Artificial intelligence is becoming increasingly critical to develop innovative, competitive, and differentiated medical businesses and products. However, each such project bears the risk of costly failures, due to lack of proper vision, guidance, and data strategy. Furthermore, deployed AI solutions always contain a degree of human and societal biases that may influence the results and have costly consequences for organisations beyond the project itself.
In this meetup, delivered by three AI and data scientists with strong backgrounds, we will explore how to identify the feasibility requirements in building successful AI projects, from identifying problems where AI can readily add value, to getting the right team and resources for your projects. We will take some sample use cases, one being a skin cancer detection project, to demonstrate various details to pay attention in preparation to successful AI projects. We will show how to leverage human-centric design to mitigate risks in AI projects in digital medicine.
11:40 am - 11:50 am Arrival and socializing
11:50 am - 12:00 pm Opening
12:00 pm - 1:50 pm Onur Yürüten, Pawel Rosikiewicz and Oksana Riba Grognuz, "Assessing readiness for AI projects: Case study with a Skin Cancer Detection Sys"
1:50 pm - 2:00 pm Q&A
Please register here.
Webinar ID: 864 4081 9063
Website: Click to Visit
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