The AI Governance Game-Changer: How to Create Bias-Free Healthcare Solutions?
Can AI make healthcare feedback fairer and smarter? In Episode 4 of The Healthcare AI Podcast, Ben Webster (VP of AI Solutions at NLP Logix) and David Talby (CEO of John Snow Labs) dive into a game-changing approach to AI governance. Discover how LangTest tackles bias in processing 1.5M hospital feedback audio files annually, ensuring fair sentiment analysis and actionable insights. From eliminating gender bias in nurse vs. doctor feedback to building robust, ethical AI models, this episode is a must-watch for healthcare and AI innovators! Join the Conversation: What’s the biggest challenge in healthcare AI today? Comment below!Timestamps06:18 – Bias in patient-feedback NLP 07:13 – LangTest & synthetic debiasing 12:30 – Data contamination & custom benchmarks 15:19 – Robustness testing & augmentation 20:18 – Medical red-teaming & safety checks 23:44 – Clinical cognitive biases in LLMsListen on your favourite platform: • YouTube: https://www.youtube.com/playlist?list=PL5zieHHAlvApZKkwtu746ivthRc5zyTiU• 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/5b1f49a6-dba8-479e-acdf-9deac2f8f60e/the-healthcare-ai-podcast 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 #AIinHealthcare #AIBias #EthicalAI #AIGovernance #NLP #HealthTech #PatientFeedback #HealthcareAI
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First Steps with Model Context Protocol (MCP). Healthcare use-cases
Dive into Episode 3 of the Healthcare AI Podcast, where Vishnu Vettrivel and Alex Thomas explore the growing world of Model Context Protocol (MCP) with a focus on Healthcare MCP (HMCP) from Innovaccer. This episode breaks down the essentials of MCP, from converting papers to N-Triples to deploying on Claude Desktop. Learn about resources, prompts, and tools that empower AI models, plus key security considerations. Stick around for a call to action to spark your thoughts on agentic frameworks! Tune in to discover why MCP could be the next big leap for AI in Healthcare. Timestamps 01:01 – Introducing the Model Context Protocol (MCP): Purpose & Core Concepts 05:44 – Healthcare MCP (HMCP) by Innovaccer 06:50 – Basics of MCP: Resources, Prompts, Tools 10:50 – Demo: Deploying to Claude Desktop (Example MCP Project) 22:24 – Healthcare Relevance & HMCP 23:46 – Security & Limitations 27:30 – Future Directions Listen on your favourite platform: • YouTube: https://www.youtube.com/playlist?list=PL5zieHHAlvApZKkwtu746ivthRc5zyTiU • 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/5b1f49a6-dba8-479e-acdf-9deac2f8f60e/the-healthcare-ai-podcastResources: - Model Context Protocol: https://modelcontextprotocol.io/overview - Introducing HMCP: A Universal, Open Standard for AI in Healthcare: https://innovaccer.com/resources/blogs/introducing-hmcp-a-universal-open-standard-for-ai-in-healthcare - We built the security layer MCP always needed: https://blog.trailofbits.com/2025/07/28/we-built-the-security-layer-mcp-always-needed/ 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 #MCP #ModelContextProtocol #HealthcareAI #MedicalData #AgenticAI #ClinicalAI #DataScience #HealthTech
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De-Identification in Multimodal Medical Data (Text, PDF, DICOM) to stay HIPAA & GDPR Compliant
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. Timestamps00:00 – Welcome & Episode Overview02:43 – How Databricks supports secure De‑identification workflows03:50 – Built-in techniques: masking, encryption, hashing05:26 – Introduction to Multimodal Data De-Identification07:15 – OCR + NLP pipeline for visual & text data – PHI Extraction08:35 – Notebook demo: PHI identification in clinical notes12:00 – PDF de-identification12:56 – DICOM file de-identification14:18 – Output: consistent masking across all modalitiesListen on your favourite platform: • YouTube: https://www.youtube.com/playlist?list=PL5zieHHAlvApZKkwtu746ivthRc5zyTiU • 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/5b1f49a6-dba8-479e-acdf-9deac2f8f60e/the-healthcare-ai-podcastResources:• John Snow Labs Models Hub: https://nlp.johnsnowlabs.com/models• Spark NLP Workshop Repo: https://github.com/JohnSnowLabs/spark-nlp-workshop• Visual NLP Workshop Repo: https://github.com/JohnSnowLabs/visual-nlp-workshop• JSL Docs: https://nlp.johnsnowlabs.com/docs• JSL Live Demos: https://nlp.johnsnowlabs.com/demos• JSL Learning Hub: https://nlp.johnsnowlabs.com/learnConnect 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#HealthcareAI #DataPrivacy #HIPAA #PHI #DeIdentification #MedicalAI #GDPR #HealthTech #MultimodalAI
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AI Meets Healthcare: Evaluating LLMs on Medical Tasks
Welcome to the first episode of The Healthcare AI Podcast, presented by John Snow Labs! Join John Snow Labs CEO David Talby and CTO Veysel Kocaman, as they crack open the future of medicine. They’ll reveal how state-of-the-art Healthcare AI is transforming the industry, directly comparing leading Frontier LLMs like OpenAI's GPT-4.5, Anthropic's Claude 3.7 Sonnet, and John Snow Labs’ Medical LLM. Dive deep into critical clinical tasks, from summarization and information extraction to de-identification and clinical coding. You'll get expert insights from practicing doctors evaluating these models for factuality, relevance, and conciseness, demonstrating which AI truly delivers. Bonus, understand the significant cost differences and learn why private, on-premise deployment is a game-changer for data privacy and compliance. You'll walk away with a deeper knowledge of the models poised to revolutionize healthcare, ensuring accuracy and compliance in your AI initiatives. Episode Highlights & Timestamps: 0:00 - Welcome & Episode Overview 0:48 - Benchmarking Frontier LLMs & Clinical NLP 2:00 - The Competitors: OpenAI, Anthropic, AWS, Azure, Google 3:15 - Introducing John Snow Labs Medical LLMs 6:42 - Why AI Evaluation is Critical in Healthcare 9:48 - Blind Evaluation by Medical Doctors: Methodology 15:12 - Overall Preference: John Snow Labs vs. GPT-4.5 & Claude Sonnet 3.7 22:56 - Clinical Information Extraction Benchmarks 27:08 - Advanced NLP: Named Entity Recognition (NER) Deep Dive 29:53 - Assertion Status Detection: the crucial role of context (e.g., patient denies pain vs. father with Alzheimer's) and how different solutions compare in accuracy. 35:37 - Medical Coding with RxNorm: the way of mapping clinical entities to standardized terminologies and the performance metrics for RxNorm. 39:18 - The Clinical De-identification of PHI Data: the most critical privacy use case in healthcare Connect with us: Our website: https://www.johnsnowlabs.com/ LinkedIn: https://www.linkedin.com/company/johnsnowlabs/ Facebook: https://www.facebook.com/JohnSnowLabsInc/ Twitter: https://x.com/JohnSnowLabs
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.
Brasil