readme updated

app.py

@@ -282,13 +282,15 @@ def redact_and_visualize(text: str, model_name: str):
 
 
 hint = """
-![SETT Logo](./assets/img/SETT_Logo.jpg)
+<p align="center">
+  <img src="https://github.com/MattStammers/Pteredactyl/blob/main/src/pteredactyl_webapp/assets/img/SETT_Logo.jpg" alt="SETT Logo" />
+</p>
 
 ## Pteredactyl Gradio Webapp and API
 
-Clinical patient identifiable information (cPII) presents a significant challenge in natural language processing (NLP) that has yet to be fully resolved but significant progress is being made [1,2]. 
+Clinical patient identifiable information (cPII) presents a significant challenge in natural language processing (NLP) that has yet to be fully resolved but significant progress is being made [1,2].
 
-This is why we created [Pteredactyl](https://pypi.org/project/pteredactyl/) - a python module to help with redaction of clinical free text. 
+This is why we created [Pteredactyl](https://pypi.org/project/pteredactyl/) - a python module to help with redaction of clinical free text.
 
 ## Tool Usage Instructions
 
@@ -305,10 +307,15 @@ docker build -t pteredactyl:latest .
 docker run -d -p 7860:7860 --name pteredactyl-app pteredactyl:latest
 ```
 
-## Information
+## Logo
 
-A lot of work and experimentation has gone into the development of this tool. Because we believe in being fully transparent further details are given below.
+<p align="center">
+  <img src="https://github.com/MattStammers/Pteredactyl/blob/main/src/pteredactyl_webapp/assets/img/Pteredactyl_Logo.jpg" alt="SETT Logo" />
+</p>
 
+## Background
+
+We introduce a concentrated validation battery to the open-source OHDSI community, a Python module for cPII redaction on free text, and a web application that compares various models against the battery. This setup, which allows simultaneous production API deployment using  Gradio, is remarkably efficient and can operate on a single CPU core.
 
 ### Methods:
 
@@ -347,8 +354,8 @@ The validation cohort introduced in this study proves to be a highly effective t
 We invite the open-source community to collaborate to improve the present results and enhance the robustness of cPII redaction methods by building on the work we have begun [here](https://github.com/SETT-Centre-Data-and-AI/PteRedactyl).
 
 ### References:
-1. Chambon PJ, Wu C, Steinkamp JM, Adleberg J, Cook TS, Langlotz CP. Automated deidentification of radiology reports combining transformer and “hide in plain sight” rule-based methods. J Am Med Inform Assoc. 2023 Feb 1;30(2):318–28. 
-2. Kotevski DP, Smee RI, Field M, Nemes YN, Broadley K, Vajdic CM. Evaluation of an automated Presidio anonymisation model for unstructured radiation oncology electronic medical records in an Australian setting. Int J Med Inf. 2022 Dec 1;168:104880. 
+1. Chambon PJ, Wu C, Steinkamp JM, Adleberg J, Cook TS, Langlotz CP. Automated deidentification of radiology reports combining transformer and “hide in plain sight” rule-based methods. J Am Med Inform Assoc. 2023 Feb 1;30(2):318–28.
+2. Kotevski DP, Smee RI, Field M, Nemes YN, Broadley K, Vajdic CM. Evaluation of an automated Presidio anonymisation model for unstructured radiation oncology electronic medical records in an Australian setting. Int J Med Inf. 2022 Dec 1;168:104880.
 """
 
 description = """