Spaces:
Sleeping
Sleeping
Wilame Lima
commited on
Commit
•
95a5eb7
1
Parent(s):
9d8505b
add reference and change example text
Browse files
app.py
CHANGED
@@ -5,10 +5,12 @@ st.sidebar.title(DASHBOARD_TITLE)
|
|
5 |
|
6 |
# add an explanation of what is NER and why it is important for medical tasks
|
7 |
st.sidebar.markdown(
|
8 |
-
"""
|
9 |
Named Entity Recognition (NER) is a subtask of information extraction that locates and classifies named entities mentioned in unstructured text into pre-defined categories such as the names of persons, organizations, locations, expressions of times, quantities, monetary values, percentages, etc.
|
10 |
|
11 |
In the medical domain, NER can be used to extract entities such as symptoms, diseases, treatments, and more. This can be useful for various tasks such as clinical decision support, medical coding, and more.
|
|
|
|
|
12 |
"""
|
13 |
)
|
14 |
|
|
|
5 |
|
6 |
# add an explanation of what is NER and why it is important for medical tasks
|
7 |
st.sidebar.markdown(
|
8 |
+
f"""
|
9 |
Named Entity Recognition (NER) is a subtask of information extraction that locates and classifies named entities mentioned in unstructured text into pre-defined categories such as the names of persons, organizations, locations, expressions of times, quantities, monetary values, percentages, etc.
|
10 |
|
11 |
In the medical domain, NER can be used to extract entities such as symptoms, diseases, treatments, and more. This can be useful for various tasks such as clinical decision support, medical coding, and more.
|
12 |
+
|
13 |
+
Model used: [{MODEL_PATH}]({MODEL_LINK})
|
14 |
"""
|
15 |
)
|
16 |
|
config.py
CHANGED
@@ -5,3 +5,4 @@ from annotated_text import annotated_text
|
|
5 |
|
6 |
DASHBOARD_TITLE = "Medical NER Dashboard"
|
7 |
MODEL_PATH = "Clinical-AI-Apollo/Medical-NER"
|
|
|
|
5 |
|
6 |
DASHBOARD_TITLE = "Medical NER Dashboard"
|
7 |
MODEL_PATH = "Clinical-AI-Apollo/Medical-NER"
|
8 |
+
MODEL_LINK = "https://huggingface.co/Clinical-AI-Apollo/Medical-NER"
|