Update descriptions

app.py

@@ -76,13 +76,14 @@ class main_window():
             gr.Markdown("""
                         # Introduction 
                         
-                        This is a demo for displaying the potential of language models fine tunned using the carefully curated dataset
-                        of structured MRI radiology reports for nasopharyngeal carcinoma (NPC) examination. Our team has an established
-                        track record for researching the role of AI in early detectio for NPC. We have already developed an AI system
-                        with high sensitivty and specificity > 90%. However. we explanability of the system is currently a major challenge
-                        for translation. In fact, this is a general problem for AI's developement in radiology. Therefore, in this pilot 
-                        study, we investigate language model in understanding the context of the disease to explore the possibility of incorporating
-                        language model in our existing system for explanability. 
+                        This demo aims to showcase the potential of language models fine-tuned using a meticulously curated dataset of 
+                        structured MRI radiology reports for the examination of nasopharyngeal carcinoma (NPC). Our team has a proven
+                        track record in researching the role of AI for the early detection of NPC, having developed an AI system that 
+                        achieves high sensitivity and specificity, both exceeding 90%. However, the explainability of the system remains 
+                        a significant hurdle for clinical application. This challenge is not unique to our system but is pervasive in the 
+                        development of AI for radiology. Therefore, in this pilot study, we investigate the capacity of language models 
+                        to comprehend the context of the disease. Our aim is to explore the integration of language models into our 
+                        existing system to enhance its explainability.
                         
                         # Affliations