An exhaustive study on the lung cancer risk models Online publication date: Mon, 13-Jul-2020
by Malayil Shanid; A. Anitha
International Journal of Bioinformatics Research and Applications (IJBRA), Vol. 16, No. 2, 2020
Abstract: One of the critical cancers leading to an upsurging rate of mortality is lung cancer. The Computed Tomography (CT) is the vastly adopted technique for effective cancer detection and risk assessment. The mortality rate and the intrusive surgery can be reduced through the risk assessment of cancer at the earlier stages. Hence, an essential lung cancer detection technique must be modelled for the risk assessment of cancer at the earlier stages. This review paper is made by carrying out a detailed survey on 40 research works presenting the existing lung cancer detection methodologies. Also extensive analysis and discussion is made with respect to the publication year, adopted detection schemes, evaluation metrics, utilised datasets, a simulation tool, accuracy range, and the extracted features. Subsequently, the research gaps and issues of the distinct lung cancer detection schemes are elucidated for directing the researchers to a better contribution of effective cancer risk assessment.
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