembler = nlp.DocumentAssembler()\
.setInputCol("text")\
.setOutputCol("document")
chunk_assembler = nlp.Doc2Chunk()\
.setInputCols(["document"])\
.setOutputCol("hpo_code")
mapperModel = medical.ChunkMapperModel.pretrained("hpo_code_gene_disease_mapper", "en", "clinical/models")\
.setInputCols(["hpo_code"])\
.setOutputCol("mappings")\
.setRels(["hpo_gene_disease"])
mapper_pipeline = nlp.Pipeline(stages=[
document_assembler,
chunk_assembler,
mapperModel
])
data = spark.createDataFrame([["HP:0000002"],["HP:6001080"],["HP:0009484"]]).toDF("text")
result = mapper_pipeline.fit(data).transform(data)
val document_assembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val chunk_assembler = new Doc2Chunk()
.setInputCols("document")
.setOutputCol("hpo_code")
val mapperModel = ChunkMapperModel.pretrained("hpo_code_gene_disease_mapper", "en", "clinical/models")
.setInputCols("hpo_code")
.setOutputCol("mappings")
.setRels(Array("hpo_gene_disease"))
val mapper_pipeline = new Pipeline().setStages(Array(
document_assembler,
chunk_assembler,
mapperModel
))
val data = Seq(("HP:0000002"),("HP:6001080"),("HP:0009484")).toDF("text")
val result = mapper_pipeline.fit(data).transform(data)
Results
+----------+------------------------------------------------------------------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------+
| hpo_code| gene_disease| all_k_resolutions|
+----------+------------------------------------------------------------------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------+
|HP:0000002|{"DUSP6": ["eunuchoid habitus", "gait disturbance", "seizure", "hypotonia", "ataxia", "dysarthria", "decreased testic...|{"DUSP6": ["eunuchoid habitus", "gait disturbance", "seizure", "hypotonia", "ataxia", "dysarthria", "decreased testic...|
|HP:6001080|{"HSD11B1": ["autosomal dominant inheritance", "low tetrahydrocortisol (thf) plus 5-alpha-thf/tetrahydrocortisone (th...|{"HSD11B1": ["autosomal dominant inheritance", "low tetrahydrocortisol (thf) plus 5-alpha-thf/tetrahydrocortisone (th...|
|HP:0009484|{"SHH": ["abnormal thumb morphology", "hand polydactyly", "poor speech", "expressive language delay", "limb dystonia"...|{"SHH": ["abnormal thumb morphology", "hand polydactyly", "poor speech", "expressive language delay", "limb dystonia"...|
+----------+------------------------------------------------------------------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------+
Model Information
| Model Name: | hpo_code_gene_disease_mapper |
| Compatibility: | Healthcare NLP 6.0.4+ |
| License: | Licensed |
| Edition: | Official |
| Input Labels: | [ner_chunk] |
| Output Labels: | [mappings] |
| Language: | en |
| Size: | 113.2 MB |