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http://hdl.handle.net/20.500.12188/24498
Наслов: | Deep learning in systems medicine | Authors: | Wang, Haiying Pujos-Guillot, Estelle Comte, Blandine de Miranda, Joao Luis Spiwok, Vojtech Chorbev, Ivan Castiglione, Filippo Tieri, Paolo Watterson, Steven McAllister, Roisin de Melo Malaquias, Tiago Zanin, Massimiliano Singh Rai, Taranjit Zheng, Huiru |
Keywords: | deep learning (DL); systems medicine (SM); data integration; biomarker discovery; disease classification | Issue Date: | мар-2021 | Publisher: | Oxford University Press | Journal: | Briefings in Bioinformatics | Abstract: | Systems medicine (SM) has emerged as a powerful tool for studying the human body at the systems level with the aim of improving our understanding, prevention and treatment of complex diseases. Being able to automatically extract relevant features needed for a given task from high-dimensional, heterogeneous data, deep learning (DL) holds great promise in this endeavour. This review paper addresses the main developments of DL algorithms and a set of general topics where DL is decisive, namely, within the SM landscape. It discusses how DL can be applied to SM with an emphasis on the applications to predictive, preventive and precision medicine. Several key challenges have been highlighted including delivering clinical impact and improving interpretability. We used some prototypical examples to highlight the relevance and significance of the adoption of DL in SM, one of them is involving the creation of a model for personalized Parkinson’s disease. The review offers valuable insights and informs the research in DL and SM. | URI: | http://hdl.handle.net/20.500.12188/24498 |
Appears in Collections: | Faculty of Computer Science and Engineering: Journal Articles |
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