Skip to main content

Research Repository

Advanced Search

Multi-Criteria Decision Support System for Lung Cancer Prediction

Al-Bander, B; Fadil, YA; Mahdi, H

Multi-Criteria Decision Support System for Lung Cancer Prediction Thumbnail


YA Fadil

H Mahdi


<jats:title>Abstract</jats:title> <jats:p>Lung cancer is one of the most common deadly malignant tumours, with the most rapid morbidity and death worldwide. Cancer risk prediction is a challenging and complex task in the field of healthcare. Many studies have been carried out by researchers to analyse and establish lung cancer symptoms and factors. However, further improvements are vital and required to be conducted in order to overcome the persistent challenges. In this study, a multi-criteria decision support system for lung cancer risk prediction based on a web-based survey data has been presented and realised. The proposed framework aims to incorporate the powerful of analytical hierarchy process (AHP) with artificial neural network for constituting lung cancer prediction model. The multiple criteria decision-making strategy (AHP) assigns a weight to each individual cancer symptom feature from survey data. The weighted features are then used to train multi-layer perceptron artificial neural network (ANN) to build a disease prediction model. Experimental analysis and evaluation performed on 276 subjects revealed promising prediction performance of developed lung cancer prediction framework in terms of various classification metrics.</jats:p>

Conference Name 2nd International Scientific Conference of Engineering Sciences (ISCES 2020)
Conference Location Diyala, Iraq
Start Date Dec 16, 2020
End Date Dec 17, 2020
Acceptance Date Feb 1, 2021
Publication Date Feb 1, 2021
Publisher IOP Publishing
Volume 1076
Pages 012036 - 012036
Publisher URL


You might also like

Downloadable Citations