Update README.md

README.md

@@ -1,26 +1,26 @@
----
-language:
-- en
-license: apache-2.0
-library_name: transformers
-tags:
-- chest X-ray report generation
-- radiology report generation
-- image captioning
-- chest X-ray
-- X-ray
-- radiology
-- cxrmate
-- cxrmate-ed
-- report
-- radiology report
-- multimodal
-- patient data
-- patient records
-- mimic-cxr
-- mimic-iv-ed
-pipeline_tag: image-text-to-text
----
+---
+language:
+- en
+license: apache-2.0
+library_name: transformers
+tags:
+- chest X-ray report generation
+- radiology report generation
+- image captioning
+- chest X-ray
+- X-ray
+- radiology
+- cxrmate
+- cxrmate-ed
+- report
+- radiology report
+- multimodal
+- patient data
+- patient records
+- mimic-cxr
+- mimic-iv-ed
+pipeline_tag: image-text-to-text
+---
 
 # **CXRMate-ED**: The Impact of Auxiliary Patient Data on Automated Chest X-Ray Report Generation and How to Incorporate It
 
@@ -30,39 +30,6 @@ The abstract from the paper:
 
 "This study investigates the integration of diverse patient data sources into multimodal language models for automated chest X-ray (CXR) report generation. Traditionally, CXR report generation relies solely on CXR images and limited radiology data, overlooking valuable information from patient health records, particularly from emergency departments. Utilising the MIMIC-CXR and MIMIC-IV-ED datasets, we incorporate detailed patient information such as vital signs, medicines, and clinical history to enhance diagnostic accuracy. We introduce a novel approach to transform these heterogeneous data sources into embeddings that prompt a multimodal language model; this significantly enhances the diagnostic accuracy of generated radiology reports. Our comprehensive evaluation demonstrates the benefits of using a broader set of patient data, underscoring the potential for enhanced diagnostic capabilities and better patient outcomes through the integration of multimodal data in CXR report generation."
 
-## MIMIC-CXR & MIMIC-IV-ED Dataset:
-
-MIMIC-CXR, MIMIC-CXR-JPG, and MIMIC-IV-ED must be in the same Physio Net directory. E.g.:
-
-```shell
-user@cluster:~$ ls /home/user/physionet.org/files
-mimic-cxr  mimic-cxr-jpg  mimic-iv-ed
-```
-
-### Download MIMIC-CXR-JPG:
-
-Download the MIMIC-CXR-JPG dataset from https://physionet.org/content/mimic-cxr-jpg, e.g.,
-```shell
-wget -r -N -c -np --user <username> --ask-password https://physionet.org/files/mimic-cxr-jpg/2.1.0/
-```
-Note that you must be a credentialised user to access this dataset.
-
-### Download the reports from MIMIC-CXR:
-
-MIMIC-CXR-JPG does not include the radiology reports and are instead included with MIMIC-CXR (the DICOM version of the dataset). To download this dataset and avoid downloading the DICOM files (which are very large), use `--reject dcm` with the wget command from https://physionet.org/content/mimic-cxr, e.g, 
-```shell
-wget -r -N -c -np --reject dcm --user <username> --ask-password https://physionet.org/files/mimic-cxr/2.0.0/
-```
-Note that you must be a credentialised user to access this dataset.
-
-### Download MIMIC-IV-ED:
-
-Download the MIMIC-IV-ED dataset from https://physionet.org/content/mimic-iv-ed, e.g.,
-```shell
-wget -r -N -c -np --user <username> --ask-password https://physionet.org/files/mimic-iv-ed/2.2/
-```
-Note that you must be a credentialised user to access this dataset.
-
 ### Prepare the dataset:
 
 ```python
@@ -123,6 +90,39 @@ for i,j in zip(findings, impression):
     print(f'Findings:\t{i}\nImpression:\t{j}\n\n')
 ```
 
+## MIMIC-CXR & MIMIC-IV-ED Dataset:
+
+MIMIC-CXR, MIMIC-CXR-JPG, and MIMIC-IV-ED must be in the same Physio Net directory. E.g.:
+
+```shell
+user@cluster:~$ ls /home/user/physionet.org/files
+mimic-cxr  mimic-cxr-jpg  mimic-iv-ed
+```
+
+### Download MIMIC-CXR-JPG:
+
+Download the MIMIC-CXR-JPG dataset from https://physionet.org/content/mimic-cxr-jpg, e.g.,
+```shell
+wget -r -N -c -np --user <username> --ask-password https://physionet.org/files/mimic-cxr-jpg/2.1.0/
+```
+Note that you must be a credentialised user to access this dataset.
+
+### Download the reports from MIMIC-CXR:
+
+MIMIC-CXR-JPG does not include the radiology reports and are instead included with MIMIC-CXR (the DICOM version of the dataset). To download this dataset and avoid downloading the DICOM files (which are very large), use `--reject dcm` with the wget command from https://physionet.org/content/mimic-cxr, e.g, 
+```shell
+wget -r -N -c -np --reject dcm --user <username> --ask-password https://physionet.org/files/mimic-cxr/2.0.0/
+```
+Note that you must be a credentialised user to access this dataset.
+
+### Download MIMIC-IV-ED:
+
+Download the MIMIC-IV-ED dataset from https://physionet.org/content/mimic-iv-ed, e.g.,
+```shell
+wget -r -N -c -np --user <username> --ask-password https://physionet.org/files/mimic-iv-ed/2.2/
+```
+Note that you must be a credentialised user to access this dataset.
+
 # Environment requirements
 
 Environment requirements can be found here: https://github.com/aehrc/cxrmate-ed/blob/main/requirements.txt.