Agentic AI in Healthcare [in person]

This month we are going to have an in person meeting about AI in Healthcare. BI and Fabric, and also a review of the most important updates recently on the Power BI and Microsoft Fabric, and the AI-related topics about it. Join us for this session of learning and networking.
Agenda:
5:00-5:30 PM Welcome and Networking/Refreshments
5:30-6:30 PM AI in Healthcare
6:30-7:00 PM Wrap Up
Topic 1: Agentic AI in Healthcare: The RAG-Powered Diagnostic Assistant
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Parametric LLM memory cannot support clinical deployment: no provenance, no patient-specific grounding at inference time, and unacceptable hallucination rates. Retrieval-Augmented Generation solves this by grounding an agentic system's reasoning loop in dynamically retrieved, evidence-backed context instead of static model weights.

The architecture: Chunking and embedding heterogeneous clinical data (imaging reports, discharge summaries, structured EHR fields), dense vector indexing with approximate nearest-neighbour retrieval, and context injection into the perceive-reason-act-learn cycle.

Key trade-offs: Retrieval latency versus context window budget, chunk size versus semantic coherence, embedding model selection for domain terminology, and multi-agent coordination for ranking and routing evidence across specialist sub-agents.

Results: 94.1% diagnostic accuracy in liver cancer detection; door-to-balloon time reduced from 211 to 68 minutes in a real cardiac workflow via concurrent retrieval across imaging, history, and evidence.

Open problems: Explainability at the retrieval-to-reasoning boundary, bias propagation through retrieved context, and the validation gap between proof-of-concept and clinical-grade reliability.
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About the speaker: Dr. Saranya Selvarangan
A seasoned academic professional consultant, and data science professional with over 10 years of experience in teaching, research, and consultancy across Information Systems, Business Analytics, Artificial Intelligence, and Data Science. Proficient in developing AI solutions, conducting advanced data analysis, and guiding research initiatives. I hold a PhD in Information and Communication Engineering and am currently pursuing a Master's in Business Data Science, applying my knowledge extensively within educational institutions and universities. Skilled in curriculum development, student mentoring, and leveraging AI-driven insights for problem-solving, I am committed to enhancing both academic and industry outcomes through research and education

Meetup Sponsor:

**RADACAD **is a leading Power BI training and consulting firm and a Microsoft Gold Partner in Data Analytics. We provide training to upskill, consultation to enhance, and expert development support for Data analytics projects using Microsoft Fabric and Power BI.

This is an in-person-only event. Please register to attend here

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We look forward to welcoming you to an evening of insightful discussions and networking with the Microsoft community!