During the January Innovation @ UMB session, Florence Doo, MD, shared insights into the digital health innovation landscape.
This article is a summary of the January session of Innovation @ UMB.
In the rapidly evolving landscape of health care, digital health innovation stands at the forefront, promising to revolutionize patient care and medical practices. At the University of Maryland, Baltimore (UMB) and the University of Maryland Institute for Health Computing (UM-IHC), Florence Doo, MD, assistant professor, Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, is leading the charge in integrating artificial intelligence (AI) with health care to create groundbreaking solutions. The landscape has many opportunities, but entrepreneurial researchers must be aware of the many rapid changes in digital health innovation, the translational process, AI, and machine learning applications.
Digital Health Innovation
The intersection of human-AI interfaces is a critical area of focus in digital health innovation. Innovators must creatively think about how AI can enhance human capabilities in health care, not just replace or overtake caregivers. In radiology, for instance, AI tools have been used since 2019 to assist in medical training and diagnostics, such as in pulmonary nodule detection and brain hemorrhage analysis that in some cases have already proven to be superior to humans. These applications demonstrate the potential of AI to improve accuracy and efficiency in medical imaging, so much so that over 50 percent of radiologists now use AI in their practice, highlighting its growing adoption and impact.
Current Work and Future Directions
Fostering an ecosystem for innovation in academic entrepreneurship and digital health care requires bringing together computer scientists, machine learning experts, and health care professionals. This collaborative approach ensures that digital health innovations are not only technologically advanced but also patient-centered and ethically sound. Understanding the entire ecosystem, including U.S. Food and Drug Administration regulations, ethics, and patient care, is crucial for successful innovation.
Translational Process
Translating technology from the bench to the bedside is a complex but essential process in digital health innovation. And the end goal cannot be to replace humans or remove human oversight, but must include digital health innovators.
In her presentation, Doo highlighted the role of digital health innovators in bridging this gap. One example she provided was Katherine Johnson, a NASA computer scientist who exemplified the importance of human oversight in AI. At the time, NASA was using computer calculations for space flights, but Johnson, understanding the critical need for human oversight, also performed the calculations by hand to ensure they were accurate. John Glenn, the first American astronaut to orbit the Earth, placed his life in Johnson’s hands and famously said, "Get the girl to check the numbers. If she says they're good to go, then I'm ready to go." This anecdote exemplifies the importance of human oversight in advanced technologies and underscores the need for careful consideration and validation of AI applications in health care.
AI and Machine Learning
AI and machine learning are at the core of digital health innovation, offering transformative potential by processing unstructured data. In health care, 80 to 90 percent of data is unstructured, including imaging, EKGs, and lab results. Expanding digital innovation to harness this unstructured data is crucial for advancing research, startups, and clinical applications. For instance, AI can automate the labeling of medical images, significantly speeding up processes that would otherwise take extensive time and resources. By moving beyond structured data like language, AI can unlock new opportunities for diagnostics and treatment, revolutionizing the field of digital health care.
Innovation at UMB and UM-IHC
The greater Baltimore region is uniquely positioned to advance digital health care technologies. At UMB, innovation thrives through the dynamic interaction between physicians, researchers, and medical data. Many UMB faculty practice at the University of Maryland Medical System and see the needs, opportunities, and challenges that patients face. They can engage with UMB’s vibrant research environment to create solutions. UM-IHC also plays a pivotal role in this vibrant ecosystem with its mission to improve health using cutting-edge computer science and innovation.
UM-IHC aims to create a health computing supercluster that attracts industry partners and significantly improves health outcomes for all Marylanders. UM-IHC focuses on several key pillars, including bioinformatics, applied AI, immersive visualization, therapeutic target discovery, population and community health, real-world evidence, and adaptive clinical trials. By integrating multimodal patient data, UM-IHC seeks to develop precision medicine and enhance doctor-patient communication, offering unique opportunities for digital innovation in academic entrepreneurship.
Future of Digital Health
The future of digital health is wide open thanks to recent developments in generative AI, which holds immense potential for assisting in new tasks and creating unprecedented opportunities. Generative AI can seamlessly integrate into health care, benefiting both patients and providers in ways previously unimagined. This reemphasizes the demand for innovators to think creatively.
There are numerous scenarios that were pipe dreams a decade ago. For instance, AI can be used to create virtual environments for patients with mobility issues, allowing them to interact with the world in innovative ways. Moreover, the concept of synthetic reality, where AI-generated environments mimic real-life interactions, opens up possibilities for psychological health innovations. Patients could interact with virtual representations of trusted individuals or past relatives, providing comfort and support in a controlled environment. These new and unknown applications of generative AI offer exciting prospects for academic entrepreneurship in digital health care technologies, paving the way for groundbreaking advancements.
Conclusion
As we stand on the brink of a new era in health care, digital health innovation offers immense potential to transform the industry. Generative AI, in particular, holds the promise of creating new and unknown applications that can revolutionize patient care and medical practices. Academic innovators and researchers interested in entrepreneurship are encouraged to be part of this exciting journey, thinking creatively about the future of health care and the role of AI in improving patient outcomes.
By embracing digital health innovation, we can translate technology into better health outcomes, ensuring that the benefits of AI and machine learning reach every corner of the health care system. The future is bright, and the possibilities are endless for those willing to innovate and lead the way in digital health.