Update README.md

README.md

@@ -17,10 +17,9 @@ size_categories:
 <!-- Provide a quick summary of the dataset. -->
 
 The "FracAtlas" dataset is a collection of musculoskeletal radiographs for fracture classification, localization, and segmentation. 
-It includes 4,083 X-Ray images with annotations in multiple formats.The annotations include labels, classes, and etc. 
+It includes 4,083 X-Ray images for bones with annotations in multiple formats.The annotations include labels, classes, and etc. 
 The dataset is intended for use in deep learning tasks in medical imaging, specifically targeting the understanding of bone fractures. 
 It is freely available under a CC-BY 4.0 license.
-## Dataset Details
 
 ### Dataset Description
 
@@ -29,32 +28,25 @@ It is freely available under a CC-BY 4.0 license.
 
 
 - **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
 - **License:** cc-by-2.5
 
-### Dataset Sources [optional]
+### Dataset Sources
 
 <!-- Provide the basic links for the dataset. -->
 
 - **Repository:** https://figshare.com/articles/dataset/The_dataset/22363012
-- **Paper [optional]:** https://www.nature.com/articles/s41597-023-02432-4
+- **Paper:** https://www.nature.com/articles/s41597-023-02432-4
 
 ## Uses
 
 <!-- Address questions around how the dataset is intended to be used. -->
+The  "FracAtlas" dataset can be used to develop multiple machine learning or deep learning algorithms. For example: 
+1. Developing a deep learning model to automatically detect fractures in radiographs.
+2. Classifying the type of fractures (e.g., hairline, compound, transverse) using machine learning models
+3. Implementing segmentation models to delineate bone structures from the surrounding tissues in the radiographs
+4. Forecasting patients’ outcomes based on the characteristics of the fracture and other patient data
+5. Developing models to identify anomalous patterns in the radiographs of bones
 
-### Direct Use
-
-<!-- This section describes suitable use cases for the dataset. -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-
-[More Information Needed]
 
 ## Dataset Structure
 
@@ -105,7 +97,7 @@ All personally identifiable information in the gathered data has been removed, a
 
 <!-- This section is meant to convey both technical and sociotechnical limitations. -->
 
-[More Information Needed]
+While the FracAtlas dataset is particularly valuable for the development of computer-aided diagnosis systems, its potential limitations should be carefully considered. Firstly, the manual annotation process, is susceptible to human error, which may result in mislabeling. Such inaccuracies can impact the performance of machine learning models trained on this data. 
 
 ### Recommendations
 
@@ -124,21 +116,3 @@ Users should be made aware of the risks, biases and limitations of the dataset.
 **APA:**
 
 [More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Dataset Card Authors [optional]
-
-[More Information Needed]
-
-## Dataset Card Contact
-
-[More Information Needed]