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Early identification of breast cancer lowers death rates. However, it is difficult to determine whether these are cancerous or noncancerous lesions due to their inconsistencies in image appearance. Machine learning techniques are widely employed in imaging analysis as a diagnostic method for breast cancer classification. However, patients cannot take advantage of remote areas as these systems are unavailable on clouds. Thus, breast cancer detection for remote patients is indispensable, which can only be possible through cloud computing. The user is allowed to feed images into the cloud system, which is further investigated through the computer aided diagnosis (CAD) system. Such systems could also be used to track patients, older adults, especially with disabilities, particularly in remote areas of developing countries that do not have medical facilities and paramedic staff. In the proposed CAD system, a fusion of AlexNet architecture and GLCM (gray-level cooccurrence matrix) features are used to extract distinguishable texture features from breast tissues. Finally, to attain higher precision, an ensemble of MK-SVM is used. For testing purposes, the proposed model is applied to the MIAS dataset, a commonly used breast image database, and achieved 96.26% accuracy.<\/jats:p>","DOI":"10.1155\/2022\/7403302","type":"journal-article","created":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T03:20:47Z","timestamp":1662002447000},"page":"1-9","source":"Crossref","is-referenced-by-count":17,"title":["Cloud Computing-Based Framework for Breast Tumor Image Classification Using Fusion of AlexNet and GLCM Texture Features with Ensemble Multi-Kernel Support Vector Machine (MK-SVM)"],"prefix":"10.1155","volume":"2022","author":[{"given":"Jaber","family":"Alyami","sequence":"first","affiliation":[{"name":"Department of Diagnostic Radiology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia"},{"name":"Smart Medical Imaging Research Group, King Abdulaziz University, Jeddah 21589, Saudi Arabia"},{"name":"Animal House Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0078-7849","authenticated-orcid":true,"given":"Tariq","family":"Sadad","sequence":"additional","affiliation":[{"name":"Department of Computer Science & Software Engineering, International Islamic University Islamabad, Islamabad, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amjad","family":"Rehman","sequence":"additional","affiliation":[{"name":"Artificial Intelligence & Data Analytics Lab CCIS Prince Sultan University, Riyadh, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fahad","family":"Almutairi","sequence":"additional","affiliation":[{"name":"Department of Diagnostic Radiology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia"},{"name":"Smart Medical Imaging Research Group, King Abdulaziz University, Jeddah 21589, Saudi Arabia"},{"name":"Animal House Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tanzila","family":"Saba","sequence":"additional","affiliation":[{"name":"Artificial Intelligence & Data Analytics Lab CCIS Prince Sultan University, Riyadh, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saeed Ali","family":"Bahaj","sequence":"additional","affiliation":[{"name":"MIS Department, College of Business Administration, Prince Sattam Bin Abdulaziz University, Alkharj 11942, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alhassan","family":"Alkhurim","sequence":"additional","affiliation":[{"name":"Department of Diagnostic Radiology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-021-05489-8"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.105015"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2022.105437"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.2174\/1573405616666201217112521"},{"key":"5","first-page":"169","article-title":"Prediction of two year survival among patients of non-small cell lung cancer","volume-title":"Lecture Notes in Computational Vision and Biomechanics","author":"Y. 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