updated md cards (#1117)

Author: akrztrk

docs/_posts/HashamUlHaq/2021-04-01-ner_ade_clinical_en.md

@@ -116,18 +116,19 @@ val result = model.transform(Seq("Hypersensitivity to aspirin can be manifested
 import nlu
 nlu.load("en.med_ner.ade.clinical").predict("""Hypersensitivity to aspirin can be manifested as acute asthma, urticaria and/or angioedema, or a systemic anaphylactoid reaction.""")
 ```
+</div>
 
-## Results
+## Result
 
 ```bash
 +-------------------------------+-----+---+---------+
-|                          chunk|begin|end|ner_label|
+|chunk                          |begin|end|ner_label|
 +-------------------------------+-----+---+---------+
-|                        aspirin|   20| 26|     DRUG|
-|                   acute asthma|   49| 60|      ADE|
-|                      urticaria|   63| 71|      ADE|
-|                     angioedema|   80| 89|      ADE|
-|systemic anaphylactoid reaction|   97|127|      ADE|
+|aspirin                        |20   |26 |DRUG     |
+|acute asthma                   |49   |60 |ADE      |
+|urticaria                      |63   |71 |ADE      |
+|angioedema                     |80   |89 |ADE      |
+|systemic anaphylactoid reaction|97   |127|ADE      |
 +-------------------------------+-----+---+---------+
 ```
 

docs/_posts/akrztrk/2024-03-14-meddra_llt_icd10_mapper_en.md

@@ -55,7 +55,7 @@ mapper_pipeline = Pipeline(stages=[
     mapperModel
 ])
 
-data = spark.createDataFrame([["10045275.0"], ["10067585.0"], ["10026182.0"]]).toDF("text")
+data = spark.createDataFrame([["10045275"], ["10067585"], ["10026182"]]).toDF("text")
 
 mapper_model = mapper_pipeline.fit(data)
 result = mapper_model.transform(data)
@@ -81,7 +81,7 @@ val mapper_pipeline = new Pipeline().setStages(Array(
     mapperModel
 )
 
-val data = Seq("10045275.0", "10067585.0", "10026182.0").toDF("text")
+val data = Seq("10045275", "10067585", "10026182").toDF("text")
 
 val mapper_model = mapper_pipeline.fit(data)
 val result = mapper_model.transform(data)

docs/_posts/akrztrk/2024-03-15-meddra_pt_icd10_mapper_en.md

@@ -55,7 +55,7 @@ mapper_pipeline = Pipeline(stages=[
     mapperModel
 ])
 
-data = spark.createDataFrame([["10000153.0"], ["10000081.0"], ["10039085.0"]]).toDF("text")
+data = spark.createDataFrame([["10000153"], ["10000081"], ["10039085"]]).toDF("text")
 
 mapper_model = mapper_pipeline.fit(data)
 result = mapper_model.transform(data)
@@ -81,7 +81,7 @@ val mapper_pipeline = new Pipeline().setStages(Array(
     mapperModel
 ))
 
-val data = Seq("10000153.0", "10000081.0", "10039085.0").toDF("text")
+val data = Seq("10000153", "10000081", "10039085").toDF("text")
 
 val mapper_model = mapper_pipeline.fit(data)
 val result = mapper_model.transform(data)