Our Autonomous Healthcare Expert Team
T1. Clinical Domain Experts (The "Teachers" & Supervisors)
Lead: Dr. June Lee, MD, PhD, Executive Deputy Director and Chief Medical Officer (CMO)
Email: JLee@nsmsusa.org
These experts define the "ground truth." They provide the medical knowledge, surgical techniques, and decision-making logic that the AI must learn.
● Surgical Specialists:
○ Neurosurgeons: Crucial for high-precision, microsurgical tasks (e.g., tumor removal, aneurysms) where the margin for error is sub-millimeter.
○ Cardiothoracic Surgeons: Essential for autonomous systems addressing moving targets (beating hearts) and complex vascular reconstruction.
○ Orthopedic Surgeons: Needed for robotic bone handling, drilling, and implant alignment (already a mature field in robotics).
○ Interventional Radiologists: Experts in image-guided, minimally invasive procedures. Key for teaching robotic navigation via catheters and needles.
○ Trauma Surgeons: Vital for designing systems that can handle "unstructured" emergencies where speed and adaptability are critical.
● Medical Treatment Specialists:
○ Clinical Pharmacologists: Essential for defining autonomous drug delivery algorithms, managing drug-drug interactions, and pharmacokinetics (how the body processes drugs in real-time).
○ Anesthesiologists: Required to automate sedation levels, pain management, and vital sign monitoring during autonomous procedures.
○ Intensivists (ICU Doctors): For designing systems that autonomously manage life support, ventilators, and fluid resuscitation.
Our Autonomous Healthcare Expert Team
T2. Technical & Robotics Engineering (The "Builders")
Lead: Dr. Emily Brown, PhD, Director and Chief Engineer
Email: EBrown@nsmsusa.org
These experts build the physical hardware that interacts with the patient.
● Mechatronics Engineers: Design the robotic arms, end-effectors (tools), and actuators that mimic or exceed human dexterity.
● Haptics Engineers: Specialists in "touch" technology. They enable the robot to "feel" tissue density, identifying the difference between a nerve, a vein, and a tumor.
● Bio-MEMS Engineers: (Micro-Electro-Mechanical Systems) Create microscopic robots or sensors (like "smart dust" or nanobots) for internal treatments.
● Soft Robotics Engineers: Focus on making robots out of compliant materials that are safer for human contact and can navigate delicate tissue without damaging it..
Our Autonomous Healthcare Expert Team
T3. AI & Computational Experts (The "Brains")
Lead: Dr. June Lee, MD, PhD, Executive Deputy Director and Chief Healthcare AI Architect
Email: JLee@nsmsusa.org
These experts build the software that perceives the environment and makes decisions.
● Computer Vision Specialists: Build the eyes of the system. They train models to segment anatomy (e.g., "this pixel is liver, this pixel is an artery") from camera feeds, MRI, or CT data.
● Deep Reinforcement Learning (RL) Experts: Train agents to make sequences of decisions (e.g., the best path to cut) by simulating millions of surgeries.
● Medical Data Scientists: Clean and annotate the massive datasets required to train the AI (scrubbing noisy hospital data).
● Sim-to-Real Engineers: Specialize in ensuring that what a robot learns in a physics simulator (virtual world) translates accurately to the messy reality of a human body.
Our Autonomous Healthcare Expert Team
T4. Regulatory, Safety & Ethics (The "Guardrails")
Lead: Dr. Christopher Johnson, PhD, Chief Regulatory Affairs Officer
Email: CJohnson@nsmsusa.org
Autonomous healthcare faces extreme scrutiny; these roles ensure the technology is legal, safe, and accepted.
● Bioethicists: Address the moral dilemmas of autonomous care (e.g., "Who is responsible if the robot makes a mistake?").
● Regulatory Affairs Specialists (FDA/EMA): Experts in the specific pathways for "Software as a Medical Device" (SaMD) and autonomous surgical robotics approval.
● Medical Cybersecurity Experts: Protect the system from being hacked. (A hacked autonomous surgeon is a lethal weapon).
● Human Factors Engineers: Design the interface between the human oversight team and the autonomous robot to prevent "automation bias" (where humans trust the robot too much and stop paying attention).
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