{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T16:15:18Z","timestamp":1781367318099,"version":"3.54.1"},"reference-count":35,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2022,10,2]],"date-time":"2022-10-02T00:00:00Z","timestamp":1664668800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Kidney cancer is a very dangerous and lethal cancerous disease caused by kidney tumors or by genetic renal disease, and very few patients survive because there is no method for early prediction of kidney cancer. Early prediction of kidney cancer helps doctors start proper therapy and treatment for the patients, preventing kidney tumors and renal transplantation. With the adaptation of artificial intelligence, automated tools empowered with different deep learning and machine learning algorithms can predict cancers. In this study, the proposed model used the Internet of Medical Things (IoMT)-based transfer learning technique with different deep learning algorithms to predict kidney cancer in its early stages, and for the patient\u2019s data security, the proposed model incorporates blockchain technology-based private clouds and transfer-learning trained models. To predict kidney cancer, the proposed model used biopsies of cancerous kidneys consisting of three classes. The proposed model achieved the highest training accuracy and prediction accuracy of 99.8% and 99.20%, respectively, empowered with data augmentation and without augmentation, and the proposed model achieved 93.75% prediction accuracy during validation. Transfer learning provides a promising framework with the combination of IoMT technologies and blockchain technology layers to enhance the diagnosing capabilities of kidney cancer.<\/jats:p>","DOI":"10.3390\/s22197483","type":"journal-article","created":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T03:07:28Z","timestamp":1665371248000},"page":"7483","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":85,"title":["Kidney Cancer Prediction Empowered with Blockchain Security Using Transfer Learning"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1443-8065","authenticated-orcid":false,"given":"Muhammad Umar","family":"Nasir","sequence":"first","affiliation":[{"name":"Riphah School of Computing and Innovation, Riphah International University Lahore Campus, Lahore 54000, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3999-6581","authenticated-orcid":false,"given":"Muhammad","family":"Zubair","sequence":"additional","affiliation":[{"name":"Faculty of Computing, Riphah International University, Islamabad 45000, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0672-7924","authenticated-orcid":false,"given":"Taher M.","family":"Ghazal","sequence":"additional","affiliation":[{"name":"Center for Cyber Security, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia"},{"name":"College of Computer and Information Technology, American University in the Emirates, Dubai Academic City, Dubai 503000, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad Farhan","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of Forensic Sciences, University of Health Sciences, Lahore 54000, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5240-0984","authenticated-orcid":false,"given":"Munir","family":"Ahmad","sequence":"additional","affiliation":[{"name":"School of Computer Science, National College of Business Administration & Economics, Lahore 54000, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6696-277X","authenticated-orcid":false,"given":"Atta-ur","family":"Rahman","sequence":"additional","affiliation":[{"name":"Department of Computer Science, College of Computer Science and Information Technology (CCSIT), Imam Abdulrahman Bin Faisal University (IAU), P.O. Box 1982, Dammam 31441, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1353-4138","authenticated-orcid":false,"given":"Hussam Al","family":"Hamadi","sequence":"additional","affiliation":[{"name":"College of Engineering and IT, University of Dubai, Dubai 14143, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9789-5231","authenticated-orcid":false,"given":"Muhammad Adnan","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of Software, Gachon University, Seongnam 13120, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2784-5188","authenticated-orcid":false,"given":"Wathiq","family":"Mansoor","sequence":"additional","affiliation":[{"name":"College of Engineering and IT, University of Dubai, Dubai 14143, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.eururo.2016.02.029","article-title":"The 2016 WHO Classification of Tumours of the Urinary System and Male Genital Organs-Part A: Renal, Penile, and Testicular Tumours","volume":"70","author":"Moch","year":"2016","journal-title":"Eur. 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