| Literature DB >> 32586255 |
Farzad Heydari1, Marjan Kuchaki Rafsanjani1.
Abstract
Due to the serious consequences of lung cancer, medical associations use computer-aided diagnostic procedures to diagnose this disease more accurately. Despite the damaging effects of lung cancer on the body, the lifetime of cancer patients can be extended by early diagnosis. Data mining techniques are practical in diagnosing lung cancer in its first stages. This paper surveys a number of leading data mining-based cancer diagnosis approaches. Moreover, this review draws a comparison between data mining approaches in terms of selection criteria and presents the advantages and disadvantages of each method. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.Entities:
Keywords: Lung cancer; MRI; data mining algorithms; detection accuracy; dignosis; machine learning
Year: 2021 PMID: 32586255 DOI: 10.2174/1573405616666200625153017
Source DB: PubMed Journal: Curr Med Imaging