Abstract update

Author: lambda-science

app/index/templates/index.html

@@ -31,7 +31,7 @@ <h3>Demo Usage Instructions</h3>
     annotation can be found
     <a href="https://www.lbgi.fr/~meyer/IMPatienT/sample_image_histo.jpg">HERE</a>.
   </p>
-
+  <br />
   <h3>Partners</h3>
   <div class="row align-items-center">
     <div class="col-xl-4">
@@ -49,36 +49,38 @@ <h3>Partners</h3>
         features for congenital myopathies classification and diagnosis.</p>
     </div>
   </div>
+  <br />
   <h3>IMPatienT🗂️️ Abstract</h3>
   <p align="justify">
     <strong>Background</strong>
     <br />
-    Medical acts such as imaging leads most of the time to the production of several medical text reports to describe
-    relevant findings. Such process induce multimodality in patient data by linking image data to free-text data.
-    Multimodal data have become central to drive research and improve diagnosis of patients. Exploiting patients’ data
-    is challenging as the ecosystem of tools is fragmented depending on the type of data to exploit (image, text,
-    genetic), the task to perform (digitization, processing, exploration) and the domain of interest (clinical
-    phenotype, histology…). There is a strong need for a simple, comprehensive, and flexible platform.
+    Medical acts, such as imaging, generally lead to the production of several medical text reports that describe the
+    relevant findings. Such processes induce multimodality in patient data by linking image data to free-text data and
+    consequently, multimodal data have become central to drive research and improve diagnosis of patients. However, the
+    exploitation of patient data is challenging as the ecosystem of available analysis tools is fragmented depending on
+    the type of data (images, text, genetic sequences), the task to be performed (digitization, processing, exploration)
+    and the domain of interest (clinical phenotype, histology…). To address the challenges, the analysis tools need to
+    be integrated in a simple, comprehensive, and flexible platform.
     <br />
     <strong>Results</strong>
     <br />
-    In this paper, we present IMPatienT (d<strong>I</strong>gitize <strong>M</strong>ultimodal <strong>PATIEN</strong>t
-    da<strong>T</strong>a), a free and open-source web application to
-    digitize, process and explore multimodal patient data. IMPatienT has a modular architecture, composed of four
-    components to: (i) create a standard vocabulary for a domain (ii) digitize and process free-text data by mapping it
-    to a set of standard terms, (iii) annotate images and perform image segmentation and (iv) generate an automatic
-    visualization dashboard to provide insight on the data and perform automatic diagnosis suggestions. Finally, we
-    showcased IMPatienT on a corpus of 40 simulated muscle biopsy reports of congenital myopathy patients.
+    Here, we present IMPatienT (d<strong>I</strong>gitize <strong>M</strong>ultimodal <strong>PATIEN</strong>t
+    da<strong>T</strong>a), a free and open-source web application to digitize, process and explore multimodal patient
+    data. IMPatienT has a modular architecture, including four components to: (i) create a standard vocabulary for a
+    domain, (ii) digitize and process free-text data by mapping it to a set of standard terms, (iii) annotate images and
+    perform image segmentation, and (iv) generate an automatic visualization dashboard to provide insight on the data
+    and perform automatic diagnosis suggestions. Finally, we demonstrate the usefulness of IMPatienT on a corpus of 40
+    simulated muscle biopsy reports of congenital myopathy patients.
     <br />
     <strong>Conclusions</strong>
     <br />
     IMPatienT is a platform to digitize, process and explore patient data that can handle image and free-text data. As
-    it relies on user-designed standard vocabulary, it is highly flexible to fit any domain of research and can be used
-    as a patient registry for exploratory data analysis (EDA). A demo instance of the application is available at <a
+    it relies on a user-designed vocabulary, it can be adapted to fit any domain of research and can be used as a
+    patient registry for exploratory data analysis (EDA). A demo instance of the application is available at <a
       href="https://impatient.lbgi.fr">https://impatient.lbgi.fr</a>.
 
-
   </p>
+  <br />
   <h3>MYO-xIA Project</h3>
   <p align="justify">
     The MYO-xIA project aims to collect data from patients with
@@ -89,6 +91,7 @@ <h3>MYO-xIA Project</h3>
     to use modern data analysis methods.<br />This project has tree mains
     objectives:
   </p>
+  <br />
   <ul align="justify">
     <li>
       <strong>Gather and format patient data</strong> to be ready for automatic
@@ -106,11 +109,13 @@ <h3>MYO-xIA Project</h3>
       reports, images, genetic data and phenotype)
     </li>
   </ul>
+  <br />
   <h3>Contact</h3>
   <p>
     The main maintainer is:<br /><strong>Corentin Meyer</strong> - PhD Student @
     CSTB Team - iCube - University Of Strasbourg <a href="mailto:[email protected]">[email protected]</a>
   </p>
+  <br />
   <h3>Citing IMPatienT🗂️</h3>
   <p>[placeholder]</p>
 </div>

app/index/templates/index.md

@@ -14,11 +14,11 @@ IMPatienT is developped and used in collaboration with the [Morphological Unit o
 ## IMPatienT🗂️ Abstract
 
 **Background**
-Medical acts such as imaging leads most of the time to the production of several medical text reports to describe relevant findings. Such process induce multimodality in patient data by linking image data to free-text data. Multimodal data have become central to drive research and improve diagnosis of patients. Exploiting patients’ data is challenging as the ecosystem of tools is fragmented depending on the type of data to exploit (image, text, genetic), the task to perform (digitization, processing, exploration) and the domain of interest (clinical phenotype, histology…). There is a strong need for a simple, comprehensive, and flexible platform.
+Medical acts, such as imaging, generally lead to the production of several medical text reports that describe the relevant findings. Such processes induce multimodality in patient data by linking image data to free-text data and consequently, multimodal data have become central to drive research and improve diagnosis of patients. However, the exploitation of patient data is challenging as the ecosystem of available analysis tools is fragmented depending on the type of data (images, text, genetic sequences), the task to be performed (digitization, processing, exploration) and the domain of interest (clinical phenotype, histology…). To address the challenges, the analysis tools need to be integrated in a simple, comprehensive, and flexible platform.
 **Results**
-In this paper, we present IMPatienT (dIgitize Multimodal PATIENt daTa), a free and open-source web application to digitize, process and explore multimodal patient data. IMPatienT has a modular architecture, composed of four components to: (i) create a standard vocabulary for a domain (ii) digitize and process free-text data by mapping it to a set of standard terms, (iii) annotate images and perform image segmentation and (iv) generate an automatic visualization dashboard to provide insight on the data and perform automatic diagnosis suggestions. Finally, we showcased IMPatienT on a corpus of 40 simulated muscle biopsy reports of congenital myopathy patients.
+Here, we present IMPatienT (d**I**gitize **M**ultimodal **PATIEN**t da**T**a), a free and open-source web application to digitize, process and explore multimodal patient data. IMPatienT has a modular architecture, including four components to: (i) create a standard vocabulary for a domain, (ii) digitize and process free-text data by mapping it to a set of standard terms, (iii) annotate images and perform image segmentation, and (iv) generate an automatic visualization dashboard to provide insight on the data and perform automatic diagnosis suggestions. Finally, we demonstrate the usefulness of IMPatienT on a corpus of 40 simulated muscle biopsy reports of congenital myopathy patients.
 **Conclusions**
-IMPatienT is a platform to digitize, process and explore patient data that can handle image and free-text data. As it relies on user-designed standard vocabulary, it is highly flexible to fit any domain of research and can be used as a patient registry for exploratory data analysis (EDA). A demo instance of the application is available at https://impatient.lbgi.fr.
+IMPatienT is a platform to digitize, process and explore patient data that can handle image and free-text data. As it relies on a user-designed vocabulary, it can be adapted to fit any domain of research and can be used as a patient registry for exploratory data analysis (EDA). A demo instance of the application is available at https://impatient.lbgi.fr.
 
 ## MYO-xIA Project
 

app/ontocreate/templates/ontocreate.html

@@ -60,7 +60,7 @@ <h5 class="modal-title" id="LangInvertPopupLabel">
     </div>
   </div>
   <div class="col-xl">
-    <h1>Vocubulary Properties</h1>
+    <h1>Vocabulary Properties</h1>
     <form method="post">
       {% for error in form.errors %}
       <span style="color: red">{{ error }}: {{form.errors[error]}}</span>