The aim of the project is to design intelligent systems to improve the diagnosis and prognosis of prevalent diseases in the aging population such as stroke and cardiovascular diseases, neurodegenerative diseases, sarcopenia, Parkinson’s disease, hypoacusia, and prostate and colorectal cancer. TMELab, as part of IIS Aragon, is involved in these last two work packages (WP), and its goal is to establish risk indicators of prostate and colorectal cancer from clinical data and medical images, both for improving early diagnosis and assisting physicians in their decisions.

For that purpose, available databases from the Aragon health system will be used, which can be incorporated into the BIGAN platform for clinical data management for research in our region. Data curation techniques will be used when necessary, as well as trained classifiers of different types depending on the nature of the available data, including supervised deep neural networks. Finally, the definition of the most probable risk indicators in each case, as well as the evaluation of the results and the comparison with those derived from the diagnoses made by specialists, will be carried out by clinical specialists of the IIS Aragon.

As a result of the WP developed in TME Lab, it is expected to have a series of databases as an initial reference, as corresponds to those mentioned above, as well as a series of tools, easily adaptable and retrainable for other databases, which will allow improving the screening or active surveillance systems that exist in different communities in our country for these two types of cancer, as well as improving the accuracy of the current screening and diagnostic tools, and advancing in the progressive replacement of biopsy as the gold standard for the diagnosis of prostate cancer by much less invasive resonance imaging.