Speaker "Marcio Aloisio Bezerra Cavalcanti Rockenbach" Details Back



Multimodal AI in Healthcare


Healthcare professionals make use of multiple sources of data. To arrive to a diagnosis and decide on patient management, they rely on a combination of several types and sources of data, such as imaging, time series, structured clinical data and non-structured data. Artificial Intelligence approaches combining multiple sources of data are becoming more common, but there are several challenges in developing and implementing these solutions in the real world. This talk will be based on this post I've written on this topic:
Who is this presentation for?
Physicians, data scientists, engineers, and product managers working in the field of healthcare AI.
Prerequisite knowledge:
Basic understanding of artificial intelligence and healthcare data.
What you'll learn?
The challenges in implementing artificial intelligence solutions combining multiple data sources in the healthcare setting.


Medical Doctor (MD) specialized in Radiology. Master of Science (MS) degree in Data Science applied to medical imaging. Currently a Product Manager at the Center for Clinical Data Science (CCDS), part of Mass General Brigham, in Boston, USA. In this role, I lead the development of a portfolio of commercial artificial intelligence (AI) projects applied to healthcare, working with physicians and researchers from Harvard Medical School.