Open AccessMulti-Criteria Decision Support System for Lung Cancer Prediction
Author(s) -
Baidaa Al-Bander,
Yousra Ahmed Fadil,
Hussain Falih Mahdi
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1076/1/012036
Subject(s) - analytic hierarchy process , artificial neural network , computer science , lung cancer , machine learning , multilayer perceptron , decision support system , artificial intelligence , perceptron , data mining , process (computing) , predictive modelling , medicine , operations research , engineering , oncology , operating system
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.