Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Lung cancer prediction with advanced graph neural networks Subject The topic of the resource Graph attention network; Graph neural network; Lung cancer; Machine learning; Prediction Description An account of the resource This research aims to enhance lung cancer prediction using advanced machine learning techniques. The major finding is that integrating graph convolutional networks (GCNs) with graph attention networks (GATs) significantly improves predictive accuracy. The problem addressed is the need for early and accurate detection of lung cancer, leveraging a dataset from Kaggle's "Lung Cancer Prediction Dataset," which includes 309 instances and 16 attributes. The proposed A-GCN with GAT model is meticulously engineered with multiple layers and hidden units, optimized through hyperparameter adjustments, early stopping mechanisms, and Adam optimization techniques. Experimental results demonstrate the model's superior performance, achieving an accuracy of 0.9454, precision of 0.9213, recall of 0.9743, and an F1 score of 0.9482. These findings highlight the model's efficacy in capturing intricate patterns within patient data, facilitating early interventions and personalized treatment plans. This research underscores the potential of graph-based methodologies in medical research, particularly for lung cancer prediction, ultimately aiming to improve patient outcomes and survival rates through proactive healthcare interventions. 2025 Institute of Advanced Engineering and Science. All rights reserved. Creator An entity primarily responsible for making the resource Moozhippurath B.; Natarajan J. Source A related resource from which the described resource is derived Indonesian Journal of Electrical Engineering and Computer Science, Vol-37, No. 2, pp. 1077-1084. Publisher An entity responsible for making the resource available Institute of Advanced Engineering and Science Date A point or period of time associated with an event in the lifecycle of the resource 2025-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/ijeecs.v37.i2.pp1077-1084" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/ijeecs.v37.i2.pp1077-1084</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210744116&amp;doi=10.11591%2Fijeecs.v37.i2.pp1077-1084&amp;partnerID=40&amp;md5=93cece260be04be8e7b060a60039c23b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210744116&amp;doi=10.11591%2fijeecs.v37.i2.pp1077-1084&amp;partnerID=40&amp;md5=93cece260be04be8e7b060a60039c23b</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 25024752 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Moozhippurath B., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Kengeri Campus, Bangalore, India; Natarajan J., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Kengeri Campus, Bangalore, India