Harvey Castro, MD, MBA.

ChatGPT Healthcare Advisor • Physician with Executive MBA • AI in Healthcare Author Ex-CEO & Physician, aiding in AI's healthcare integration. Empowering physicians, patients, authoring the AI in healthcare revolution.

Confused on AI implementation? We help 👋 | Top AI Voice | Founder of Everyday AI, a Top 10 Tech Podcast | AI Strategist | AI Consultant | AI Keynote Speaker | Helping companies leverage GenAI

At 2 a.m. in the emergency room, seconds decide outcomes.
Soon, those same decisions will be shaped by AI models, planetary-scale data, and infrastructure that lives beyond Earth.

I’m Dr. Harvey Castro, an ER physician and Chief AI Officer at Phantom Space, working at the intersection of medicine, artificial intelligence, and space-based computing to help healthcare move from reactive to predictive without losing its humanity.

For over 20 years, I treated crisis after it walked through the door.
That experience shaped my conviction: the future of healthcare isn’t faster reactions, it’s earlier signals.

Today, I focus on how:

AI + clinical data

Edge computing, satellites, and orbital data centers

Human-centered design

can work together to anticipate illness, reduce burnout, and protect patient safety at scale.

What I’m working on now

Serving as Chief AI Officer at Phantom Space, helping design AI strategies that leverage space-based data pipelines and resilient orbital infrastructure for real-world health impact

Advising health systems, governments, and regulators on safe, ethical, deployable AI

Translating frontier technologies generative AI, ambient sensing, edge inference into tools clinicians can actually trust and use

Chief Executive Officer

Medical Intelligence Ops, where we are pioneering the integration of Large Language Models (LLMs) into healthcare. Our physician-led team is committed to transforming patient care and hospital operations through intelligent solutions.

We are automating decisions we haven’t fully defined.

That’s the risk hiding in plain sight.

Before automation, humans absorbed ambiguity.
Context.
Judgment.
Nuance.

AI doesn’t absorb gaps.
It locks them in.

If a decision isn’t clearly defined,
AI will still execute it.
At scale.
With confidence.

Healthcare learned this the hard way.

When criteria are vague, automation doesn’t clarify them.
It hardens them.

Memorable line:
If you can’t explain a decision, you shouldn’t automate it.

AI doesn’t remove ambiguity.
It forces it to choose.

The leadership question is simple and uncomfortable.
Do we actually agree on how this decision should be made?

If the answer is no,
automation will decide for you.

Best practices before automating decisions:

Define decision boundaries in plain language
Document assumptions and failure modes
Separate judgment from execution
Require human review where stakes are high
Refuse to automate what cannot be explained

AI doesn’t just execute decisions.
It exposes the ones we never fully understood.

Organizations that recognize this early will avoid scaling the wrong logic.

Harvey Castro, MD, MBA.  #drgpt
Follow me and repost

#AI #ArtificialIntelligence #Leadership #ResponsibleAI #AIGovernance
#DecisionMaking #DigitalTransformation #RiskManagement #HumanCenteredAI #DrGPT

Harvey Castro

AI isn’t coming to healthcare.

It’s already here and most leaders aren’t ready.

This morning, I had the honor of serving as the keynote speaker at the 2026 Executive Leadership Conference for the American Academy of Physician Associates.

In the room: 300+ #PA and #NP leaders from across the country.

Not beginners.

Decision-makers.

The people who determine whether AI becomes noise…
or becomes patient impact.

We didn’t talk about shiny demos.

We talked about consequences.

Here’s what we unpacked:

• The 10M global workforce shortage and why AI + Clinician is no longer optional

• Automation bias and the “GPS effect” quietly reshaping clinical judgment

• How AI hallucinations could create Medicare fraud exposure

• Dataset bias in dermatology and genomic blind spots

• The rise of shadow AI inside hospitals

• And why empathy remains the most advanced technology in medicine

But the most important conversation wasn’t technical.

It was responsibility.

AI moves exponentially.
Healthcare systems move linearly.

That gap creates pressure.

Pressure creates mistakes.

And mistakes in medicine cost lives.

For years, I’ve said:

AI + Clinician > AI alone or Clinician alone

Today, I updated it:

AI + Clinician = Survival
Not because AI replaces us.

But because the demand curve, burnout rates, and complexity of care are outpacing human capacity alone.

AI is not the captain of the ship.

You are.

AI is the lighthouse.

Grateful for the thoughtful questions on governance, regulation, and responsible implementation and for the leaders who stayed after to wrestle with the hard parts.

The future of healthcare won’t be written by algorithms.

It will be written by clinicians courageous enough to shape how those algorithms are used.

The real question is:

Will we design AI around medicine…

Or redesign medicine around AI?

#HealthcareAI #PAleadership #AIethics #DigitalHealth #FutureOfHealthcare #aapa

No alternative text description for this image

Great interview! We talked about TEDx talks and more.

Interested in becoming a TEDx speaker? 


On GRASP Confidence Podcast, I sat down with Harvey Castro, MD, MBA. physician, healthcare innovator, and TEDx speaker to unpack what it really takes to step onto the red dot and how to turn it into momentum for your speaking career.

From refining your message to understanding how organizers choose speakers, Harvey shares insights every aspiring TEDx speaker should hear.

If you feel called to share an idea that could impact lives, this conversation will help you move from thinking about it… to pursuing it.


Your voice matters.



#GRASPConfidencePodcast

Everyone talks about AI making cities smarter.

Fewer people talk about what happens when those systems fail.

As AI becomes embedded across transport, energy, healthcare, and public services, something new emerges:

Interconnected intelligence.

But interconnected systems have a hidden property.

When one breaks…
others can fall with it.

This is one of the central questions we explored in this new whitepaper on AI governance for digital public services and smart cities.

Proud to contribute alongside an incredible group of global experts.

One insight stood out:

Smart city systems are becoming critical infrastructure.
And critical infrastructure must be designed for resilience not just efficiency.  

That means thinking about:

• interoperability across vendors
• transparency and explainability
• fallback modes when systems fail
• human oversight in high-risk decisions

From my perspective working on AI infrastructure at Phantom Space, resilience may also require rethinking where compute lives.

Edge.
Cloud.
And eventually space-based infrastructure designed to keep AI systems operating even when terrestrial systems fail.

Because the future of AI isn’t just smarter software.

It’s resilient intelligence infrastructure.

Curious what others think:

What is the biggest risk we face as cities become AI-driven?


#AI #SmartCities #AIgovernance #TrustworthyAI #Infrastructure #DrGPT

📢 𝐖𝐇𝐈𝐓𝐄𝐏𝐀𝐏𝐄𝐑: 𝐂𝐚𝐧 𝐀𝐈-𝐩𝐨𝐰𝐞𝐫𝐞𝐝 𝐬𝐦𝐚𝐫𝐭 𝐜𝐢𝐭𝐢𝐞𝐬 𝐝𝐞𝐥𝐢𝐯𝐞𝐫 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐡𝐚𝐫𝐦𝐢𝐧𝐠 𝐑𝐄𝐒𝐈𝐋𝐈𝐄𝐍𝐂𝐄 [𝐇𝐢𝐧𝐭: 𝐢𝐧𝐭𝐞𝐫𝐜𝐨𝐧𝐧𝐞𝐜𝐭𝐞𝐝 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐜𝐫𝐞𝐚𝐭𝐞 𝐜𝐚𝐬𝐜𝐚𝐝𝐢𝐧𝐠 𝐁𝐈𝐆 𝐟𝐚𝐢𝐥𝐮𝐫𝐞𝐬.]

📜 𝐃𝐢𝐠𝐢𝐭𝐚𝐥 𝐏𝐮𝐛𝐥𝐢𝐜 𝐒𝐞𝐫𝐯𝐢𝐜𝐞𝐬: GOVERNANCE Challenges in AI-Enabled Smart Cities examines how Europe can build interoperable, trustworthy urban infrastructure as AI becomes core to transport, energy, HEALTH, and public administration - linked-high-risk sectors under European Commission's EU AI Act. 

As municipalities rapidly deploy AI-driven services—𝘧𝘳𝘰𝘮 𝘵𝘳𝘢𝘧𝘧𝘪𝘤 𝘮𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵 𝘵𝘰 𝘴𝘮𝘢𝘳𝘵 𝘮𝘦𝘵𝘦𝘳𝘪𝘯𝘨 𝘵𝘰 𝘥𝘪𝘨𝘪𝘵𝘢𝘭 𝘩𝘦𝘢𝘭𝘵𝘩 𝘳𝘦𝘤𝘰𝘳𝘥𝘴—the challenges extend beyond individual systems. Tightly coupled platforms, cross-border data flows, and multi-vendor service chains create systemic RISKS that can cascade across sectors and jurisdictions, affecting millions of citizens simultaneously.

Developed by AI & Partners with a global network of legal, technical, policy, and civil-society experts, the whitepaper explores how regulatory frameworks can operationalise fairness, transparency, and operational resilience in smart city deployments—while enabling the efficiency and inclusion benefits of digital transformation.

𝐊𝐞𝐲 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬 𝐟𝐫𝐨𝐦 𝐭𝐡𝐞 𝐑𝐞𝐩𝐨𝐫𝐭
+++ 𝑰𝒏𝒕𝒆𝒓𝒐𝒑𝒆𝒓𝒂𝒃𝒊𝒍𝒊𝒕𝒚 𝒂𝒔 𝑰𝒏𝒇𝒓𝒂𝒔𝒕𝒓𝒖𝒄𝒕𝒖𝒓𝒆 – Why open standards, data portability, and cross-border coordination are essential to prevent vendor lock-in and enable seamless service delivery.
+++ 𝑹𝒆𝒔𝒊𝒍𝒊𝒆𝒏𝒄𝒆 𝒃𝒚 𝑫𝒆𝒔𝒊𝒈𝒏 – How AI systems supporting critical urban functions must include fallback modes, incident reporting, and graceful degradation to prevent cascading failures.
+++ 𝑷𝒓𝒊𝒗𝒂𝒄𝒚 𝒊𝒏 𝑴𝒖𝒍𝒕𝒊-𝑺𝒆𝒏𝒔𝒐𝒓 𝑬𝒏𝒗𝒊𝒓𝒐𝒏𝒎𝒆𝒏𝒕𝒔 – Why extensive sensor networks and data fusion require privacy-by-design and explicit safeguards for marginalised communities.

🙏 Special thanks to our contributors:
• Sean Musch, AI & Partners
• Michael Charles Borrelli, AI & Partners
• Dr. Don Liyanage
• Dr. Benedikt Kohn
• Harvey Castro, MD, MBA.
• Lisa Ventura MBE FCIIS MBCS
• Helen Yu
• Mariia Shcherbakova 
• Patrick Orsos 
• Shreyas Karanjkar
• Edward Cole 
• Neil Oschlag-Michael 
• Mitko Karushkov 
• Vibhav Mithal, FHCA
• Mateo Jarrin Cuvi
• Michael Boevink 布 纷 奇 , 마이클 보빈크, مايكل بوفينك
• Ina Schöne
• Richard Chiumento 
• Carolyn Harrison
• And the many global experts and partners shaping responsible, human-centric AI governance

—

💬 For policymakers, public authorities, and system designers: Where do you see the hardest trade-off today?

#Law #Policy #TrustworthyAI #government #publicservices

W-DPS

Helping companies achieve EU AI Act compliance

As a Director at AI & Partners, Europe's leading professional services firm for firms subject to the EU AI Act, this leverages 10+ years of experience in financial services, compliance, and technology to help clients navigate the complex and evolving regulatory landscape of AI. This includes a strong passion for responsible AI and its potential to create positive social impact, while minimizing its risks and challenges.

In addition to this role at AI & Partners, responsibilities include serving as a IoD Finance and FinTech Ambassador and an AI 2030 Chapter Advisor, where contributions are made to the development and dissemination of knowledge, best practices, and policy recommendations on AI and FinTech. Additionally, a Master of Laws in Financial Regulation and Compliance, an Oxford FinTech Programme certificate, and a Google Cloud Introduction to Responsible AI certificate are held, among others. Other skills include being a prolific writer and speaker on topics related to AI, FinTech, and compliance, having published multiple articles and delivered several presentations at various events and platforms.

Michael Charles Borrelli

AI & Partners - 🌍 Excited to Speak at Media Law International’s Sixth Annual Global Conference (AGC6)! 🎤

I’m honoured to be joining an incredible lineup of industry leaders at Media Law International’s Sixth Annual Global Conference (AGC6) on 7 May 2026 — a premier gathering of global media law professionals, including CNBC! 🚀✨ 

This event brings together senior decision-makers, in-house legal teams, founders, CEOs, and thought leaders to explore the trends shaping the future of media, technology, regulation and legal practice. 🌐👩‍⚖️ Whether you’re seeking fresh insights, deep industry connections, or vibrant discussions on the evolving media landscape, this is one not to miss! 

I’m truly grateful for the opportunity to speak alongside such distinguished professionals — thank you to Media Law International,  and Mediaspace.global for inviting me to contribute. 🙏💡 

👉 Why you should attend:
✨ Gain thought-leadership insights from global experts
🤝 Expand your network with senior leaders and innovators
📈 Engage in conversations that will shape the media and legal ecosystem 

Don’t miss this chance to be part of a meaningful and forward-looking conversation — see you there! 💼🎟️

https://lnkd.in/eybCAUc3?

#AGC6 #MediaLaw #Networking #LegalInnovation #ThoughtLeadership Kinga Incze Zineb Serroukh-Ouarda

AI & Partners - Excited to see The Economist Impact convene finance and business leaders in London this March for:
➡️ AI for CFOs Summit
➡️ AI & Business Innovation Summit
📍 Convene 155 Bishopsgate

Two days focused on turning AI into real enterprise value — from forecasting and automation to governance and scalable innovation.

Looking forward to the insights and conversations.

Find out more > https://lnkd.in/eEk_ykHT

Hannah Flynn

TE-PR

AI & Partners - It’s officially live.

In collaboration with the Fin.Tech Marketing Community , we’ve launched the EU AI Act Learning Course — now open for registration.

If you’re operating in the UK or Europe, working with European clients, or leading teams that use AI across marketing, product, or data this is no longer optional. The EU AI Act is here, and understanding its impact is now a leadership responsibility.

I’m seeing ambitious teams move fast with AI adoption - but without full clarity on risk categorisation, governance structures, and accountability. That’s exactly why we built this course: to bridge the gap between regulatory theory and practical business execution.

Here’s what you’ll gain:

🔹 Clear understanding of AI risk “buckets” and what applies to your organisation
🔹 Governance frameworks that enable innovation without exposing your business to heavy non-compliance fines
🔹 A practical assessment and certification to confidently lead your team’s transition

🔥 We’re offering a 50% Launch Discount until 13 March 2026  and we’re already seeing strong early interest.

Ready to lead the transition? Check out the course brochure here - https://lnkd.in/e5yKrJS2

Mounika Dasetty

Open article: Download the EU AI Act Course Brochure by fintecb2bmarketing-8580337.hs-sites.com

Fin.Tech Logo (White Logo) for dark backgrounds-01

AI & Partners - 🚨 [REPORT]: QUALITY Management Systems for AI under the EU AI Act (Hint: AI quality is not about model accuracy. It’s about sustained control.]

✅AI systems are now embedded in healthcare, finance, manufacturing, and public administration.

But as adoption accelerates, one issue is becoming unavoidable:

⚠️ 𝐖𝐡𝐨 𝐢𝐬 𝐀𝐂𝐂𝐎𝐔𝐍𝐓𝐀𝐁𝐋𝐄 𝐟𝐨𝐫 𝐀𝐈 𝐛𝐞𝐡𝐚𝐯𝐢𝐨𝐮𝐫 𝐨𝐧𝐜𝐞 𝐢𝐭 𝐥𝐞𝐚𝐯𝐞𝐬 𝐭𝐡𝐞 𝐥𝐚𝐛?

Our new report, “EU AI Act – Quality Management Systems: Facilitating AI System Outputs,” examines how organizations can operationalize governance under the EU AI Act — moving from abstract COMPLIANCE requirements to structured, lifecycle-based control.

𝐅𝐫𝐨𝐦 𝐅𝐫𝐚𝐠𝐦𝐞𝐧𝐭𝐞𝐝 𝐂𝐨𝐧𝐭𝐫𝐨𝐥𝐬 → 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞𝐝 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞
Many organizations approach AI quality incrementally:
 — Controls differ across teams
 — Data governance is inconsistent
 — Intended purpose is loosely defined
 — MONITORING is reactive

A mature AI Quality Management System (QMS) changes this by embedding GOVERNANCE across the full lifecycle:
— Design and change control
— Structured development and validation
— Data management with traceability
— Risk integration across functions


𝐐𝐮𝐚𝐥𝐢𝐭𝐲 𝐈𝐬 𝐚 𝐒𝐲𝐬𝐭𝐞𝐦, 𝐍𝐨𝐭 𝐚 𝐂𝐡𝐞𝐜𝐤𝐥𝐢𝐬𝐭
The report highlights three foundational principles:
1. 𝑳𝒊𝒇𝒆𝒄𝒚𝒄𝒍𝒆 𝑻𝒉𝒊𝒏𝒌𝒊𝒏𝒈
AI risks evolve in operation. Monitoring, feedback loops, and corrective mechanisms must be embedded — not improvised.

2. 𝑫𝒊𝒔𝒕𝒓𝒊𝒃𝒖𝒕𝒆𝒅 𝒃𝒖𝒕 𝑫𝒆𝒇𝒊𝒏𝒆𝒅 𝑹𝒆𝒔𝒑𝒐𝒏𝒔𝒊𝒃𝒊𝒍𝒊𝒕𝒚
Makers, users, and suppliers each hold differentiated obligations. Governance fails where accountability is ambiguous.

3. 𝑷𝒓𝒐𝒑𝒐𝒓𝒕𝒊𝒐𝒏𝒂𝒍𝒊𝒕𝒚 𝑩𝒂𝒔𝒆𝒅 𝒐𝒏 𝑬𝒗𝒊𝒅𝒆𝒏𝒄𝒆 𝒐𝒇 𝑪𝒐𝒏𝒕𝒓𝒐𝒍
More documentation does not equal better governance. What matters is demonstrable oversight, traceability, and the practical ability to intervene.

𝐀 𝐥𝐢𝐯𝐢𝐧𝐠 𝐀𝐈 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 𝐬𝐲𝐬𝐭𝐞𝐦……
1. Under the EU AI Act, AI quality management is not a static compliance artefact. 
2. It is a living governance system that integrates legal, technical, and operational decision-making.
----- Accuracy alone is not sufficient.
----- Documentation alone is not sufficient.
----- Intent alone is not sufficient.

𝐀𝐈 𝐪𝐮𝐚𝐥𝐢𝐭𝐲 𝐮𝐥𝐭𝐢𝐦𝐚𝐭𝐞𝐥𝐲 𝐦𝐞𝐚𝐧𝐬:
 + Clear responsibility.
 + Sustained monitoring.
 + Structured intervention when real-world behaviour changes.

------------------------------------------

With contributions from:
+ Sean Musch, AI & Partners 
+ Michael Charles Borrelli, AI & Partners
+ Michael Charles Borrelli, CMS UK 
+ Chakib Achour
+ Dr. Ian Gauci
+ Jacek Kotarbinski, PhD
+ Yonah Welker 

-------------------------------------------------------

💬 Question for peers and governance leads:
Is your AI oversight framework a documented policy?

#ArtificialIntelligence #AIForBusiness #Digital #Manufacturing #Automotive

🚨 [REPORT]: QUALITY Management Systems for AI under the EU AI Act (Hint: AI quality is not about model accuracy. It’s about sustained control.]

✅AI systems are now embedded in healthcare, finance, manufacturing, and public administration.

But as adoption accelerates, one issue is becoming unavoidable:

⚠️ 𝐖𝐡𝐨 𝐢𝐬 𝐀𝐂𝐂𝐎𝐔𝐍𝐓𝐀𝐁𝐋𝐄 𝐟𝐨𝐫 𝐀𝐈 𝐛𝐞𝐡𝐚𝐯𝐢𝐨𝐮𝐫 𝐨𝐧𝐜𝐞 𝐢𝐭 𝐥𝐞𝐚𝐯𝐞𝐬 𝐭𝐡𝐞 𝐥𝐚𝐛?

Our new report, “EU AI Act – Quality Management Systems: Facilitating AI System Outputs,” examines how organizations can operationalize governance under the EU AI Act — moving from abstract COMPLIANCE requirements to structured, lifecycle-based control.

𝐅𝐫𝐨𝐦 𝐅𝐫𝐚𝐠𝐦𝐞𝐧𝐭𝐞𝐝 𝐂𝐨𝐧𝐭𝐫𝐨𝐥𝐬 → 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞𝐝 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞
Many organizations approach AI quality incrementally:
 — Controls differ across teams
 — Data governance is inconsistent
 — Intended purpose is loosely defined
 — MONITORING is reactive

A mature AI Quality Management System (QMS) changes this by embedding GOVERNANCE across the full lifecycle:
— Design and change control
— Structured development and validation
— Data management with traceability
— Risk integration across functions


𝐐𝐮𝐚𝐥𝐢𝐭𝐲 𝐈𝐬 𝐚 𝐒𝐲𝐬𝐭𝐞𝐦, 𝐍𝐨𝐭 𝐚 𝐂𝐡𝐞𝐜𝐤𝐥𝐢𝐬𝐭
The report highlights three foundational principles:
1. 𝑳𝒊𝒇𝒆𝒄𝒚𝒄𝒍𝒆 𝑻𝒉𝒊𝒏𝒌𝒊𝒏𝒈
AI risks evolve in operation. Monitoring, feedback loops, and corrective mechanisms must be embedded — not improvised.

2. 𝑫𝒊𝒔𝒕𝒓𝒊𝒃𝒖𝒕𝒆𝒅 𝒃𝒖𝒕 𝑫𝒆𝒇𝒊𝒏𝒆𝒅 𝑹𝒆𝒔𝒑𝒐𝒏𝒔𝒊𝒃𝒊𝒍𝒊𝒕𝒚
Makers, users, and suppliers each hold differentiated obligations. Governance fails where accountability is ambiguous.

3. 𝑷𝒓𝒐𝒑𝒐𝒓𝒕𝒊𝒐𝒏𝒂𝒍𝒊𝒕𝒚 𝑩𝒂𝒔𝒆𝒅 𝒐𝒏 𝑬𝒗𝒊𝒅𝒆𝒏𝒄𝒆 𝒐𝒇 𝑪𝒐𝒏𝒕𝒓𝒐𝒍
More documentation does not equal better governance. What matters is demonstrable oversight, traceability, and the practical ability to intervene.

𝐀 𝐥𝐢𝐯𝐢𝐧𝐠 𝐀𝐈 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 𝐬𝐲𝐬𝐭𝐞𝐦……
1. Under the EU AI Act, AI quality management is not a static compliance artefact. 
2. It is a living governance system that integrates legal, technical, and operational decision-making.
----- Accuracy alone is not sufficient.
----- Documentation alone is not sufficient.
----- Intent alone is not sufficient.

𝐀𝐈 𝐪𝐮𝐚𝐥𝐢𝐭𝐲 𝐮𝐥𝐭𝐢𝐦𝐚𝐭𝐞𝐥𝐲 𝐦𝐞𝐚𝐧𝐬:
 + Clear responsibility.
 + Sustained monitoring.
 + Structured intervention when real-world behaviour changes.

------------------------------------------

With contributions from:
+ Sean Musch, AI & Partners 
+ Michael Charles Borrelli, AI & Partners
+ Michael Charles Borrelli, CMS UK 
+ Chakib Achour
+ Dr. Ian Gauci
+ Jacek Kotarbinski, PhD
+ Yonah Welker 

-------------------------------------------------------

💬 Question for peers and governance leads:
Is your AI oversight framework a documented policy — or an operational system with tested controls and clear accountability?

#ArtificialIntelligence #AIForBusiness #Digital #Manufacturing #Automotive

R-QMS

Michael Boevink 布 纷 奇 , 마이클 보빈크, مايكل بوفينك

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Harvey Castro, MD, MBA.'s LinkedIn Performance

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