Clinical De-identification (Mask)
收藏Databricks2024-05-09 收录
下载链接:
https://marketplace.databricks.com/details/40f9b4db-ba84-4af1-aba6-57abfba24676/John-Snow-Labs_Clinical-De-identification-(Mask)
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资源简介:
**Clinical De-identification (Mask):**
The Clinical De-Identification model is designed to recognize and anonymize PHI in English-language clinical notes. It employs state-of-the-art natural language processing techniques to detect sensitive information such as patient names, addresses, medical record numbers, and other identifiers. Once identified, the PHI is effectively masked, rendering the text safe for broader use while maintaining its informational integrity.
**Key Features:**
- The model is finely tuned to identify a wide range of PHI elements in medical texts, ensuring comprehensive de-identification.
- The de-identification process aligns with HIPAA and other healthcare privacy regulations, aiding in legal compliance and data protection.
- Ideal for research, analytics, and training purposes, this model enables the safe utilization of medical texts without compromising patient privacy.
This model is a useful asset in the healthcare and research sectors, where the protection of patient privacy is paramount. It allows for the ethical and legal use of valuable medical data, promoting research and analysis while upholding the highest standards of data privacy and security.
**Additional Model Information**
- [Industry Use-Case Demo](https://demo.johnsnowlabs.com/healthcare/DEID_PHI_TEXT_MULTI/)
- [Full model info on John Snow Labs Models Hub](https://nlp.johnsnowlabs.com/2023/07/11/clinical_deidentification_en.html)
- **Domain:** Clinical Data Privacy
- **Subdomain:** PHI Masking and De-identification
- **Predictable entities:** AGE, CONTACT, DATE, ID, LOCATION, NAME, PROFESSION, CITY, COUNTRY, DOCTOR, HOSPITAL, IDNUM, MEDICALRECORD, ORGANIZATION, PATIENT, PHONE, PROFESSION, STREET, USERNAME, ZIP, ACCOUNT, LICENSE, VIN, SSN, DLN, PLATE, IPADDR
- **Deployment Identifier:** 1. Clinical De-identification (Mask)
**How to run this model:**
1. Acquire a John Snow Labs Pay As You Go (PAYG) license from [John Snow Labs](https://my.johnsnowlabs.com/).
2. Import this listing
3. Use the attached notebook to deploy the model with **1. Clinical De-identification (Mask)** as the model parameter. **Do not use the Open button on this page which appears after importing this listing. It will fail to deploy a model and does not work yet, you must use the attached notebook.**
This model comes with optimized CPU and GPU builds. You can select which one to deploy via the notebook.
**How to obtain a PAYG license for John Snow Labs models:**
1. Access [my.JohnSnowLabs.com](https://my.johnsnowlabs.com/) and log in to your account. If you don't have an account, create one.
2. Go to the Get License page.
3. Switch to the PAYG Subscription tab and provide your credit card details.
4. Carefully review the End User License Agreement and the Terms and Conditions documents. If you agree, click on the Create Subscription button.
5. Once the process is complete, you will find your PAY-As-You-Go license listed on the My Subscriptions page.
6. Visit the My Subscriptions page and copy the PAYG license key by clicking on the copy icon in the License Key column.
7. Go to your Databricks notebook and paste your JSL-license into the JSL-License field in the top of the notebook. You are now ready to go!
提供机构:
John Snow Labs



