{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T03:29:51Z","timestamp":1781234991293,"version":"3.54.1"},"reference-count":57,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2022,12,10]],"date-time":"2022-12-10T00:00:00Z","timestamp":1670630400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"FCT\/MCTES","award":["UIDB\/50008\/2020-UIDP\/50008\/2020"],"award-info":[{"award-number":["UIDB\/50008\/2020-UIDP\/50008\/2020"]}]},{"name":"FCT\/MCTES","award":["57473408"],"award-info":[{"award-number":["57473408"]}]},{"name":"Nigerian Petroleum Technology Development Fund (PTDF)","award":["UIDB\/50008\/2020-UIDP\/50008\/2020"],"award-info":[{"award-number":["UIDB\/50008\/2020-UIDP\/50008\/2020"]}]},{"name":"Nigerian Petroleum Technology Development Fund (PTDF)","award":["57473408"],"award-info":[{"award-number":["57473408"]}]},{"name":"German Academic Exchange Service (DAAD)","award":["UIDB\/50008\/2020-UIDP\/50008\/2020"],"award-info":[{"award-number":["UIDB\/50008\/2020-UIDP\/50008\/2020"]}]},{"name":"German Academic Exchange Service (DAAD)","award":["57473408"],"award-info":[{"award-number":["57473408"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Healthcare systems in recent times have witnessed timely diagnoses with a high level of accuracy. Internet of Medical Things (IoMT)-enabled deep learning (DL) models have been used to support medical diagnostics in real time, thus resolving the issue of late-stage diagnosis of various diseases and increasing performance accuracy. The current approach for the diagnosis of leukemia uses traditional procedures, and in most cases, fails in the initial period. Hence, several patients suffering from cancer have died prematurely due to the late discovery of cancerous cells in blood tissue. Therefore, this study proposes an IoMT-enabled convolutional neural network (CNN) model to detect malignant and benign cancer cells in the patient\u2019s blood tissue. In particular, the hyper-parameter optimization through radial basis function and dynamic coordinate search (HORD) optimization algorithm was used to search for optimal values of CNN hyper-parameters. Utilizing the HORD algorithm significantly increased the effectiveness of finding the best solution for the CNN model by searching multidimensional hyper-parameters. This implies that the HORD method successfully found the values of hyper-parameters for precise leukemia features. Additionally, the HORD method increased the performance of the model by optimizing and searching for the best set of hyper-parameters for the CNN model. Leukemia datasets were used to evaluate the performance of the proposed model using standard performance indicators. The proposed model revealed significant classification accuracy compared to other state-of-the-art models.<\/jats:p>","DOI":"10.3390\/s22249689","type":"journal-article","created":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T05:10:19Z","timestamp":1670821819000},"page":"9689","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["An Enhanced Hyper-Parameter Optimization of a Convolutional Neural Network Model for Leukemia Cancer Diagnosis in a Smart Healthcare System"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1020-4432","authenticated-orcid":false,"given":"Joseph Bamidele","family":"Awotunde","sequence":"first","affiliation":[{"name":"Department of Computer Science, Faculty of Information and Communication Sciences, University of Ilorin, Ilorin 240003, Nigeria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8921-8353","authenticated-orcid":false,"given":"Agbotiname Lucky","family":"Imoize","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronics Engineering, Faculty of Engineering, University of Lagos, Akoka, Lagos 100213, Nigeria"},{"name":"Department of Electrical Engineering and Information Technology, Institute of Digital Communication, Ruhr University, 44801 Bochum, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2116-8059","authenticated-orcid":false,"given":"Oluwafisayo Babatope","family":"Ayoade","sequence":"additional","affiliation":[{"name":"Department of Computing and Information Science, School of Pure & Applied Sciences, College of Science, Bamidele Olumilua University of Education, Science & Technology, Ikere-Ekiti 361264, Nigeria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Moses Kazeem","family":"Abiodun","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Landmark University, Omu-Aran 251103, Nigeria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dinh-Thuan","family":"Do","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, College of Information and Electrical Engineering, Asia University, Taichung 41354, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7008-6773","authenticated-orcid":false,"given":"Ad\u00e3o","family":"Silva","sequence":"additional","affiliation":[{"name":"Instituto de Telecomunica\u00e7\u00f5es (IT) and Departamento de Eletr\u00f3nica, Telecomunica\u00e7\u00f5es e Inform\u00e1tica (DETI), University of Aveiro, 3810-193 Aveiro, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8184-0623","authenticated-orcid":false,"given":"Samarendra Nath","family":"Sur","sequence":"additional","affiliation":[{"name":"Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Majitar, Rangpo 737136, Sikkim, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3303","DOI":"10.1007\/s12652-020-02218-1","article-title":"Echo state learned compositional pattern neural networks for the early diagnosis of cancer on the internet of medical things platform","volume":"12","author":"Kirubakaran","year":"2021","journal-title":"J. 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