diff --git a/README.md b/README.md
index 572cd25..5ef93fd 100644
--- a/README.md
+++ b/README.md
@@ -1,4 +1,4 @@
-# Clinical Text Summarization by Adapting LLMs
+# Clinical Text Summarization by Adapting LLMs | Nature Medicine
 
 Official implementation from Stanford University<br>
 - <b> Title: </b>[Adapted Large Language Models Can Outperform Medical Experts in Clinical Text Summarization](https://arxiv.org/pdf/2309.07430.pdf)<br>
@@ -56,12 +56,13 @@ Below is a description of relevant scripts:
 ## Citation
 
 ```
-@misc{vanveen2023clinical,
-      title={Clinical Text Summarization: Adapting Large Language Models Can Outperform Human Experts},
-      author={Dave Van Veen and Cara Van Uden and Louis Blankemeier and Jean-Benoit Delbrouck and Asad Aali and Christian Bluethgen and Anuj Pareek and Malgorzata Polacin and William Collins and Neera Ahuja and Curtis P. Langlotz and Jason Hom and Sergios Gatidis and John Pauly and Akshay S. Chaudhari},
-      year={2023},
-      eprint={2309.07430},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL}
+@article{vanveen2024linical,
+  title={Adapted large language models can outperform medical experts in clinical text summarization},
+  author={Van Veen, Dave and Van Uden, Cara and Blankemeier, Louis and Delbrouck, Jean-Benoit and Aali, Asad and Bluethgen, Christian and Pareek, Anuj and Polacin, Malgorzata and Collins, William and Ahuja, Neera and Langlotz, Curtis P. and Hom, Jason and Gatidis, Sergios and Pauly, John and Chaudhari, Akshay S.},
+  journal={Nature Medicine},
+  year={2024},
+  doi={10.1038/s41591-024-02855-5},
+  url={https://doi.org/10.1038/s41591-024-02855-5},
+  published={27 February 2024}
 }
 ```
diff --git a/index.html b/index.html
index 150d0d4..20a0038 100644
--- a/index.html
+++ b/index.html
@@ -291,7 +291,12 @@
 				<tr>
 					<td align=center width=120px>
 						<center>
-							<span style="font-size:24px"><a href='https://arxiv.org/abs/2309.07430'>[Paper]</a></span>
+							<span style="font-size:24px"><a href='https://www.nature.com/articles/s41591-024-02855-5'>[Nature Medicine]</a></span>
+						</center>
+					</td>
+					<td align=center width=120px>
+						<center>
+							<span style="font-size:24px"><a href='https://arxiv.org/abs/2309.07430'>[arXiv]</a></span>
 						</center>
 					</td>
 					<td align=center width=120px>
@@ -301,7 +306,7 @@
 					</td>
 					<td align=center width=120px>
 						<center>
-							<span style="font-size:24px"><a href='https://github.com/StanfordMIMI/clin-summ'>[Code]</a></span><br>
+							<span style="font-size:24px"><a href='https://github.com/StanfordMIMI/clin-summ'>[GitHub]</a></span><br>
 						</center>
 					</td>
 				</tr>
diff --git a/resources/bibtex.txt b/resources/bibtex.txt
index 37bbbab..f09f1c8 100644
--- a/resources/bibtex.txt
+++ b/resources/bibtex.txt
@@ -1,8 +1,9 @@
-@misc{vanveen2023clinical,
-      title={Clinical Text Summarization: Adapting Large Language Models Can Outperform Human Experts}, 
-      author={Dave Van Veen and Cara Van Uden and Louis Blankemeier and Jean-Benoit Delbrouck and Asad Aali and Christian Bluethgen and Anuj Pareek and Malgorzata Polacin and William Collins and Neera Ahuja and Curtis P. Langlotz and Jason Hom and Sergios Gatidis and John Pauly and Akshay S. Chaudhari},
-      year={2023},
-      eprint={2309.07430},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL}
+@article{vanveen2024linical,
+  title={Adapted large language models can outperform medical experts in clinical text summarization},
+  author={Van Veen, Dave and Van Uden, Cara and Blankemeier, Louis and Delbrouck, Jean-Benoit and Aali, Asad and Bluethgen, Christian and Pareek, Anuj and Polacin, Malgorzata and Collins, William and Ahuja, Neera and Langlotz, Curtis P. and Hom, Jason and Gatidis, Sergios and Pauly, John and Chaudhari, Akshay S.},
+  journal={Nature Medicine},
+  year={2024},
+  doi={10.1038/s41591-024-02855-5},
+  url={https://doi.org/10.1038/s41591-024-02855-5},
+  published={27 February 2024}
 }