Add cross-ref to simulated data (#120)

* doc: Update simulated data paper

* chore

* chore

README.md

@@ -7,12 +7,11 @@
 ### News
 This repo contains the code for the paper `Accelerating Detection of Lung Pathologies with Explainable Ultrasound Image Analysis` which is now [available](https://www.mdpi.com/2076-3417/11/2/672). Please [cite](#Citation) that one instead of our preprint.
 
-### Goal
-This is an ongoing ultrasound data collection initiative for COVID-19. Please help growing the [database](data/README.md).
-
 ### Dataset
 Feel free to use (and cite) our dataset. We currently have >200 LUS videos labelled with a diagnostic outcome. Moreover, lung severity scores for 136 videos are made available in the [dataset_metadata.csv](./data/dataset_metadata.csv) under the column **"Lung Severity Score"** from [Gare et al., 2022](https://arxiv.org/abs/2201.07357). Further clinical information (symptoms, visible LUS patterns etc) are provided for some videos. For details see [data/README.md](data/README.md).
 
+If you are looking for more data, please consider using the 40,000 [carefully simulated LUS images](https://gitlab.com/pulselab/covid19) from the paper by [Zhao et al. (2024, *Communications Medicine*)](https://www.nature.com/articles/s43856-024-00463-5) that were partially derived from the data in this repo.
+
 **NOTE: Please make sure to create a meaningful train/test data split. Do not split the data on a frame-level, but on a video/patient-level. The task becomes trivial otherwise. See the instructions [here](pocovidnet/#cross-validation-splitting).**
 
 Please note: The founders/authors of the repository take no responsibility or liability for the data contributed to this archive. The contributing sites have to ensure that the collection and use of the data fulfills all applicable legal and ethical requirements.
@@ -75,7 +74,7 @@ An [abstract of our work was published](https://thorax.bmj.com/content/76/Suppl_
 The full paper is available via the COVID-19 special issue of [Applied Sciences](https://www.mdpi.com/2076-3417/11/2/672).
 Please cite these in favor of our deprecated [POCOVID-Net preprint](https://arxiv.org/abs/2004.12084).
 
-Please use the following bibtex entries:
+**Please use the following bibtex entry to cite this dataset:**
 ```bib
 @article{born2021accelerating,
   title={Accelerating Detection of Lung Pathologies with Explainable Ultrasound Image Analysis}, 
@@ -90,21 +89,6 @@ Please use the following bibtex entries:
   month={Jan}, 
   pages={672}
 }
-
-@article {born2021l2,
-  author = {Born, J and Wiedemann, N and Cossio, M and Buhre, C and Br{\"a}ndle, G and Leidermann, K and Aujayeb, A},
-  title = {L2 Accelerating COVID-19 differential diagnosis with explainable ultrasound image analysis: an AI tool},
-  volume = {76},
-  number = {Suppl 1},
-  pages = {A230--A231},
-  year = {2021},
-  doi = {10.1136/thorax-2020-BTSabstracts.404},
-  publisher = {BMJ Publishing Group Ltd},
-  issn = {0040-6376},
-  URL = {https://thorax.bmj.com/content/76/Suppl_1/A230.2},
-  eprint = {https://thorax.bmj.com/content/76/Suppl_1/A230.2.full.pdf},
-  journal = {Thorax}
-}
 ```
 
 If you use the severity scores, please cite the [Gare et al., 2022](https://arxiv.org/abs/2201.07357) paper using the following bibtex entry:
@@ -120,3 +104,17 @@ If you use the severity scores, please cite the [Gare et al., 2022](https://arxi
     arxivId = {2201.07357}
 }
 ```
+
+If you use the 40,000 synthetic images from [Zhao et al., 2024](https://www.nature.com/articles/s43856-024-00463-5), please cite their paper with the following bibtex entry:
+```bib
+@article{zhao2024detection,
+  title={Detection of COVID-19 features in lung ultrasound images using deep neural networks},
+  author={Zhao, Lingyi and Fong, Tiffany Clair and Bell, Muyinatu A Lediju},
+  journal={Communications Medicine},
+  volume={4},
+  number={1},
+  pages={41},
+  year={2024},
+  publisher={Nature Publishing Group UK London}
+}
+```