MITRE Identification Scrubber Toolkit

Status: Beta

Brought to you by: aberdeen, sambayer, slbayer

Add a Review

Downloads: 3 This Week

Last Update: 2022-11-16

Download

Get an email when there's a new version of MITRE Identification Scrubber Toolkit

The MITRE Identification Scrubber Toolkit (MIST) is a suite of tools for identifying and redacting personally identifiable information (PII) in free-text medical records.

Project Activity

See All Activity >

License

BSD License

Follow MITRE Identification Scrubber Toolkit

MITRE Identification Scrubber Toolkit Web Site

Other Useful Business Software

Earn up to 16% annual interest with Nexo.

Let your crypto work for you

Put idle assets to work with competitive interest rates, borrow without selling, and trade with precision. All in one platform. Geographic restrictions, eligibility, and terms apply.

Get started with Nexo.

Rate This Project

User Reviews

Be the first to post a review of MITRE Identification Scrubber Toolkit!

Additional Project Details

Intended Audience

Healthcare Industry

Programming Language

Java, JavaScript, Python

Registered

2010-09-28

Report inappropriate content

Full-stack observability with actually useful AI | Grafana Cloud

Our generous forever free tier includes the full platform, including the AI Assistant, for 3 users with 10k metrics, 50GB logs, and 50GB traces.

Built on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.

Create free account

Recommended Projects

PasteGuard
Masks sensitive data and secrets before they reach AI
Mist Cloud Management Platform
Mist is an open source, multicloud management platform
WaterfallGrid
A waterfall grid layout view for SwiftUI
MIST
A MATLAB toolbox to simulate optical systems
Coding Analysis Toolkit
The Coding Analysis Toolkit (or "CAT") consists of a ASP.NET based suite of tools to facilitate efficient and effective analysis of text datasets that have been coded using the CAT coding module or ATLAS.ti.