better index

Author: lambda-science

app/index/templates/index.html

@@ -1,8 +1,7 @@
 {% extends "base.html" %} {% block content %}
 <div class="col-xl-6 offset-xl-3">
   <h1 align="center">
-    EHRoes 🦸: an all-in-one web application for patients’ data digitization
-    and exploration
+    EHRoes 🦸: an all-in-one web application for patients’ data digitization and exploration
   </h1>
   <p align="center">
     <img src="{{ url_for('static', filename='banner.png') }}" alt="EHRoes Banner" style="border-radius: 25px;" />
@@ -16,7 +15,7 @@ <h1 align="center">
   </p>
   <br />
   <h2>Demo Usage Instructions</h2>
-  <p>
+  <p align="justify">
     If you are on the demo instance (<a href="https://ehroes.lbgi.fr">https://ehroes.lbgi.fr</a>), you can login on top
     right with
     <strong>login: demo ; password: demo</strong><br /> The application is
@@ -39,46 +38,42 @@ <h2>Partners</h2>
       </a>
     </div>
     <div class="col-xl">
-      <p>EHRoes is developped and used in collaboration with the <a
+      <p align="justify">EHRoes is developped and used in collaboration with the <a
           href="https://www.institut-myologie.org/en/recherche-2/neuromuscular-exploration-and-evaluation-centre/laboratoire-dhistopathologie-dr-norma-b-romero/">
           Morphological Unit of the Institute of Myology of Paris</a>.
         A production instance is deployed to help discovering new relevant
         features for congenital myopathies classification and diagnosis.</p>
     </div>
   </div>
   <h2>EHRoes Abstract</h2>
-  <p>
-    <strong>Background</strong><br />With a growing amount of patient data such
-    as sequencing, imaging, and medical records, electronic health records (EHR)
-    became central to drive research and improve diagnosis of patients by using
-    multimodal data. But EHR usage is challenging as they require tools to
-    format, digitize and interpret data. Today’s EHR exploitation tools
-    ecosystem is heavily fragmented among tools to create EHR (format and
-    digitize) and tools to interpret the data (exploration and diagnosis).
-    Also most of the tools are specialized for one specific type of data,
-    multiplying the number of different software needed for multimodal
-    approaches. There is a strong need for a simple, all-rounder and flexible
-    platform.<br /><strong>Results</strong><br />In this paper we present
-    EHRoes, an all-in-one web application for patients’ data digitization and
-    exploration. With its module-based architecture, we developed four modules
-    to: (i) create a set of standard vocabulary for a domain, (ii) automatically
-    digitize free-text data to a set of standard terms, (iii) annotate images
-    with standard vocabulary using automatic segmentation and (iv) generate an
-    automatic visualization dashboard to provide insight on the data and perform
-    automatic diagnosis suggestions. Using this platform, we successfully
-    digitized 89 muscle histology reports from patients with congenital
-    myopathies and we obtained an accuracy of 0.75 for congenital myopathy
-    subtypes classification.<br /><strong>Conclusions</strong><br />With EHRoes
-    we created a platform for both patients data digitization and exploration
-    that can handle image data and free-text data. As it uses user designed
-    standard vocabulary, it is highly flexible to fit any domain of research. It
-    can be used both as a patient registry with automatic diagnosis or as a
-    research tool to explore a cohort of patients. A demo instance of the
-    application is available at
-    <a href="https://ehroes.lbgi.fr">https://ehroes.lbgi.fr</a>.
+  <p align="justify">
+    <strong>Background</strong><br />With a growing amount of patient data such as sequencing, imaging, and medical
+    records, electronic health records (EHR) are now central to drive research and improve diagnosis of patients by
+    using multimodal data. Exploiting patient data is a challenge as patient data exploitation tools ecosystem is often
+    fragmented into tools to digitize and format the data and those interpreting the data (exploration, diagnosis).
+    Furthermore, as most of the tools are specialized in one type of data, a multitude of software is needed for
+    multimodal approaches. There is a strong need for a simple, all-rounder and flexible platform.
+    <br />
+    <strong>Results</strong>
+    <br />
+    In this paper we present EHRoes, an all-in-one web application to digitize and explore patient data. EHRoes has a
+    module-based architecture, composed of four modules to: (i) create a standard vocabulary for a domain (ii)
+    automatically digitize free-text data to a set of standard terms (iii) annotate images with standard vocabulary
+    using automatic segmentation and (iv) generate an automatic visualization dashboard to provide insight on the data
+    and perform automatic diagnosis suggestions. We demonstrated the utility of EHRoes by digitizing 40 artificial
+    muscle histology reports of patients with congenital myopathies.
+    <br />
+    <strong>Conclusions</strong>
+    <br />
+    With EHRoes we created a platform for both digitization and exploration of patient data that can handle image data
+    and free-text data. As it uses user-designed standard vocabulary, it is highly flexible to fit any domain of
+    research. It can be used both as a patient registry with automatic diagnosis or as a research tool to explore a
+    cohort of patients. A demo instance of the application is available at <a
+      href="https://ehroes.lbgi.fr">https://ehroes.lbgi.fr</a>.
+
   </p>
   <h2>MYO-xIA Project</h2>
-  <p>
+  <p align="justify">
     The MYO-xIA project aims to collect data from patients with
     <strong>congenital myopathies</strong> in order to analyse them using
     <strong>explainable AI approaches</strong>. In the field of congenital
@@ -87,7 +82,7 @@ <h2>MYO-xIA Project</h2>
     to use modern data analysis methods.<br />This project has tree mains
     objectives:
   </p>
-  <ul>
+  <ul align="justify">
     <li>
       <strong>Gather and format patient data</strong> to be ready for automatic
       exploitation (patient histology-report form, image annotation, OCR/NLP)

app/index/templates/index.md

@@ -14,12 +14,11 @@ EHRoes is developped and used in collaboration with the [Morphological Unit of t
 ## EHRoes Abstract
 
 **Background**
-With a growing amount of patient data such as sequencing, imaging, and medical records, electronic health records (EHR) became central to drive research and improve diagnosis of patients by using multimodal data. But EHR usage is challenging as they require tools to format, digitize and interpret data. Today’s EHR exploitation tools ecosystem is heavily fragmented among tools to create EHR (format and digitize) and tools to interpret the data (exploration and diagnosis). Also most of the tools are specialized for one specific type of data, multiplying the number of different software needed for multimodal approaches. There is a strong need for a simple, all-rounder and flexible platform.
+With a growing amount of patient data such as sequencing, imaging, and medical records, electronic health records (EHR) are now central to drive research and improve diagnosis of patients by using multimodal data. Exploiting patient data is a challenge as patient data exploitation tools ecosystem is often fragmented into tools to digitize and format the data and those interpreting the data (exploration, diagnosis). Furthermore, as most of the tools are specialized in one type of data, a multitude of software is needed for multimodal approaches. There is a strong need for a simple, all-rounder and flexible platform.
 **Results**
-In this paper we present EHRoes, an all-in-one web application for patients’ data digitization and exploration. With its module-based architecture, we developed four modules to: (i) create a set of standard vocabulary for a domain, (ii) automatically digitize free-text data to a set of standard terms, (iii) annotate images with standard vocabulary using automatic segmentation and (iv) generate an automatic visualization dashboard to provide insight on the data and perform automatic diagnosis suggestions. Using this platform, we successfully digitized 89 muscle histology reports from patients with congenital myopathies and we obtained an accuracy of 0.75 for congenital myopathy subtypes classification.
+In this paper we present EHRoes, an all-in-one web application to digitize and explore patient data. EHRoes has a module-based architecture, composed of four modules to: (i) create a standard vocabulary for a domain (ii) automatically digitize free-text data to a set of standard terms (iii) annotate images with standard vocabulary using automatic segmentation and (iv) generate an automatic visualization dashboard to provide insight on the data and perform automatic diagnosis suggestions. We demonstrated the utility of EHRoes by digitizing 40 artificial muscle histology reports of patients with congenital myopathies.
 **Conclusions**
-With EHRoes we created a platform for both patients data digitization and exploration that can handle image data and free-text data. As it uses user designed standard vocabulary, it is highly flexible to fit any domain of research. It can be used both as a patient registry with automatic diagnosis or as a research tool to explore a cohort of patients.
-A demo instance of the application is available at https://ehroes.lbgi.fr.
+With EHRoes we created a platform for both digitization and exploration of patient data that can handle image data and free-text data. As it uses user-designed standard vocabulary, it is highly flexible to fit any domain of research. It can be used both as a patient registry with automatic diagnosis or as a research tool to explore a cohort of patients. A demo instance of the application is available at https://ehroes.lbgi.fr.
 
 ## MYO-xIA Project