A5.3.2 Neoplasms and lung cancer

End-to-end Artificial Intelligence platform for decision-making support in the context of histopathological analysis, with collaborative and progressive annotation functionalities (supported by Artificial Intelligence), importing data from different laboratory/hospital sources. The aim is to consolidate the development of a set of methodologies based on digital image processing and deep learning, in possible collaboration with other more statistically-based analysis techniques (e.g. clustering, anomaly detection, etc.) to optimize annotations in terms of effectiveness and efficiency, from the annotator's point of view, mixed with active learning strategies (human-in-the-loop) for strong consolidation - in other words, using the unanimous classification of a highly qualified group of health professionals. Recent AutoML approaches for the characterization of abnormal tissue will also be tested

Date Start

Nov. 2, 2021

Date End

Jan. 31, 2025