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https://scidar.kg.ac.rs/handle/123456789/16275
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DC Field | Value | Language |
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dc.contributor.author | Filipovic, Nenad | - |
dc.contributor.author | Sustersic, Tijana | - |
dc.contributor.author | Vulović, Aleksandra | - |
dc.contributor.author | Tsuda A. | - |
dc.date.accessioned | 2023-02-08T16:52:03Z | - |
dc.date.available | 2023-02-08T16:52:03Z | - |
dc.date.issued | 2019 | - |
dc.identifier.issn | - | - |
dc.identifier.uri | https://scidar.kg.ac.rs/handle/123456789/16275 | - |
dc.description.abstract | This review paper gives state-of-the-art in the field of lung cancer modelling. Due to the increasing amount of data available, research in lung cancer comes into the era of Big Data. New algorithms and methods are developed and coupled with machine learning techniques in order to improve the prediction of lung cancer development, determine the adequate therapy and increase the patient survival. We first give the overview of the current situation in the field of lung cancer, then investigate the role of ‘omics’ data in prevention and treatment of lung cancer, only to reach the explanations of the new available methods in lung cancer research—computational modelling and machine learning methods. | - |
dc.rights | info:eu-repo/semantics/openAccess | - |
dc.source | Shanghai Chest | - |
dc.title | Big Data and machine learning: new frontier in lung cancer care | - |
dc.type | review | - |
dc.identifier.doi | 10.21037/shc.2019.07.11 | - |
dc.identifier.scopus | 2-s2.0-85122683638 | - |
Appears in Collections: | Faculty of Engineering, Kragujevac |
Files in This Item:
File | Description | Size | Format | |
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5310-PB21-7242-R3.pdf | 844.43 kB | Adobe PDF | View/Open |
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