Update app.py

app.py

@@ -6,11 +6,11 @@ import pandas as pd
 
 
 description = """
-# 🧠 NeuroSynth: MRI-Derived Neuroanatomical Generative Models and Associated Dataset of 18,000 Samples
+# 🧠 Generative models of MRI-derived neuroimaging features and associated dataset of 18000 samples
 
 <!-- Provide a quick summary of the dataset. -->
 
-NeuroSynth is a dataset which consists of 18,000 synthetic neuroimaging data samples covering worldwide healthy population across human lifespan.
+GenMIND is a dataset which consists of 18,000 synthetic neuroimaging data samples covering worldwide healthy population across human lifespan.
 
 ## Dataset Details
 
@@ -27,7 +27,7 @@ The dataset has the following characteristics:
 * Other browser users can directly click on the "Download" button to save the data
 * Download via command line:
 ```
-wget https://rongguangw-neuro-synth.hf.space/file=dataset/neurosynth_dataset.csv
+wget https://rongguangw-neuro-synth.hf.space/file=dataset/genmind_dataset.csv
 ```
 * You can also customize sex and race for the subjects and sample size by generating online in the below panels. The synthesized data will be showing in the lower right panel, and then, you can save the data by clicking on the "Download" button.
 """
@@ -36,7 +36,7 @@ citation = """
 ## Citation
 ```
 @article{chintapalli2024neurosynth,
-  title={NeuroSynth: MRI-Derived Neuroanatomical Generative Models and Associated Dataset of 18,000 Samples},
+  title={Generative models of MRI-derived neuroimaging features and associated dataset of 18000 samples},
   author={Chintapalli, Sai Spandana and Wang, Rongguang and Yang, Zhijian and Tassopoulou, Vasiliki and Yu, Fanyang and Bashyam, Vishnu and Erus, Guray and Chaudhari, Pratik and Shou, Haochang and Davatzikos, Christos},
   journal={arXiv preprint arXiv:2407.12897},
   year={2024}
@@ -44,8 +44,8 @@ citation = """
 ```
 """
 
-file_name = "dataset/neurosynth_dataset.csv"
-save_name = "dataset/customized_neurosynth.csv"
+file_name = "dataset/genmind_dataset.csv"
+save_name = "dataset/customized_genmind.csv"
 example_df = pd.read_csv(file_name)