Candidate Identification Technique for Lung Cancer

Sadaf Batool Naqvi and Abad Ali Shah
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Sadaf Batool Naqvi: Johns Hopkins Aramco, Saudi Arabia
Abad Ali Shah: UET, USA

International Journal of Reliable and Quality E-Healthcare (IJRQEH), 2021, vol. 10, issue 1, 1-13

Abstract: Intensive research work has been done related to lung cancer prognosis. However, the current research mainly emphasises on decreasing the mortality rate, and increasing the survival rate of lung cancer patients. In this paper, the authors argue that an early identification and candidate identification (CI) of this disease can change the early detection treatment of lung cancer and hence can markedly reduce the mortality rate. The proposed technique CI will recognize the disease well in advance and can potentially save the candidate's life. In other words, a candidate of lung cancer is identified and treated in Stage 0 (explained later) instead of in Stage 1 or in the later stages of the lung cancer. In this paper, the authors have introduced a technique, called candidate identification, to identify candidates of the lung cancer. In the proposed technique, a backward forecasting function (BFF) is also proposed to generate Stage 0 data of the patients who have already lung cancer.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jrqeh0:v:10:y:2021:i:1:p:1-13

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