Commit
·
921ec68
1
Parent(s):
edd3b21
Update README.md
Browse files
README.md
CHANGED
@@ -12,6 +12,25 @@ dataset_info:
|
|
12 |
download_size: 1108991167
|
13 |
dataset_size: 1108945726.54
|
14 |
---
|
15 |
-
# Dataset Card
|
16 |
|
17 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
12 |
download_size: 1108991167
|
13 |
dataset_size: 1108945726.54
|
14 |
---
|
15 |
+
# Indiana University Chest Xray Dataset Card
|
16 |
|
17 |
+
## Data sources:
|
18 |
+
This is a converted and processed version of the open access pneumonia chest x-ray dataset provided by the indiana university
|
19 |
+
You can see its information page [here](https://openi.nlm.nih.gov/faq).
|
20 |
+
The compressed images in the png format were downloaded from [here](https://openi.nlm.nih.gov/imgs/collections/NLMCXR_png.tgz) and the corresponding reports from [here](https://openi.nlm.nih.gov/imgs/collections/NLMCXR_reports.tgz).
|
21 |
+
|
22 |
+
## Data fields:
|
23 |
+
There are two fields: image and text.
|
24 |
+
The images are the x-rays and the texts are their associated findings.
|
25 |
+
|
26 |
+
## Preprocessing done:
|
27 |
+
|
28 |
+
1. **Make all text lowercase**: Convert all text to lowercase to ensure consistent and case-insensitive processing.
|
29 |
+
|
30 |
+
2. **Remove all punctuation**: Eliminate any punctuation marks (e.g., periods, commas, exclamation marks) from the text to avoid interference in language analysis.
|
31 |
+
|
32 |
+
3. **Remove all numbers**: Eliminate all numeric characters from the text since they might not be relevant for certain natural language processing tasks.
|
33 |
+
|
34 |
+
4. **Remove all words with 2 or more Xs in a row**: Remove any words that contain two or more consecutive occurrences of the letter "X" as they may not contribute meaningful information.
|
35 |
+
|
36 |
+
5. **Remove the bottom and top 2% of text by length**: Discard the shortest and longest text samples, removing the bottom 2% and top 2% of the text's length, respectively. This step is aimed at reducing the impact of outliers and ensuring a more balanced dataset.
|