TAMI

The aim of the project TAMI is to create a new platform for commercial, scientific and academic use that will provide "consumers" access to results and explanations of registered diagnostic orders, filtered data sets access for investigators or scientists and a knowledge base for academic purposes. In order to achieve such objective, the project will be based on the following specific objectives involving the development of research in the following areas: a) quantitative methods to objectively assess and compare different explanations of the automatic decisions; b) methods to generate better explanations, providing variety in the explanations, adapting the explanations to who will consume them and explaining multimodal decisions; c) novel visualization solutions for interpretations of decisions based on imagiological data. In order to accomplish that, TAMI will use clinical data, from structured to image data, in order to design and validate interpretable machine learning models. During the project, different multimodal settings will be tested to enable a better understanding of the AI-based decisions. Moreover, the algorithms will be designed to generate self-explanatory AIbased decisions, minimise bias, and act ethically in their context. Proof-of-concepts and demonstrators of how to integrate the researched explainable AI into workflows of cervical cancer treatment, pathology detection in chest X-Ray images in a screening environment, and glaucoma detection in retinal fundus images will be developed to validate the algorithmic solutions.