Medical Copilot and Product Lifecycle Copilot Powered by Hopsworks & Neo4j
summary
Medical Copilot centralizes FHIR patient records, runs NVIDIA MONAI x‑ray models, and grounds LLM answers with a vector index and Neo4j so clinical detection, differential diagnosis, and treatment plans cite structured evidence rather than hallucination; it summarizes trends, flags missing history, and supports prompt tuning or model fine‑tuning. PLM Copilot ingests tickets and docs, generates personalized story points, predicts bottlenecks and timelines from graph queries and heuristics, and uses Neo4j for grounding while being built in two to four weeks.
AI-written summary · about
chapters (5)
- 0:00Introduction to Medical Copilot
- 7:45Technical Architecture Overview
- 9:52Live Demo Start
- 17:50Product Lifecycle Copilot
- 22:30Q&A and Summary
related talks
11mDragon Copilot: AI-Powered Clinical Assistant
21mAI Copilot - Enterprise-wide and Heterogeneous
27mRevolutionize Manufacturing with Copilot custom copilots in Teams
09mCopilot App Deep Dive: Intelligence, Context & Agents
55mCopilot is my Copilot: Pair programming with an AI
26mFrom Concept to Prototype
11mLeverage Copilot in Microsoft Loop for productivity and collaboration
49mShaping next-gen development: the future of Copilot in Power Platform
