AI expert from Tausight discusses deploying edge AI models to find sensitive data like PHI, challenges in detecting 'dark PHI,' using AI and ML to protect PHI in healthcare, and success stories in safeguarding sensitive data.
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Quick takeaways
Implementing edge AI models can help healthcare providers search for sensitive data efficiently.
Tausight utilizes customized AI models to detect and safeguard PHI across diverse healthcare settings.
Deep dives
The Significance of PHI and Healthcare Data Security
Personal Health Identifiable (PHI) data is highly targeted by hackers due to its valuable information like medical history, social security numbers, and insurance details, leading to identity theft and other illegal activities. Healthcare data breaches, primarily caused by hacking, have increased drastically, affecting millions of Americans. 78% of data breaches result from network hacking, with additional breaches occurring through stolen devices or phishing attacks.
Impacts of Healthcare Data Breaches
Healthcare organizations face significant consequences when data breaches occur, such as public disclosure, penalties, fines, and reputational damage. The cybersecurity costs for healthcare have surpassed billions of dollars without ensuring PHI protection. The 'Wall of Shame' is a platform where government-listed breached organizations face public scrutiny, highlighting the severe repercussions of data breaches.
Challenges in Healthcare AI and Machine Learning
Implementing AI and machine learning in healthcare poses unique challenges due to limited access to real patient data, data heterogeneity, and onsite processing constraints at the edge. Healthcare organizations struggle with detecting unstructured data like 'dark PHI' residing within various file extensions, complicating data monitoring and breach prevention efforts.
Utilizing AI in PHI Detection and Protection
Talsight leverages AI to address the complexity of PHI detection in healthcare, offering optimized models that operate effectively in edge environments. By deploying AI to scan unstructured content, Talsight can detect PHI without relying on rule-based approaches, mitigating false positives and enhancing data protection measures. The adoption of customized and efficient AI models enables Talsight to identify and safeguard sensitive data across diverse healthcare settings.
We’ve all heard about breaches of privacy and leaks of private health information (PHI). For healthcare providers and those storing this data, knowing where all the sensitive data is stored is non-trivial. Ramin, from Tausight, joins us to discuss how they have deploy edge AI models to help company search through billions of records for PHI.
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