At WoundReference, our commitment to advancing innovation in wound care remains at the forefront of everything we do. Our recent collaboration with the Association for the Advancement of Wound Care (AAWC) highlights our mission to enhance clinical decision-making through cutting-edge technology.

On November 20th, 2024, Elaine Horibe Song MD PhD MBA, Wound Reference Inc CEO and Co-Founder, had the honor of presenting an innovative webinar, “The Promise and Responsibility of AI in Wound Care", hosted by AAWC.

This session explored the transformative potential of artificial intelligence in healthcare, its current applications, and the critical importance of ethical and responsible adoption.

Below is an outline and key points shared during the webinar. For more information, sign up to receive a copy of our complimentary ebook “Artificial Intelligence in Wound Care: Current Applications, Best Practices, and Perspectives” as soon as it’s available.

• Origins of Artificial Intelligence (AI)
• 3 Epochs of AI in Healthcare
• Current AI Applications in Wound Care
• 3.0 AI in Wound Care - Our Journey
• Responsibility in AI Use
• Best Practices for Clinicians Using AI in Wound Care
• Future Perspectives

Leveraging Artificial Intelligence in Wound Care

The term "Artificial Intelligence" was coined by John McCarthy in 1955, a computer science professor at Stanford University. AI in healthcare can be categorized into three key epochs:

• AI 1.0 – Symbolic and Probabilistic Models: These early systems relied on strict rules and logic for problem-solving. Examples include rule-based clinical decision support tools.
• AI 2.0 – Machine Learning and Deep Learning Models: Data-driven models capable of classification, prediction, and pattern recognition. Examples include identification and classification of venous leg ulcers and diabetic foot ulcers
• AI 3.0 – Generative AI: These models can handle many tasks without needing to be retrained for each task. They’re flexible and very powerful, but they also come with new risks, such as hallucinations (i.e. inaccurate or made-up information). Examples include PubmedGPT.  Techniques to mitigate hallucinations and clinical judgement are imperative for integration in clinical practice. 

Applications of Artificial Intelligence in Wound Care Today

Real-world applications of AI are already transforming wound care, improving diagnostic precision, accelerating healing processes, and reducing clinician workload - all while enhancing patient care. Key applications can be categorized into 3 segments of wound care:

• Wound Diagnosis: AI-based tools may be used to help identify, classify and measure wounds, such as venous ulcers and diabetic foot ulcers.
• Wound Prognosis: Machine learning models may be used to help predict wound healing outcomes and assess risks, such as delayed healing or complications.
• Wound Management: Emerging technologies, like AI-driven bandages and sensors, are being developed to provide real-time monitoring and updates

The webinar covered specific examples and publications of AI-based applications in each of the areas above. 

MY wAI - Wound AI: A Responsible Innovation for Clinicians

The webinar introduced WoundReference’s MY wAI - Wound AI, a responsible AI-powered solution specifically designed to enhance clinical decision-making. The tool empowers clinicians by delivering accurate, vetted information at the point of care, aiming to reduce the cognitive burden and accelerate decision-making.

MY wAI is not intended to replace human judgment but to work alongside it. By using advanced generative AI models and applying safeguards to minimize inaccuracies, the tool aims to quickly deliver reliable, evidence-based answers drawn from WoundReference’s peer-reviewed and regularly updated knowledge base.

This integration of technology and evidence-based practice reflects a commitment to maintaining high standards in patient safety and clinical reliability while supporting clinicians in their daily work.

Key Features of MY wAI - Wound AI:

• Access to a growing Prompt Library for frequent wound care inquiries.
• The ability to search any term and receive immediate, referenced, evidence-based answers from a trusted knowledge base, enabling faster and more informed decision-making
• Seamless integration with workflows to support complex care scenarios, such as venous ulcer treatment and hyperbaric oxygen therapy planning

The Responsibility of AI in Wound Care

While the potential of AI is promising, responsible technology assessment and implementation is crucial. Key considerations discussed in the webinar include:

• Data Collection and Accessibility
• Algorithm Training and Diversity
• Ethical and Legal Concerns
• Data Privacy and Security
• Equitable Access and Cost

The integration of AI into wound care is promising, but it requires a balanced approach. Staying open to the advancements AI can bring, while proactively addressing challenges, is critical to ensuring the safe and effective use of these technologies.

Partnering with AAWC: A Shared Vision for Innovation

This webinar showcased WoundReference’s leadership in responsible AI integration for wound care. This collaboration reflects a shared commitment to advancing the field through innovation and education. We thank AAWC for providing an opportunity for meaningful discussions on how AI can potentially be used to elevate care quality, making it impactful and accessible for wound care professionals worldwide.

Stay Informed

Missed the webinar? No problem! Our upcoming eBook, "Artificial Intelligence in Wound Care: Current Applications, Best Practices, and Perspectives", will cover all the topics discussed and more. Sign up with your email to get your complimentary copy as soon as it’s released!

In the meantime, contact us to learn more about MY wAI - Wound AI

Together, we can improve clinical outcomes more efficiently - one intelligent solution at a time.

References

• Ganesan O, Morris MX, Guo L, Orgill D. A review of artificial intelligence in wound care. Artif Intell Surg. 2024 Nov 4;4(4):364–75.
• Rippon MG, Fleming L, Chen T, Rogers AA, Ousey K. Artificial intelligence in wound care: diagnosis, assessment and treatment of hard-to-heal wounds: a narrative review. J Wound Care. 2024 Apr 2;33(4):229–42.
• WHO. Ethics and governance of artificial intelligence for health: WHO guidance. 2021