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mims-harvard · Jul 11, 2023 · 2644c1b · 2644c1b
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diff --git a/feed.xml b/feed.xml
@@ -1,2 +1,2 @@
-<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="3.8.6">Jekyll</generator><link href="http://localhost:4000/feed.xml" rel="self" type="application/atom+xml" /><link href="http://localhost:4000/" rel="alternate" type="text/html" /><updated>2023-07-09T16:35:07-07:00</updated><id>http://localhost:4000/feed.xml</id><title type="html">TDC</title><subtitle>Artificial intelligence foundation for therapeutic science
+<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="3.8.6">Jekyll</generator><link href="http://localhost:4000/feed.xml" rel="self" type="application/atom+xml" /><link href="http://localhost:4000/" rel="alternate" type="text/html" /><updated>2023-07-10T22:55:51-07:00</updated><id>http://localhost:4000/feed.xml</id><title type="html">TDC</title><subtitle>Artificial intelligence foundation for therapeutic science
 </subtitle></feed>
diff --git a/multi_pred_tasks/trialoutcome/index.html b/multi_pred_tasks/trialoutcome/index.html
@@ -287,7 +287,7 @@ <h3 id="trial-outcome-prediction-top">Trial Outcome Prediction (TOP)</h3>
 
 <p class="is-size-6">  <strong> Task Description: </strong> Binary Classification. Given clinical trial features including drug molecular structure, disease code, and eligibility criteria (inclusion and exclusion criteria), predict if it would be approved. </p>
 
-<p class="is-size-6">  <strong> Dataset Statistics: </strong> Phase I: 3373 trials / Phase II: 8225 trials / Phase III: 9433 trials. </p>
+<p class="is-size-6">  <strong> Dataset Statistics: </strong> Phase I: 2,402 trials / Phase II: 7,790 trials / Phase III: 5,741 trials. </p>
 
 <p class="is-size-6">  <strong> Dataset Split: </strong> <span class="tag is-info is-light">Temporal split</span> </p>
 

diff --git a/news/index.html b/news/index.html
@@ -151,6 +151,11 @@
 
 <div class="content">
     <h1 id="news">News</h1>
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+<hr />
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+<p class="is-size-5"><strong>2023.07.10</strong> TDC <code>0.4.1</code> is released! TDC has a new exciting task on clinical trial outcome prediction  (Thanks to Tianfan)! Checkout <a href="/multi_pred_tasks/trialoutcome/">here</a> for more information.</p>
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 <hr />
 
 <p class="is-size-5"><strong>2023.04. 17</strong> TDC <code>0.4.0</code> is released! We're excited to announce the release of a new interface <code>tdc_hf_interface</code> that allows users to easily access and leverage pre-trained models hosted at <a href="https://huggingface.co/tdc"> HuggingFace on TDC datasets and tasks</a>. In this first batch, we've released nine pre-trained models from <a href="https://github.com/kexinhuang12345/DeepPurpose">DeepPurpose</a> that cover three popular ADMET datasets in the Commons. To load our pre-trainend model, simply do the following: