This is the fourth blog, in a series of five, discussing the results of the Ethical AI workshop at MPNE Consensus Data 2024.
Continuing from the previous blog (Ethical AI – Perspectives from Patient Advocates: Ethics and Emerging Technology – Group 2 (Part 1)), this blog focuses on the remaining results from Group 2. These results include discussions on explainability, trust and transparency.
This blog is part one of the third, in a series of five, discussing the results of the Ethical AI workshop at MPNE Consensus Data 2024.
Polarized light has wide spread advantges in-vivo skin imaging and is used to various ends. In the case of pre cancer diagnostics, polarized light has been rightly able to distinguish between benign nevi, melanocytic nevus, melanoma, and normal skin. Here we present a general overview of non-contact polarimetry that relies on certain parameters, as it is relevant to the iToBoS project.
MediaPipe is a set of open-source machine learning libraries created by Google that allow easy access to many models including object detection, image classification, image segmentation, and face detection.
Trilateral Research previously blogged about a workshop the team hosted on Ethical AI at MPNE Consensus Data 2024 for the iToBoS project.
iToBoS project has been selected to participate in the EU Innovation Radar.
The process of data acquisition involves capturing dermoscopic images using the High-definition Imaging Module (HDIM).
Every May 23, society comes together on World Melanoma Day, a date that seeks to raise awareness and promote concrete actions to combat this disease.
The use of 8 dermoscopic modules allowed to explore the scanning of the full-patient body, acquired with the highest resolution requiring a short acquisition time.