wzkariampuzha commited on
Commit
fb5e624
1 Parent(s): f8ef3fe

Update app.py

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Files changed (1) hide show
  1. app.py +6 -3
app.py CHANGED
@@ -12,7 +12,7 @@ import pickle
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  import plotly.graph_objects as go
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  ########## Title for the Web App ##########
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- st.markdown('''<img src="https://huggingface.co/spaces/ncats/EpiPipeline4GARD/resolve/main/NCATS_logo.png" alt="National Center for Advancing Translational Sciences Logo" width=550>''',unsafe_allow_html=True)
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  #st.markdown("![National Center for Advancing Translational Sciences (NCATS) Logo](https://huggingface.co/spaces/ncats/EpiPipeline4GARD/resolve/main/NCATS_logo.png")
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  #st.markdown('''<img src="https://huggingface.co/spaces/ncats/EpiPipeline4GARD/raw/main/NCATS_logo.svg" alt="National Center for Advancing Translational Sciences Logo" width="800" height="300">''',unsafe_allow_html=True)
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  st.title("Epidemiology Extraction Pipeline for Rare Diseases")
@@ -34,6 +34,8 @@ st.markdown(
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  unsafe_allow_html=True,
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  )
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  #max_results is Maximum number of PubMed ID's to retrieve BEFORE filtering
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  max_results = st.sidebar.number_input("Maximum number of articles to find in PubMed", min_value=1, max_value=None, value=50)
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@@ -103,10 +105,11 @@ with st.spinner('Loading Epidemiology Models and Dependencies...'):
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  #nlpSci2 = spacy.load('en_ner_bionlp13cg_md')
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  #classify_model_vars = (nlp, nlpSci, nlpSci2, classify_model, classify_tokenizer)
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  loaded = st.success('All Models and Dependencies Loaded!')
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- disease_or_gard_id = st.text_input("Input a rare disease term or GARD ID.")
 
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  loaded.empty()
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- st.markdown("Examples of rare diseases include [**Fellman syndrome**](https://rarediseases.info.nih.gov/diseases/1/gracile-syndrome), [**Classic Homocystinuria**](https://rarediseases.info.nih.gov/diseases/6667/classic-homocystinuria) and [**Phenylketonuria**](https://rarediseases.info.nih.gov/diseases/7383/phenylketonuria).")
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  st.markdown("A full list of rare diseases tracked by GARD can be found [here](https://rarediseases.info.nih.gov/diseases/browse-by-first-letter).")
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  import plotly.graph_objects as go
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  ########## Title for the Web App ##########
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+ st.markdown('''<img src="https://huggingface.co/spaces/ncats/EpiPipeline4GARD/resolve/main/Logo_GARD_fullres.png" alt="NIH Genetic and Rare Diseases Information Center Logo" width=550>''',unsafe_allow_html=True)
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  #st.markdown("![National Center for Advancing Translational Sciences (NCATS) Logo](https://huggingface.co/spaces/ncats/EpiPipeline4GARD/resolve/main/NCATS_logo.png")
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  #st.markdown('''<img src="https://huggingface.co/spaces/ncats/EpiPipeline4GARD/raw/main/NCATS_logo.svg" alt="National Center for Advancing Translational Sciences Logo" width="800" height="300">''',unsafe_allow_html=True)
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  st.title("Epidemiology Extraction Pipeline for Rare Diseases")
 
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  unsafe_allow_html=True,
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  )
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+ st.markdown("This application was built by the [National Center for Advancing Translational Sciences (NCATS)](https://ncats.nih.gov/) for the [National Institutes of Health (NIH)](https://www.nih.gov/) [Genetic and Rare Diseases Information Center](https://rarediseases.info.nih.gov/) to automatically search PubMed abstracts for rare disease epidemiology statistics.")
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+
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  #max_results is Maximum number of PubMed ID's to retrieve BEFORE filtering
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  max_results = st.sidebar.number_input("Maximum number of articles to find in PubMed", min_value=1, max_value=None, value=50)
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  #nlpSci2 = spacy.load('en_ner_bionlp13cg_md')
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  #classify_model_vars = (nlp, nlpSci, nlpSci2, classify_model, classify_tokenizer)
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  loaded = st.success('All Models and Dependencies Loaded!')
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+ st.markdown("Input a rare disease term or GARD ID.")
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+ disease_or_gard_id = st.text_input()
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  loaded.empty()
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+ st.markdown("Examples of rare diseases include [**Fellman syndrome**](https://rarediseases.info.nih.gov/diseases/1/gracile-syndrome), [**Classic Homocystinuria**](https://rarediseases.info.nih.gov/diseases/6667/classic-homocystinuria), [**7383**](https://rarediseases.info.nih.gov/diseases/7383/phenylketonuria), and [**GARD:0009941**](https://rarediseases.info.nih.gov/diseases/9941/fshmd1a).")
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  st.markdown("A full list of rare diseases tracked by GARD can be found [here](https://rarediseases.info.nih.gov/diseases/browse-by-first-letter).")
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