Meet One of Our Health Board Advisors Expert

Nick Yaitsky

Top Keynote Talk Topics:

  • The Future of
    Depression Care:
    What Weʼre Learning
    From 900+ DBS
    Surgeries A talk that
    breaks down how
    deep brain stimulation
    helps people with severe depression, what the newest NIH-funded research is showing, and how imaging helps predict who will benefit.

  • The Future of Depression Care: What Weʼre Learning From 900+ DBS Surgeries A talk that breaks down how deep brain stimulation helps people with severe depression, what the newest NIH-funded research is showing, and how imaging helps predict who will benefit.

  • When Treatment Fails: New Hope for Patients With Tremor, Parkinsonʼs, and Depression A practical look at what happens when medications stop working and how DBS and focused ultrasound offer strong, lasting results — with real data and clear explanations for clinicians and leaders.

  • Why Advanced Brain Treatments Are Underused — And How We Can Fix It A keynote for health systems, policymakers, and investors about the barriers that keep patients from life-changing treatments, how much this costs the system, and what solutions can improve access.

  • Building Better Brain Implants: What Doctors, Industry, and Patients Really Need Based on Dr. Fenoyʼs experience working with medical device companies and inventing new tools. Covers what makes technology adoptable, what the field is missing, and how to design devices people will actually use.

  • Using Brain Imaging to Guide Care: How fMRI and DTI Are Changing Neurosurgery A simple explanation of how imaging shows brain networks changing over time — and how this helps predict outcomes, improve device placement, and personalize care for movement and mood disorders.

Bio:

Nick Yaitsky serves on the HIMSS Americas Advisory Board and TAG Digital Health Board. He's the former Chief AI Officer at Wellstar Health System and Senior Vice President at Sharecare. With twenty-plus years leading healthcare technology innovation, Nick specializes in AI transformation, digital health platforms, and enterprise governance.

A Trusted Voice:

Top Keynote Talk Topics

  1. AI in Healthcare: What’s Real, What’s Noise, and What Actually Works

    A grounded, no-hype breakdown of what AI truly is (and isn’t) in healthcare, how leaders should think about it, and where organizations waste time chasing buzzwords instead of outcomes.

  2. Building AI-Ready Healthcare Organizations: Governance, Compliance, and Trust

    How healthcare systems and startups can structure AI governance, compliance, and operational guardrails that allow innovation without risking patient safety, data security, or regulatory exposure.

  3. From Buzzword to Backbone: Making AI Native Instead of AI-Labeled

    Why simply “adding AI” doesn’t create value—and how organizations can design AI-native workflows, systems, and decision-making that actually move the needle.

  4. Agentic Systems in Healthcare: What They Are and How to Use Them Responsibly

    A forward-looking talk on agentic AI systems—what they can do today, what they shouldn’t do yet, and how healthcare leaders should think about deploying them safely and strategically.

  5. When AI Is the Wrong Answer: Smarter Automation and Operational Efficiency

    An honest conversation about when AI is unnecessary, when deterministic systems work better, and how leaders can avoid overengineering solutions while still improving workforce and back-office efficiency.

Top Interview Questions:

  1. Everyone is calling themselves an AI company right now—how can healthcare leaders tell the difference between real AI capability and marketing spin?

  2. What does an effective AI governance and compliance framework actually look like inside a healthcare organization?

  3. You’ve said not every problem needs AI—can you share examples where simpler, deterministic solutions outperform AI-driven ones?

  1. Agentic AI systems are getting a lot of attention—what should healthcare leaders understand before deploying them?

  2. What operational and cultural changes need to happen inside an organization before AI can truly be effective?

  3. Looking ahead, what AI capabilities in healthcare are underdeveloped today but likely to have the biggest impact in the next few years?

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