Creating an international healthcare AI development and education network: HAIDEN

HI, I'm HAIDEN, your personal guide to the Healthcare Artificial Intelligence Development and Education Network.

Creating the dissemination and implementation of artificial intelligence applications at scale has many barriers.

Artificial intelligence (AI) holds indisputable potential in solving global challenges faced in healthcare provision, resulting in its ever-increasing utilization in various medical fields. This review aims to present a thorough evaluation of the advantages, challenges, and leading strategies for utilizing AI in the field of medical education.

I am here to help you engage with the international network of medical educators, administrators, students, patients, communities and stakeholders who are integrating data literacy, data dexterity and artificial intelligence into medical professional schools around the world and improving patient AI awareness and education.

Just getting started? Here's an example:

Teaching AI to healthcare professionals involves several challenges, including:

1. Complexity of AI Systems: AI in healthcare can be highly complex, involving intricate algorithms and vast amounts of data. Educators need to simplify these concepts without losing essential details, which can be difficult.
2. Integration with Existing Knowledge: Healthcare professionals already have a substantial body of knowledge and clinical experience. Integrating AI into this existing framework can be challenging, particularly if it requires significant changes in how they practice or think about their work.
3. Data Privacy and Security: AI systems often rely on large datasets, including sensitive patient information. Ensuring that these systems adhere to strict privacy and security standards is crucial, and healthcare professionals must be trained on these aspects.
4. Lack of Standardization: There is a lack of standardized AI tools and practices across the healthcare field. This makes it difficult to provide consistent training and to ensure that the AI systems being used are up-to-date and effective.
5. Resistance to Change: Some healthcare professionals might be resistant to adopting AI due to concerns about job displacement, skepticism about the technology’s accuracy, or a general reluctance to change established practices.
6. Training and Resources: There is often a lack of tailored training programs and resources that cater specifically to healthcare professionals. Developing and providing these resources can be resource-intensive.
7. Interdisciplinary Knowledge: Effective use of AI in healthcare often requires an understanding of both medical knowledge and technical aspects of AI. This interdisciplinary knowledge can be challenging to impart in a way that is both comprehensive and practical.
8. Ethical and Legal Concerns: AI in healthcare raises various ethical and legal issues, such as informed consent, accountability for errors, and bias in algorithms. Training must address these concerns and ensure that healthcare professionals understand the implications of AI use.
9. Keeping Up with Rapid Advancements: AI technology evolves rapidly, and staying current with the latest developments can be challenging. Continuous education and professional development are required to keep healthcare professionals updated.
10. Practical Implementation: Training needs to go beyond theory and include practical, hands-on experience with AI tools. Ensuring that professionals have opportunities to work with these tools in a clinical setting is essential but can be logistically challenging.

Addressing these barriers requires a concerted effort from educational institutions, healthcare organizations, and technology developers to create effective and practical training programs.

Using AI to help you use AI to teach and create educational, training, and development content, our proprietary learning platform will guide you through your journey upskilling your students and workforce to practice responsible AI by practicing and demonstrating evidence-based competencies.

We are not just another AI bot, but an international AI education ecosystem designed to:

1. Exchange initiatives
2. Compare lessons learned
3. Network
4. Share resources
5. Meet both online and in real time during regional conferences
6. Connect to patient communities and their caregiver teams
7. Work with others to practice AIntrepreneurship
8. Collaborate and communicate on social media sites
9. Find a job as a healthcare AI educator
10. Develop your edupreneurial knowledge, skills, attitudes and competencies

Thanks for joining www.AIDEN.ai (the domain is still available). Always ad-free...until it's not.

In the meantime, here is something to get you connected.

Our Slack channel is https://join.slack.com/t/haidenhealthc-dq46658/shared_invite/zt-2pn5w8r6s-04QWGPg2IWKhYiGQoDa3Ew

Welcome to your guide to creating the future of healthcare AI education, training, and development.

Arlen Meyers, MD, MBA is the President and CEO of the Society of Physician Entrepreneurs on Substack and at MI10