Update app.py

app.py

@@ -5,7 +5,7 @@
 """
 
 import streamlit as st
-
+import streamlit.components.v1 as components
 
 USER_GROUPS = ["Developer", "Manager", "Practitioner"]
 
@@ -30,39 +30,33 @@ st.session_state['user_group'] = backend
 st.sidebar.title("About")
 st.sidebar.info(
     """
-    Web App URL: <https://google.com>
-    GitHub repository: <https://github.com/kaplansinan/streamlit-airamework>
+    Web App URL: <http://testxaiprod-xaiframeworkdemo.rahtiapp.fi/Decision_Exploration_Panel>
+
+    GitHub repository: <https://github.com/>
     """
 )
 
 st.sidebar.title("Contact")
 st.sidebar.info(
     """
-    Sinan Kaplan: <https://www.linkedin.com/in/kaplansinan>
-    [GitHub](https://github.com/kaplansinan) | [LinkedIn](https://www.linkedin.com/in/kaplansinan)
+    John Doe and Jane Doe :[LinkedIn](https://www.linkedin.com/)
     """
 )
 
 # Customize page title
-st.title("XAI Framework Application-OCT Image Analysis by Deep Learning")
+st.title("Explainable Artificial Intelligence Framework Case Study - Optical Coherence Tomography Image Analysis by Deep Learning")
 
 
 markdown1 = """
-The framework is created to  briefly illustrate  how to use the poposed framework in our paper. Hence, we demonstrate a case study,which aims to detect certain anomalies from Retinal OCT images. 
+The proposed framework, as presented in our paper, aims to assist in the detection of selected anomalies from Retinal Optical Coherence Tomography (OCT) images. To illustrate the usage of the framework, we have developed a case study that focuses on identifying Choroidal Neovascularization (CNV), Diabetic Macular Edema (DME), Drusen, and normal/healthy retinal conditions.
 
-This system is developed to classifiy certain anamolies from OCT of retina images. Those anamolies are: 
+1. [Choroidal Neovascularization (CNV)](https://www.cell.com/cell/fulltext/S0092-8674(18)30154-5) is a type of retinal disease that involves the growth of abnormal blood vessels in the choroid layer of the eye. These new blood vessels can lead to fluid accumulation beneath and within the layers of tissue, causing vision loss.
 
-1. Choroidal Neovascularization (CNV): neovascular membrane and associated subretinal fluid (Choroidal Neovascularization (CNV) is a retinal disease,which is associated with the growth of 
-abnormal blood vessels in the choroid layer, which lies between two other layers of tissue that make up the wall of the eye. 
-These new blood vessels can cause fluid to accumulate beneath and within these layers, leading to vision loss.)
+2. [Diabetic Macular Edema (DME)](https://www.cell.com/cell/fulltext/S0092-8674(18)30154-5) is a common complication of diabetes that affects the retina responsible for central vision. This condition occurs when fluid accumulates in and around the macula, leading to retinal thickening and swelling, which can result in impaired vision or blindness if left untreated.
 
-2. Diabetic Macular Edema (DME) : A retinal disease that appears as a result of diabetes in the retina.   retinal-thickening-associated intraretinal fluid (arrows).Diabetic Macular Edema (DME) is a common complication of diabetes that affects the retina, 
-which is responsible for central vision. DME occurs when fluid accumulates in and around the macula, causing retinal thickening and swelling. 
-This can lead to impaired vision or even blindness if left untreated.)
-
-3. Drusen is a condition accosiated with early AMD Age-Related Macular Degeneration (AMD) in the retina.
-4. NORMAL(HEALTHY): A healthy retina,
+3. [Drusen](https://www.cell.com/cell/fulltext/S0092-8674(18)30154-5) is a condition associated with early Age-related Macular Degeneration (AMD) in the retina. It involves the accumulation of small deposits of liquid material in the retina, which can lead to vision problems.
 
+4. Finally, the framework includes a classification model for NORMAL or healthy retina, providing a baseline for comparison with the aforementioned anomalies.
 
 """
 st.markdown(markdown1)
@@ -75,13 +69,15 @@ st.markdown(markdown1)
 st.header("Framework Sections")
 
 markdown = """
-A different users can beenfit from this framework. The framework is divided into 4 different sections and each of them sheds a light at a different part of  this AI application.
+The framework consists of four distinct sections, each focusing on a different aspect of the Artificial Intelligence(AI) application.
+
+1. The Data Panel provides comprehensive information about the data used in the framework, including the sources, pre-processing techniques, and any relevant characteristics.
 
+2. The Model Panel offers insights into the AI model used in the framework, including its architecture, parameters, and training procedures.
 
-1. DATA PANEL:This section presents information regarding thedata in details. 
-2. MODEL PANEL: This section presents details regarding AI model. 
-3. PERFORMANCE EVALUATION PANEL: This panel hihglights the performance of the AI model over test set. 
-4. DECISION EXPLORATION: This section is decisgned to explore global and instance level explanations.
+3. The Performance Evaluation Panel can be used to analyze and report on the performance of the AI model over a test set, providing detailed metrics and visualization of results.
+
+4. Finally, the Decision Exploration section is designed to explore global and instance-level explanations of the AI model's decision-making process.
 """
 
 st.markdown(markdown)
@@ -91,10 +87,13 @@ st.markdown(markdown)
 st.header("How to Use the Framework")
 
 markdown = """
-To effectively use the framwork, please follow steps as instrcuted below:
+To utilize the framework efficiently, following the instructions below should be helpful:
+
+1. Navigate to the left sidebar and select a user group from the available options.
+
+2. Begin exploring the framework by clicking on the different panels, which are located in the upper left corner of the screen.
 
-1. On left sidebar under'USER GROUPS' choose user group
-2. Start exploring any panel by clicking on them on the upper left corner. We suggest to follow the order as data-> model-> performance-> decision exploration.
+It is recommend to follow the order of Data Panel, Model Panel, Performance Evaluation Panel, and Decision Exploration Panel to ensure a systematic understanding of the framework's functionality.
 """
 
 st.markdown(markdown)