Prediction of pneumoconiosis risks in coal workers using an artificial neural network

Aim: This study aims to create a model that can predict the risk of pneumoconiosis in coal workers by using an artificial neural network. Materials and Methods: An artificial neural network-based model has been developed using the health data of the workers working in the Turkish Hard Coal Enterprises. The network model has a 7-33-2 architecture. Input neurons include age, the year they started employment, occupational category, the number of days worked Keyword: Kömür = Coal ; Kömür işletmeleri = Coal enterprises ; Kömür madenciliği = Coal mining ; Madenci = Miner ; Pnömokonyoz = Pneumoconiosis ; Risk faktörleri = Risk factors ; Sinir ağları = Nerve net ; Yapay sinir ağları = Artificial neural networks