wzkariampuzha commited on
Commit
0b17811
1 Parent(s): 9b4d781

Update app.py

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Files changed (1) hide show
  1. app.py +25 -16
app.py CHANGED
@@ -121,13 +121,31 @@ if disease_or_gard_id:
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  NER_pipeline, entity_classes,
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  extract_diseases,GARD_dict, max_length,
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  classify_model_vars)
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- st.dataframe(df, height=100)
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- st.markdown(df.columns)
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- st.markdown('''COLUMNS:
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- - PROB_OF_EPI: Probability that the paper is an epidemiologic study based on its abstract.
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- - IsEpi: If it is an epidemiologic study (If PROB_OF_EPI >0.5)
 
 
 
 
 
 
 
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  - DIS: Rare disease terms or synonyms identified in the abstract from the GARD Dictionary
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- - IDS: GARD IDs identified in the abstract from the GARD Dictionary
 
 
 
 
 
 
 
 
 
 
 
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  - EPI: Epidemiology Types are the metrics used to estimate disease burden such as "incidence", "prevalence rate", or "occurrence"
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  - STAT: Epidemiology Rates describe how many people are afflicted by a disease.
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  - DATE: The dates when the epidemiologic studies were conducted
@@ -135,16 +153,7 @@ if disease_or_gard_id:
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  - SEX: The biological sexes mentioned in the abstract. Useful for diseases that disproportionately affect one sex over the other or may provide context to composition of the study population
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  - ETHN: Ethnicities, races, and nationalities of those represented in the epidemiologic study.
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  ''')
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- csv = convert_df(df)
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- st.download_button(
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- label="Download epidemiology results for "+disease_or_gard_id+" as CSV",
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- data = csv,
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- file_name=disease_or_gard_id+'.csv',
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- mime='text/csv',
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- )
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  #st.dataframe(data=None, width=None, height=None)
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  fig = epi_sankey(sankey_data,disease_or_gard_id)
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- #if st.button('Display Sankey Diagram of Automated Search'):
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- st.plotly_chart(fig, use_container_width=True)
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- # st.code(body, language="python")
 
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  NER_pipeline, entity_classes,
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  extract_diseases,GARD_dict, max_length,
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  classify_model_vars)
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+ st.dataframe(df, height=200)
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+ csv = convert_df(df)
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+ st.download_button(
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+ label="Download epidemiology results for "+disease_or_gard_id+" as CSV",
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+ data = csv,
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+ file_name=disease_or_gard_id+'.csv',
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+ mime='text/csv',
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+ )
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+ if 'IDS' in list(df.columns):
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+ st.markdown('''COLUMNS: \\
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+ - PROB_OF_EPI: Probability that the paper is an epidemiologic study based on its abstract. \\
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+ - IsEpi: If it is an epidemiologic study (If PROB_OF_EPI >0.5) \\
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  - DIS: Rare disease terms or synonyms identified in the abstract from the GARD Dictionary
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+ - IDS: GARD IDs identified in the abstract from the GARD Dictionary \\
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+ - EPI: Epidemiology Types are the metrics used to estimate disease burden such as "incidence", "prevalence rate", or "occurrence"
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+ - STAT: Epidemiology Rates describe how many people are afflicted by a disease.
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+ - DATE: The dates when the epidemiologic studies were conducted
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+ - LOC: Where the epidemiologic studies were conducted.
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+ - SEX: The biological sexes mentioned in the abstract. Useful for diseases that disproportionately affect one sex over the other or may provide context to composition of the study population
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+ - ETHN: Ethnicities, races, and nationalities of those represented in the epidemiologic study.
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+ ''')
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+ else:
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+ st.markdown('''COLUMNS: \\
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+ - PROB_OF_EPI: Probability that the paper is an epidemiologic study based on its abstract. \\
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+ - IsEpi: If it is an epidemiologic study (If PROB_OF_EPI >0.5) \\
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  - EPI: Epidemiology Types are the metrics used to estimate disease burden such as "incidence", "prevalence rate", or "occurrence"
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  - STAT: Epidemiology Rates describe how many people are afflicted by a disease.
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  - DATE: The dates when the epidemiologic studies were conducted
 
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  - SEX: The biological sexes mentioned in the abstract. Useful for diseases that disproportionately affect one sex over the other or may provide context to composition of the study population
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  - ETHN: Ethnicities, races, and nationalities of those represented in the epidemiologic study.
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  ''')
 
 
 
 
 
 
 
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  #st.dataframe(data=None, width=None, height=None)
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  fig = epi_sankey(sankey_data,disease_or_gard_id)
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+ st.plotly_chart(fig, use_container_width=True)