This project is a Java-based anonymization tool that reads medical notes from a text file, anonymizes personal information, and saves the anonymized data along with a log of original-to-anonymized mappings.
It replaces personal information such as names, dates of birth, addresses, phone numbers, and email addresses with unique identifiers to maintain privacy. The tool ensures that even repeated occurrences of the same names receive distinct IDs to avoid cross-referencing.
- Reads personal data from a text file named
PatientNotes.txt. - Anonymizes the following types of information:
- Full names (with titles like Dr., Mr., Ms., etc.)
- Dates of Birth (DoB)
- Addresses with or without postal codes
- Phone numbers
- Email addresses
- National Insurance Numbers (NINs)
- Outputs the results to two files:
AnonymizedData.txt: The anonymized text.MappedData.txt: A log of original data mapped to anonymized IDs.
- Generates unique IDs for each occurrence of personal data, even if the same name or info appears multiple times.
- Java StringBuilder is used for efficient logging and processing.
- Reading Input: The program reads the content from
PatientNotes.txt. - Anonymizing Data: It identifies personal data using regular expressions and replaces them with unique IDs.
- Names are anonymized line by line, ensuring each occurrence receives a unique ID.
- Writing Output: The anonymized text is saved in
AnonymizedData.txtand the mapping log inMappedData.txt.
- Java Development Kit (JDK) 8 or higher installed.
- Basic understanding of Java file I/O operations.
- Clone the repository:
git clone https://github.com/your-username/anonymization-tool.git
cd anonymization-tool- Compile the Java program:
javac AnonymizationTool.java-
Create a
PatientNotes.txtfile in the same directory with some sample medical notes. -
Run the program:
java AnonymizationTool- Check the output:
- Anonymized text:
AnonymizedData.txt - Mapped log:
MappedData.txt
Input (PatientNotes.txt):
Ms. Emily Johnson, 34-year-old, lives at 123 Elm Street, New York, NY.
Dr. Elon Musk, aged 45, can be contacted at 555-123-4567 or [email protected].
Mr. William Turner visited on 05/12/2023.
Ms. Emily Johnson visited again on 05/15/2023.Sample Output (AnonymizedData.txt):
1.1, 34-year-old, lives at 1.3.
2.1, aged 45, can be contacted at 1.6 or 1.7.
3.1 visited on 1.2.
4.1 visited again on 2.2.Sample Mapping (MappedData.txt):
1.1: Ms. Emily Johnson
2.1: Dr. Elon Musk
3.1: Mr. William Turner
4.1: Ms. Emily Johnson
1.3: 123 Elm Street, New York, NY
1.6: 555-123-4567
1.7: [email protected]
1.2: 05/12/2023
2.2: 05/15/2023- Sensitive information detection depends on the accuracy of regular expressions, so the tool may miss non-standard data formats.
- Anonymization is irreversible, meaning the original data cannot be restored from the anonymized output.
- Only supports English-language text; might not work well with other languages.
– Feel free to use and modify it.
If you encounter any issues or have suggestions for improvements, please open an issue on the GitHub repository.