AI Health Frontiers: A Practical Workshop for Healthcare Leaders in São Paulo
Fabio Ynoe de Moraes, Radiation Oncologist and Associate Professor at Queen's University, is convening a hands-on Healthcare AI Workshop and Immersion in São Paulo. The goal is simple: help healthcare leaders turn credible AI evidence into outcomes that matter-better care, safer decisions, and more efficient operations.
This isn't theory. It's structured discussion, real use cases, and clear frameworks you can take back to your hospital, clinic, or health organization.
Event Snapshot
- Location: São Paulo
- Date: December 3
- Time: 8:30-3:00 pm
Who it's for: hospital and clinic executives, department heads, physicians with leadership roles, quality and safety managers, data and IT leaders, payers, and industry partners.
What You'll Walk Away With
- A shared, plain-language vocabulary for AI in healthcare: models, validation, bias, drift, and safety.
- A practical checklist to select high-impact clinical and operational use cases.
- Methods to assess evidence quality, feasibility, and ROI-before you buy or build.
- A governance blueprint covering privacy, security, equity, and local regulations (including LGPD).
- An implementation playbook: workflow integration, change management, and procurement essentials.
- Clear metrics that tie to outcomes: quality, safety, throughput, cost, and clinician time.
Why It Matters Now
AI is moving from pilots to production in areas like imaging triage, clinical documentation, and service-line operations. Leaders need a way to separate signal from hype, reduce risk, and deliver measurable value to patients and clinicians.
This immersion connects real AI advances to your institutional reality-constraints, budgets, data, and frontline workflows.
Topics on the Agenda
- Clinical decision support: evidence standards, validation, and safety monitoring.
- Radiation oncology and radiology use cases with practical guardrails.
- Documentation and ambient scribe tools: accuracy, privacy, and clinician workflow.
- Operations: scheduling, capacity, length of stay, and throughput.
- Bias, data quality, and equity: testing and mitigation in practice.
- Regulatory and ethics updates, including guidance from WHO on AI for health and the FDA's AI/ML framework.
Format
Short expert briefings, case discussions, and peer exchange, followed by working sessions. You'll leave with a one-page action plan for a priority use case tailored to your setting.
Who Should Attend
- Hospital and clinic executives (CEO, COO, CFO, CMIO, CNIO, CIO)
- Clinical department leads and service-line managers
- Quality, safety, and patient experience leaders
- Data, analytics, and IT teams
- Payers, life sciences, and health-tech partners
Prepare Before You Arrive
- List 2-3 high-friction workflows you want to improve (clinical or operational).
- Note your data access, integration, and governance constraints.
- Define the outcome metrics you care about-then prioritize one.
Registration
Seats are limited. Register now to secure your spot.
Fabio Ynoe de Moraes' work and perspectives have been featured across oncology circles and platforms like OncoDaily, reflecting a strong focus on evidence-based AI adoption in cancer care and beyond.
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