ando55 commited on
Commit
bee48d6
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1 Parent(s): 0abdfd0

Update app.py

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Files changed (1) hide show
  1. app.py +3 -3
app.py CHANGED
@@ -12,7 +12,7 @@ os.system('git clone --depth 1 https://github.com/neologd/mecab-unidic-neologd.g
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  st.set_page_config(
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- page_title="Clinical segment splitter",
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  page_icon="πŸš‘",
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  layout="wide"
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  )
@@ -38,7 +38,7 @@ def _max_width_():
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  #with c30:
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  # st.image("logo.png", width=400)
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- st.title("πŸš‘ Clinical segment splitter")
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  st.header("")
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@@ -47,7 +47,7 @@ with st.expander("ℹ️ - About this app", expanded=True):
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  st.write(
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  """
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- - The *Clinical segment splitter* app is an implementation of our paper.
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  >Kenichiro Ando, Takashi Okumura, Mamoru Komachi, Hiromasa Horiguchi, Yuji Matsumoto (2022) [Exploring optimal granularity for extractive summarization of unstructured health records: Analysis of the largest multi-institutional archive of health records in Japan.](https://doi.org/10.1371/journal.pdig.0000099) PLOS Digital Health 1(9): e000009.
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  - This app automatically splits Japanese sentences into smaller units representing medical meanings.
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  """
 
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  st.set_page_config(
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+ page_title="Clinical Segment Splitter",
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  page_icon="πŸš‘",
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  layout="wide"
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  )
 
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  #with c30:
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  # st.image("logo.png", width=400)
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+ st.title("πŸš‘ Clinical Segment Splitter")
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  st.header("")
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  st.write(
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  """
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+ - *Clinical segment splitter* app is an implementation of our paper.
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  >Kenichiro Ando, Takashi Okumura, Mamoru Komachi, Hiromasa Horiguchi, Yuji Matsumoto (2022) [Exploring optimal granularity for extractive summarization of unstructured health records: Analysis of the largest multi-institutional archive of health records in Japan.](https://doi.org/10.1371/journal.pdig.0000099) PLOS Digital Health 1(9): e000009.
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  - This app automatically splits Japanese sentences into smaller units representing medical meanings.
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  """