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The PIEnsemble primarily combines three deep learning techniques, ResNet Model, GoogleNet Model, and Inception Model, integrated with two dimensionality reduction techniques, PCA and ICA, which are used for feature extraction with a combination of Linear, Batch1Norm1D, and ReLU layers. Simulations in a series\u00a0on two benchmarks datasets were run to show the improved effectiveness of the PIEnsemble model. The experimental results highlighted the improvements to the PIEnsemble classifier structure, which has the highest classification accuracy ratio and superior performance to other methods, with a 98.25% accuracy for Dataset 1 and a 98.75% accuracy for Dataset\u00a02. <\/jats:p>","DOI":"10.1142\/s1793005725500115","type":"journal-article","created":{"date-parts":[[2023,12,18]],"date-time":"2023-12-18T07:06:47Z","timestamp":1702883207000},"page":"195-211","source":"Crossref","is-referenced-by-count":0,"title":["A Novel Ensemble Model for Brain Tumor Diagnosis"],"prefix":"10.1142","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9413-3079","authenticated-orcid":false,"given":"Amira Samy","family":"Talaat","sequence":"first","affiliation":[{"name":"Computers and Systems Department, Electronics Research Institute, Cairo 12622, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2024,1,23]]},"reference":[{"volume-title":"The Leading Cause of Death Due to Brain Tumors in the United States","year":"2022","author":"Scott T.","key":"S1793005725500115BIB001"},{"key":"S1793005725500115BIB002","doi-asserted-by":"publisher","DOI":"10.13005\/bpj\/1511"},{"key":"S1793005725500115BIB003","doi-asserted-by":"publisher","DOI":"10.1109\/iCareTech49914.2020.00032"},{"key":"S1793005725500115BIB004","doi-asserted-by":"publisher","DOI":"10.1007\/s11063-020-10398-2"},{"key":"S1793005725500115BIB005","doi-asserted-by":"publisher","DOI":"10.1613\/jair.614"},{"key":"S1793005725500115BIB006","doi-asserted-by":"publisher","DOI":"10.1109\/MCAS.2006.1688199"},{"key":"S1793005725500115BIB007","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-009-9124-7"},{"key":"S1793005725500115BIB008","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"S1793005725500115BIB010","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"S1793005725500115BIB011","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2019.103345"},{"key":"S1793005725500115BIB012","doi-asserted-by":"publisher","DOI":"10.1016\/j.jocs.2018.12.003"},{"key":"S1793005725500115BIB013","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2892455"},{"key":"S1793005725500115BIB014","doi-asserted-by":"publisher","DOI":"10.1016\/j.bbe.2018.10.004"},{"key":"S1793005725500115BIB015","doi-asserted-by":"publisher","DOI":"10.3390\/s19091992"},{"key":"S1793005725500115BIB016","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2019.05.001"},{"key":"S1793005725500115BIB017","doi-asserted-by":"publisher","DOI":"10.1080\/08839514.2022.2031824"},{"key":"S1793005725500115BIB018","doi-asserted-by":"publisher","DOI":"10.3390\/axioms11010034"},{"key":"S1793005725500115BIB019","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"S1793005725500115BIB020","doi-asserted-by":"publisher","DOI":"10.1016\/j.mehy.2019.109433"},{"key":"S1793005725500115BIB021","doi-asserted-by":"publisher","DOI":"10.3390\/app10061999"},{"key":"S1793005725500115BIB022","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-020-00347-9"},{"volume-title":"Healthcare","year":"2021","author":"D\u00edaz-Pernas F. 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