Pie & AI is a series of DeepLearning.AI meetups independently hosted by community groups. This event is hosted by Godwin France, Learnira. Special thanks to their support!

Picture this: “A passionate AI Engineer sets out to leverage AI for the betterment of society. They see the medical and healthcare sector as a promising avenue for achieving remarkable improvements in human well-being. This dream is fueled by a strong vision of rapid and unfathomable business growth. The Prototype is developed… Now is the time to talk to the “users”...

Next, the Engineer meets the Healthcare Product Developer, the person who will help them to “check a couple of things”, to ensure the product’s usability and desirability. Suddenly, the Engineer is confronted by a stream of stringent medical validation standards, regulatory barriers, and business requirements. Then come the everyday realities of doctors and nurses, and the way they are used to their workflows… As the Engineer progresses, their motivation gradually gives way to frustration, overwhelm, even ruminative anxiety… How is it even possible to innovate in this environment?!

The lengthy and well-defined (one could say, a bit rigid) process of developing evidence-based healthcare products appears to directly clash with the agile and dynamic nature of software production life cycles, which are already mathematically proven approaches… The Engineer however has a dream! So they roll up their sleeves and get to work.

This is the beginning of the story of many AI Engineers who dabble for the first time into the world of healthcare. Who knows, knows. The story usually goes on to extensive scrutiny of the AI Engineer’s Prototype, including intense debates, defining processes, and concerted efforts from a diverse group of experts - engineers, medical professionals, product strategists, regulatory specialists, commercial experts… You name it.

Something curious appears to the AI Engineer during this process… They see how these “rigid” regulations and medical processes exist for valid reasons, and it appears the only path to production is teaming up. Things do not seem so confusing or innovation resistant anymore, and that medical expert, or healthcare product developer have turned from frenemies to necessary teammates. The development of AI tools for medical purposes is a process where medicine becomes a partner rather than merely a customer or user of technology.

Event Agenda & Speakers:

Agenda for Zoom Session: ""Deciphering Deep Learning: Is It Ready for Disease Diagnosis?""

Outline:

I. Introduction (6 minutes)

II. Case Study (10-12 mins)

III. Use Cases & RW Learnings in Diseases Diagnosis (15 min)

IV. What next - future potential for disease diagnosis

V. Ethical and Legal Implications - Considerations & Implications

V. Key takeaways for AI integration into healthcare products

VI. Audience Questions

VII. Conclusion, Closing Remarks

Participants are encouraged to engage in informal networking, share insights, and connect with speakers and fellow attendees.

Ghaith Sankari (https://www.linkedin.com/in/ghaith-sankari/)

Paula Sandrak (https://www.linkedin.com/in/paula-sandrak/)

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Beginner friendly.

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