Andrew Ting, MD has built his career on thoughtful problem-solving, careful analysis, and a deep understanding of how medical decisions are made in real clinical settings. After years of direct patient care, he recognized an opportunity to apply his experience in a new and rapidly evolving direction. Today, he is dedicated to helping AI companies and start-ups train and improve AI in the medical space, ensuring that emerging technologies reflect the realities, challenges, and nuances of clinical practice.
His work focuses on bringing medical insight into model development, guiding teams toward solutions that enhance accuracy, safety, and practical usability. By combining his clinical expertise with a commitment to innovation, Dr. Ting supports the creation of tools that strengthen medical decision-making and improve patient outcomes. This website expands on that mission, sharing perspectives shaped by decades of hands-on experience and a forward-looking approach to the future of healthcare.
Andrew Ting, MD discovered his passion for medicine early in life, drawn to the way small changes within the body could influence overall health. He spent much of his youth exploring subjects that explained how the body heals, adapts, and responds to care. This curiosity naturally guided him toward a pre-medical track as an undergraduate, where he immersed himself in courses that strengthened his scientific understanding and shaped his clinical instincts.
Those formative years gave him the academic foundation he needed for a meaningful career in medicine, reinforcing both discipline and purpose. What began as a simple interest soon developed into a lasting commitment to learning how to restore health, ease discomfort, and support long-term well-being for the patients he would one day serve. Today, Dr. Andrew Ting is applying that same dedication to innovation by helping AI companies and start-ups with training and improving AI in the medical space.
During residency, Dr. Andrew Ting discovered how essential clear reasoning, clinical judgment, and real-world insight are in delivering effective medical care—an understanding that now shapes his work beyond traditional practice. Today, he applies that same foundation to helping AI companies and start-ups with training and improving AI in the medical space. Drawing on years of hands-on clinical experience, he brings attentiveness, adaptability, and a deep respect for the complexities of medical decision-making to the development of technologies that aim to enhance patient care and support clinicians.
Improving AI in the medical space requires thoughtful decision-making, precise judgment, and an understanding of how complex data interacts in real clinical environments. Andrew Ting, MD approaches this work with the same depth of care and clarity that shaped his medical career. He recognizes that developing effective medical AI tools demands more than technical expertise—it calls for insight into real-world workflows, patient variability, and the nuanced reasoning clinicians rely on every day.
Andrew Ting believes that AI systems should be designed around the unique needs of healthcare providers and the patients they serve. By drawing on his clinical experience, he helps companies understand the medical context behind their technology, ensuring that models are trained, tested, and refined with practical, human-centered considerations in mind. Through careful observation, collaboration, and a commitment to accuracy, he guides teams toward solutions that enhance reliability, safety, and usability. His personalized, thoughtful approach supports the creation of AI tools that improve decision-making, strengthen clinical care, and ultimately raise the standard of health outcomes.
Alongside his clinical background, Andrew Ting, MD is committed to advancing the development of AI tools that strengthen medical decision-making and improve patient care. He emphasizes the importance of designing systems that reflect real clinical needs, support physicians in high-pressure environments, and enhance accuracy without adding unnecessary complexity. By helping AI companies understand how clinicians think, interpret information, and respond to evolving situations, he ensures that the technology is built on a foundation of practicality and clarity.
A significant part of his work involves guiding teams through identifying which features genuinely improve clinical workflows and which elements may unintentionally create obstacles. He takes time to explain why certain refinements matter, enabling developers to implement changes that result in more intuitive, reliable tools. This focus on thoughtful, purpose-driven improvement not only enhances the day-to-day usability of medical AI systems but also supports safer and more effective care—helping the technology grow in ways that truly benefit patients and the professionals who serve them.