Update app.py

app.py

@@ -503,9 +503,10 @@ title = "Physics-informed self-supervised learning for predicting cardiac digita
 
 description = """
 <p style='text-align: center'> Keying Kuang, Frances Dean, Jack B. Jedlicki, David Ouyang, Anthony Philippakis, David Sontag, Ahmed Alaa  <br>
- <a href='https://github.com/AlaaLab/CardioPINN' target='_blank'>Code</a></p>
-We develop methodology for predicting digital twins from non-invasive cardiac ultrasound images in <a href='https://arxiv.org/abs/2403.00177'>Non-Invasive Medical Digital Twins using Physics-Informed Self-Supervised Learning</a>. \n\n 
-We demonstrate the ability of our model to predict left ventricular pressure-volume loops using image data here.
+ Check out our <a href='https://github.com/AlaaLab/CardioPINN' target='_blank'>code.</a></p>
+<p> We develop methodology for predicting digital twins from non-invasive cardiac ultrasound images in <a href='https://arxiv.org/abs/2403.00177'>Non-Invasive Medical Digital Twins using Physics-Informed Self-Supervised Learning</a>. \n \n 
+We demonstrate the ability of our model to predict left ventricular pressure-volume loops using image data here. To run example predictions on samples from the <a href='https://echonet.github.io/dynamic/'>EchoNet</a> dataset, click the first button. \n \n 
+Below you can input values of predicted parameters and output a simulated pressure-volume loop predicted by the <a href='https://ieeexplore.ieee.org/document/4729737/keywords#keywords'>Simaan et al 2008</a> hydraulic analogy model by pressuing 'Run simulation.'</p>
 """
 
 gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>" + title + "</h1>")