{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,13]],"date-time":"2025-09-13T16:11:26Z","timestamp":1757779886499,"version":"3.30.1"},"reference-count":35,"publisher":"Tech Science Press","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.32604\/iasc.2023.029037","type":"journal-article","created":{"date-parts":[[2022,7,19]],"date-time":"2022-07-19T02:42:18Z","timestamp":1658198538000},"page":"1907-1921","source":"Crossref","is-referenced-by-count":3,"title":["Game Theory-Based Dynamic Weighted Ensemble for Retinal Disease Classification"],"prefix":"10.32604","volume":"35","author":[{"given":"Kanupriya","family":"Mittal","sequence":"first","affiliation":[]},{"given":"V.","family":"Mary Anita Rajam","sequence":"additional","affiliation":[]}],"member":"17807","reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"22389","DOI":"10.1007\/s11042-020-09041-y","article-title":"Computerized retinal image analysis-a survey","volume":"79","author":"Mittal","year":"2020","journal-title":"Multimedia Tools and Applications"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"69","DOI":"10.4103\/0301-4738.178150","article-title":"Diabetic retinopathy: An epidemic at home and around the world","volume":"64","author":"Raman","year":"2016","journal-title":"Indian Journal of Ophthalmology"},{"key":"ref3","unstructured":"National Eye Institute. \u201cAMD,\u201d 2020. [Online]. Available: https:\/\/www.nei.nih.gov\/learn-about-eye-health\/eye-conditions-and-diseases\/age-related-macular-degeneration."},{"key":"ref4","first-page":"44","article-title":"Retinal imaging modalities: Advantages and limitations for clinical practice","volume":"8","author":"Khaderi","year":"2011","journal-title":"Retinal Physician"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"1205","DOI":"10.1109\/2944.796348","article-title":"Optical coherence tomography (OCT): A review","volume":"5","author":"Schmitt","year":"1999","journal-title":"IEEE Journal of Selected Topics in Quantum Electronics"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"5862","DOI":"10.1167\/iovs.10-7075","article-title":"Automatic detection of diabetic retinopathy and age-related macular degeneration in digital fundus images","volume":"52","author":"Agurto","year":"2011","journal-title":"Investigative Ophthalmology & Visual Science"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.compbiomed.2016.04.015","article-title":"Automated screening system for retinal health using bi-dimensional empirical mode decomposition and integrated index","volume":"75","author":"Acharya","year":"2016","journal-title":"Computers in Biology and Medicine"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.compbiomed.2017.03.008","article-title":"Diagnosis of retinal health in digital fundus images using continuous wavelet transform (cwt) and entropies","volume":"84","author":"Koh","year":"2017","journal-title":"Computers in Biology and Medicine"},{"key":"ref9","first-page":"1379","article-title":"Automated detection of retinal health using phog and surf features extracted from fundus images","volume":"48","author":"Koh","year":"2018","journal-title":"Applied Intelligence"},{"key":"ref10","doi-asserted-by":"crossref","first-page":"1382","DOI":"10.1109\/TBME.2017.2752701","article-title":"An automated system for the detection and classification of retinal changes due to red lesions in longitudinal fundus images","volume":"65","author":"Adal","year":"2017","journal-title":"IEEE Transactions on Biomedical Engineering"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"4023","DOI":"10.1109\/TMI.2020.3008871","article-title":"Self-supervised feature learning via exploiting multi-modal data for retinal disease diagnosis","volume":"39","author":"Li","year":"2020","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"ref12","series-title":"COLINS","first-page":"715","article-title":"Bagging of convolutional neural networks for diagnostic of eye diseases","author":"Smaida","year":"2020"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.jbi.2015.12.001","article-title":"Intellihealth: A medical decision support application using a novel weighted multi-layer classifier ensemble framework","volume":"59","author":"Bashir","year":"2016","journal-title":"Journal of Biomedical Informatics"},{"key":"ref14","first-page":"251","article-title":"Ensemble kernel method: Svm classification based on game theory","volume":"27","author":"Liu","year":"2016","journal-title":"Journal of Systems Engineering and Electronics"},{"key":"ref15","series-title":"IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS)","first-page":"3563","article-title":"Game theory based data fusion for precision agriculture applications","author":"Bruce","year":"2016"},{"key":"ref16","series-title":"2021 Int. Conf. on Recent Advances in Mathematics and Informatics (ICRAMI)","first-page":"1","article-title":"Game theory-based ensemble of deep neural networks for large scale audio tagging","author":"Ykhlef","year":"2021"},{"key":"ref17","doi-asserted-by":"crossref","unstructured":"C. B. Zhang, P. T. Jiang, Q. Hou, Y. Wei, Q. Han et al., \u201cDelving deep into label smoothing,\u201d arXiv preprint arXiv:2011.12562, 2020.","DOI":"10.1109\/TIP.2021.3089942"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"4328","DOI":"10.1109\/JBHI.2021.3111415","article-title":"Choquet integral and coalition game-based ensemble of deep learning models for covid-19 screening from chest x-ray images","volume":"25","author":"Bhowal","year":"2021","journal-title":"IEEE Journal of Biomedical and Health Informatics"},{"key":"ref19","doi-asserted-by":"crossref","first-page":"101690","DOI":"10.1016\/j.artmed.2019.06.006","article-title":"Using game theory and decision decomposition to effectively discern and characterise bi-locus diseases","volume":"99","author":"Versbraegen","year":"2019","journal-title":"Artificial Intelligence in Medicine"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/JIOT.2021.3124073","article-title":"Game-based access for AoI-oriented data transmission under dynamic attack","author":"Yang","year":"2021","journal-title":"IEEE Internet of Things Journal"},{"key":"ref21","series-title":"Proc. of the First Conf. on Visualization in Biomedical Computing","first-page":"337","article-title":"Contrast-limited adaptive histogram equalization: Speed and effectiveness","author":"Pizer","year":"1990"},{"key":"ref22","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1007\/3-540-26808-1_23","author":"Rosca","year":"2005","journal-title":"Advances in Multiresolution for Geometric Modelling"},{"key":"ref23","series-title":"Int. Conf. on Advanced Informatics for Computing Research","first-page":"499","article-title":"Image processing by using different types of discrete wavelet transform","author":"Thakral","year":"2018"},{"key":"ref24","doi-asserted-by":"crossref","first-page":"908","DOI":"10.1049\/iet-ipr.2015.0150","article-title":"Combination of contrast limited adaptive histogram equalisation and discrete wavelet transform for image enhancement","volume":"9","author":"Lidong","year":"2015","journal-title":"IET Image Processing"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1007\/978-0-85729-748-8_2","author":"Pietikainen","year":"2011","journal-title":"Computer Vision Using Local Binary Patterns"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"45","DOI":"10.14203\/j.inkom.420","article-title":"Texture feature extraction by using local binary pattern","volume":"9","author":"Prakasa","year":"2016","journal-title":"INKOM Journal"},{"key":"ref27","series-title":"IEEE Computer Society Conf. on Computer Vision and Pattern Recognition (CVPR\u201905)","first-page":"886","article-title":"Histograms of oriented gradients for human detection","volume":"1","author":"Dalal","year":"2005"},{"key":"ref28","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1016\/j.ijar.2010.01.004","article-title":"Gaussian kernel based fuzzy rough sets: Model, uncertainty measures and applications","volume":"51","author":"Hu","year":"2010","journal-title":"International Journal of Approximate Reasoning"},{"key":"ref29","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1080\/03081079008935107","article-title":"Rough fuzzy sets and fuzzy rough sets","volume":"17","author":"Dubois","year":"1990","journal-title":"International Journal of General System"},{"key":"ref30","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1016\/j.ins.2009.09.008","article-title":"Attribute selection with fuzzy decision reducts","volume":"180","author":"Cornelis","year":"2010","journal-title":"Information Sciences"},{"key":"ref31","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.fss.2014.08.014","article-title":"A fuzzy rough set approach for incremental feature selection on hybrid information systems","volume":"258","author":"Zeng","year":"2015","journal-title":"Fuzzy Sets and Systems"},{"key":"ref32","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1613\/jair.953","article-title":"Smote: Synthetic minority over-sampling technique","volume":"16","author":"Chawla","year":"2002","journal-title":"Journal of Artificial Intelligence Research"},{"key":"ref33","series-title":"Proc. of the 22nd ACM Sigkdd Int. Conf. on Knowledge Discovery and Data Mining","first-page":"785","article-title":"Xgboost: A scalable tree boosting system","author":"Chen","year":"2016"},{"key":"ref34","doi-asserted-by":"crossref","first-page":"748","DOI":"10.1016\/j.jfranklin.2008.04.009","article-title":"Enhancement of blood vessels in digital fundus photographs via the application of multiscale line operators","volume":"345","author":"Farnell","year":"2008","journal-title":"Journal of the Franklin Institute"},{"key":"ref35","doi-asserted-by":"crossref","first-page":"101660","DOI":"10.1016\/j.media.2020.101660","article-title":"Automatic detection of rare pathologies in fundus photographs using few-shot learning","volume":"61","author":"Quellec","year":"2020","journal-title":"Medical Image Analysis"}],"container-title":["Intelligent Automation &amp; Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.techscience.com\/ueditor\/files\/iasc\/TSP_IASC-35-2\/TSP_IASC_29037\/TSP_IASC_29037.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T21:29:54Z","timestamp":1733520594000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/iasc\/v35n2\/48911"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":35,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023]]}},"URL":"https:\/\/doi.org\/10.32604\/iasc.2023.029037","relation":{},"ISSN":["1079-8587"],"issn-type":[{"type":"print","value":"1079-8587"}],"subject":[],"published":{"date-parts":[[2023]]}}}