Artificial intelligence methods for biomedical imaging and omics data
Contributo in Atti di convegno
Data di Pubblicazione:
2023
Abstract:
The use of deep learning in biomedical imaging and omics data has shown great potential for enhancing medical diagnosis and improving patient outcomes. In this paper, we present the deep learning and machine learning research activities of two research laboratories: EIDOS and qBio. Our research encompasses a broad range of topics, including digital pathology, integration of omics data, digital radiology, computational epidemiology and neuroimaging. We collaborate with several hospitals for the collection of relevant datasets and with international research centers and foreign universities to develop state-of-the-art techniques. Overall, we believe that the activities of these laboratories in deep and machine learning have the potential to improve the way we diagnose and treat various medical conditions.
Tipologia CRIS:
04A-Conference paper in volume
Keywords:
Biomedical imaging; computational epidemiology; deep learning; histopathology; integration of omics data; machine learning; neuroimaging; radiology
Elenco autori:
Barbano C.A.; Beccuti M.; Cordero F.; Ivanov D.N.; Licheri N.; Pernice S.; Presta A.; Renzulli R.; Grangetto M.
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Titolo del libro:
CEUR Workshop Proceedings
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