Explore regulatory‑grade multimodal data de‑identification and tokenisation with Youssef Mellah, PhD, Senior Data Scientist at John Snow Labs and Srikanth Kumar Rana, Solutions Architect at Databricks. 
Learn how to remove, mask or transform PHI across clinical notes, tables, PDFs and DICOMs at scale, while meeting HIPAA, GDPR and CCPA standards — all without sacrificing analytical value. 

Timestamps
00:00 – Welcome & Episode Overview
02:43 – How Databricks supports secure De‑identification workflows
03:50 – Built-in techniques: masking, encryption, hashing
05:26 – Introduction to Multimodal Data De-Identification
07:15 – OCR + NLP pipeline for visual & text data – PHI Extraction
08:35 – Notebook demo: PHI identification in clinical notes
12:00 – PDF de-identification
12:56 – DICOM file de-identification
14:18 – Output: consistent masking across all modalities

Listen on:
• ⁠⁠Apple Podcast⁠⁠: https://podcasts.apple.com/us/podcast/the-healthcare-ai-podcast/id1827098175
• ⁠⁠Spotify⁠⁠: https://open.spotify.com/show/2XNrQBeCY7OGql2jVhcP7t 
• Amazon Music⁠⁠: https://music.amazon.com/podcasts


Connect with us:

Our website: https://www.johnsnowlabs.com/
LinkedIn: https://www.linkedin.com/company/johnsnowlabs/
Facebook: https://www.facebook.com/JohnSnowLabsInc/
X: https://x.com/JohnSnowLabs

The Healthcare AI Podcast – Ep. 2: De-Identification in Multimodal Medical Data (Text, PDF, DICOM)

Explore real-world applications of generative AI, large language models, and advanced NLP in The Applied AI Podcast. We dive into healthcare, finance, legal, life sciences, and more with expert interviews, practical case studies, and insights on open-source tools and frameworks. Discover how organizations deploy AI at scale, navigate ethical and technical challenges, and unlock transformative business value. Open and impactful discussions for AI professionals and enthusiasts.

New tracks tagged #DeIdentification