I could not have been prouder to present at the Southern Thoracic Surgical Association annual meeting in Orlando. I last attended this meeting 45 years ago (!) with my father, who was a member for decades along with my father-in-law, as was their mentor Dr. Robert Ellison a former president of STSA. Over 17 years I have given nearly 1000 presentations, but this one was special. Thank you to all at STSA.
Ron Galloway is a researcher who concentrates on disruptive trends and technologies, with a particular focus on the impact of artificial intelligence across industries and society.
Over the last 17 years, he has spoken at hundreds of conferences, board retreats, and corporate events. He is the author of 4 books, and the director of 3 films.
He is a graduate of Georgia Tech, and began coding AI in Turbo Prolog (in DOS) in 1988. You read that right, 35 years ago. Time flies.
HealthTech: Clear & To The Point
Ron’s 25 module set of on-demand educational videos on complex tech topics relevant to healthcare professionals and hospital trustees.
(You may need to click the sound button on the bottom right to hear the video)
This is a preview of segment 18 of the 25-video set of "HealthTech: Clear & To The Point." Each is around 20 minutes in length, which has been shown to be an effective length to hold attention and promote learning. I adhered to Richard Mayer's 12 Principles of Multimedia Education, as well as the Assertion/Evidence method from Penn State. In essence, I tried to combined clear writing with interesting relevant visuals, and no other distractions.
The New Book
"AI: Clear And To The Point" offers readers a focused exploration of artificial intelligence. Conveying complex concepts in an accessible manner, Galloway traces its origins from its nascent stages to its current transformative impact on various aspects of our lives.
"AI: Clear And To The Point" serves as a resource for anyone seeking to comprehend the intricate interplay between technology, society, and the promise that AI holds.
How are AI and ML changing healthcare? In every way, and in a lot of ways we have not imagined yet. "Data To Diagnosis," delves into the transformative impact of AI and machine learning on healthcare.
The book not only looks back on the strides made by AI in healthcare but also looks ahead, examining potential future scenarios and the ethical considerations associated with integrating technology into medical practices. "Data To Diagnosis" serves as an insightful resource for medical professionals seeking to understand and leverage AI's potential in their field, while also providing an accessible entry point for readers interested in the evolving relationship between technology and healthcare.
What Is Generative AI & How Will It Affect Healthcare?
In this session you will learn how generative AI represents a seismic shift in healthcare capabilities, moving from reactive to proactive through its ability to create new data. Unlike algorithmic AI that analyzes existing information, generative models can simulate unlimited scenarios - envisioning disease progressions, treatment responses, and novel therapies.
This predictive prowess amplifies accuracy in diagnosis and personalized medicine. By modeling disease and patient variability beyond textbook examples, generative AI arms physicians with perspective to tailor optimal interventions. Its versatility also accelerates drug development, rapidly assessing molecular designs and delivery mechanisms to unlock revolutionary therapies faster than ever before. Ultimately, generative AI signifies a future of medicine where we probe possibilities rather than just problems - where we peer into what could be rather than what already exists.
- Generative AI creates new data, while algorithmic AI analyzes existing data
- It can simulate disease progression and treatment response scenarios
- Enhances diagnosis and personalized medicine through modeling variability
- Accelerates drug development by rapidly prototyping molecular designs
- Represents a shift towards proactive, predictive medicine rather than reactive
Hospitals As Data Institutions
In this session you will learn how hospitals are undergoing a metamorphosis from caregivers to data curators. Electronic records, wearables, AI systems - exponential data streams are transforming hospitals into hubs of analytics, predicting diseases, guiding treatments, and optimizing operations.
This data-centric shift brings immense potential - from predictive population health to personalized care plans informed by analytics. But with great power comes great responsibility - robust data governance is imperative. As hospital databases balloon, ethical frameworks must advance in tandem to earn patient trust and enable sustainable innovation. Ultimately, data-centric hospitals promise more agile, effective care but require updated mindsets - seeing patients as both people and patterns, balancing intuition with intelligence. Data defines medicine’s future but wisdom must govern its course.
5 key takeaways:
- Hospitals are becoming data institutions due to growing data volume
- Enables predictive, preventive, personalized care through analytics
- Improves clinical outcomes and operational efficiency
- Requires strong data governance frameworks to build patient trust
- Signals a paradigm shift - care decisions based on both data and judgement
AI & The Future Of Nursing
In this session you will learn how AI is transforming nursing practice - from clinical decision tools to automated monitoring, AI promises to enhance care and efficiency. But it also warrants updated training so nurses can evaluate AI appropriately and uphold ethical standards regarding privacy and transparency.
Fundamentally, AI should serve as an assistive force, not a replacement, for human-centered care. The therapeutic nurse-patient bond depends on compassion, trust, critical thinking - irreplicable human qualities. By considering AI a collaborative partner rather than just a technological innovation, nurses can integrate its analytical powers while retaining the essence of their vital profession.
5 key takeaways:
- AI set to improve predictive analytics, diagnostics and streamline workflows
- Innovations in smart devices and robots assisting with patient care
- Need updated training in AI competencies and ethical frameworks
- Importance of consent, privacy and oversight regarding AI systems
- AI should augment rather than replace compassion and critical thinking in nursing
AI & The Patient Experience
In this session you will learn how AI and big data analytics are transforming hospital experiences - optimizing workflows while providing personalized care from registration to discharge. Chatbots, predictive models, and insights from integrated records allow hospitals to tailor interactions around patient needs.
The future promises even smarter facilities that can anticipate patient requirements and deploy targeted resources proactively. Virtual care will also grow more advanced using these technologies. However, progress requires planning around ethical AI use and health equity. If executed responsibly, data-driven personalization can make hospitals more agile while keeping patients at the center. By continuously innovating, hospitals can leverage AI to not only treat health issues but provide wholesome healing.
5 key takeaways:
- AI and big data enable personalized patient interactions
- Technologies optimize hospital workflows and resource planning
- The future holds smarter hospitals anticipating and addressing needs proactively
- Virtual care set to become more responsive and customized
- Responsible innovation key to providing optimal care through personalization