{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T15:26:54Z","timestamp":1774538814702,"version":"3.50.1"},"reference-count":62,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T00:00:00Z","timestamp":1751673600000},"content-version":"vor","delay-in-days":185,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100023674","name":"Deanship of Scientific Research, King Khalid University","doi-asserted-by":"publisher","award":["RGP1\/15\/46"],"award-info":[{"award-number":["RGP1\/15\/46"]}],"id":[{"id":"10.13039\/501100023674","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Intelligent Systems"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:p>Breast cancer is the primary cause of death for women around the world, necessitating the development of highly accurate, interpreted, and technologically advanced predictive approaches to support early diagnosis and treatment. In this research, we introduce a deep learning (DL) model for predicting breast cancer using both public and private datasets. The model uses the internet of things (IoT) to improve data collection and real\u2010time monitoring, and it also uses the SMOTE method to resolve issues of class imbalance. The proposed model combines an explainable AI approach with SHAP values to ensure model interpretability. To identify the best DL algorithm for this method, we assess and compare six different DL algorithms: temporal convolutional networks (TCNs), neural factorization machines (NFMs), long short\u2013term memory (LSTM) networks, recurrent neural networks (RNNs), gated recurrent units (GRUs), and deep kernel learning (DKL). IoT devices allow for the continuous acquisition of patient data, which, when integrated with our predictive models, improve the capacity for early detection. Reliable cancer detection relies on our method\u2019s enhanced predictive accuracy and sensitivity. Furthermore, we offer crucial transparency in clinical settings by using SHAP to give detailed explanations of model decisions. By employing thorough statistical analysis and cross\u2010validation, we guarantee that our model is resilient and can be applied to various patient populations. The results show that our proposed IoT integrated method has the potential to improve prediction performance and boost confidence in AI\u2010powered medical diagnostics by making them more accessible and easier to use. From a performance perspective, the proposed approach, which uses the TCN algorithm and SMOTE, achieved the best accuracy for BC prediction. With the public dataset, the experimental results were 99.44%, 100.0%, 99.01%, 98.75%, 99.37%, and 99.89% for accuracy, sensitivity, specificity, precision, F1\u2010score, and AUC, respectively. The experimental results for accuracy, sensitivity, specificity, precision, F1\u2010score, and AUC using the private dataset were 97.33%, 93.33%, 100%, 100%, 96.55%, and 99.48%, respectively. On the other hand, with the combined datasets, the TCN algorithm achieved 100% for all performance metrics.<\/jats:p>","DOI":"10.1155\/int\/8884481","type":"journal-article","created":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T05:05:15Z","timestamp":1751691915000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["An Enhanced Approach for Predicting Breast Cancer Using Different Deep Learning Algorithms and Explainable AI Techniques in an IoT Environment"],"prefix":"10.1155","volume":"2025","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7292-6345","authenticated-orcid":false,"given":"Belgacem","family":"Bouallegue","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0701-087X","authenticated-orcid":false,"given":"Yasser M.","family":"Abd El-Latif","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4467-7227","authenticated-orcid":false,"given":"Hosam","family":"El-Sofany","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3028-6751","authenticated-orcid":false,"given":"Islam A. T. F.","family":"Taj-Eddin","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2025,7,5]]},"reference":[{"key":"e_1_2_13_1_2","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21660"},{"key":"e_1_2_13_2_2","doi-asserted-by":"publisher","DOI":"10.5306\/wjco.v5.i3.412"},{"key":"e_1_2_13_3_2","article-title":"Breast Cancer Prediction Using Machine Learning Models: a Systematic Review","volume":"186","author":"Aftab A.","year":"2022","journal-title":"Expert Systems with Applications"},{"key":"e_1_2_13_4_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-018-0316-z"},{"key":"e_1_2_13_5_2","article-title":"Deep Learning in Breast Cancer Prognosis and Prediction","volume":"13","author":"Liu Y.","year":"2022","journal-title":"Genes"},{"key":"e_1_2_13_6_2","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-019-0192-5"},{"key":"e_1_2_13_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2018.06.056"},{"key":"e_1_2_13_8_2","article-title":"Addressing Data Imbalance in Cancer Prediction Using SMOTE","volume":"133","author":"Rahman M. M.","year":"2021","journal-title":"Computers in Biology and Medicine"},{"key":"e_1_2_13_9_2","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-019-0048-x"},{"key":"e_1_2_13_10_2","first-page":"4765","volume-title":"Advances in Neural Information Processing Systems","author":"Lundberg S. M.","year":"2017"},{"key":"e_1_2_13_11_2","volume-title":"Interpretable Machine Learning: A Guide for Making Black Box Models Explainable","author":"Molnar C.","year":"2020"},{"key":"e_1_2_13_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2020.3027314"},{"key":"e_1_2_13_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/tbme.2015.2496264"},{"key":"e_1_2_13_14_2","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.26244"},{"key":"e_1_2_13_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2017.07.005"},{"key":"e_1_2_13_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2017.10.005"},{"key":"e_1_2_13_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.csbj.2014.11.005"},{"key":"e_1_2_13_18_2","doi-asserted-by":"publisher","DOI":"10.1145\/3386252"},{"key":"e_1_2_13_19_2","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2019182716"},{"key":"e_1_2_13_20_2","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"e_1_2_13_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2008.239"},{"key":"e_1_2_13_22_2","doi-asserted-by":"publisher","DOI":"10.1145\/1007730.1007735"},{"key":"e_1_2_13_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2016.12.035"},{"key":"e_1_2_13_24_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2018.07.011"},{"key":"e_1_2_13_25_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2017.09.030"},{"key":"e_1_2_13_26_2","article-title":"Consistent Individualized Feature Attribution for Tree Ensembles","author":"Lundberg S. M.","year":"2018","journal-title":"arXiv preprint arXiv:1802.03888"},{"key":"e_1_2_13_27_2","unstructured":"YangX. WangL. ZhangW. YuH. andXieL. Explainable Deep Learning for Medical Imaging: a Survey 2019."},{"key":"e_1_2_13_28_2","doi-asserted-by":"publisher","DOI":"10.1631\/fitee.1700808"},{"key":"e_1_2_13_29_2","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.aay7120"},{"key":"e_1_2_13_30_2","doi-asserted-by":"crossref","unstructured":"GilpinL. H. BauD. YuanB. Z. BajwaA. SpecterM. andKagalL. Explaining Explanations: an Overview of Interpretability of Machine Learning 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA) May 2018 80\u201389 https:\/\/doi.org\/10.1109\/dsaa.2018.00018 2-s2.0-85062824495.","DOI":"10.1109\/DSAA.2018.00018"},{"key":"e_1_2_13_31_2","first-page":"611","article-title":"Integrating Deep Learning with multi-modal Data for Precision Medicine in Cancer","volume":"21","author":"Zhao W.","year":"2021","journal-title":"Nature Reviews Cancer"},{"key":"e_1_2_13_32_2","unstructured":"TonekaboniS. JoshiS. McCraddenM. D. andGoldenbergA. What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use 2019."},{"key":"e_1_2_13_33_2","first-page":"57","article-title":"Multi-Modal Deep Learning: Methods and Applications","volume":"134","author":"Li X.","year":"2021","journal-title":"Neural Networks"},{"key":"e_1_2_13_34_2","first-page":"97","article-title":"A Novel CNN-based Method for Predicting Lung Cancer Growth on Serial Cts","volume":"104","author":"Zhao Z.","year":"2019","journal-title":"Computers in Biology and Medicine"},{"key":"e_1_2_13_35_2","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2009.191"},{"key":"e_1_2_13_36_2","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2016.2528162"},{"key":"e_1_2_13_37_2","doi-asserted-by":"publisher","DOI":"10.1109\/jproc.2020.3004555"},{"key":"e_1_2_13_38_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-97-6992-6_5"},{"key":"e_1_2_13_39_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2015.2437951"},{"key":"e_1_2_13_40_2","first-page":"6122","article-title":"Internet of Things-IoT: Definition, Characteristics, Architecture, Enabling Technologies, Application & Future Challenges","volume":"6","author":"Patel M.","year":"2016","journal-title":"International Journal of Engineering Science and Computing"},{"key":"e_1_2_13_41_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2021.102785"},{"key":"e_1_2_13_42_2","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2018.1700494"},{"key":"e_1_2_13_43_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2971393"},{"key":"e_1_2_13_44_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2015.2491281"},{"key":"e_1_2_13_45_2","doi-asserted-by":"crossref","unstructured":"BuiN.andZorziM. Health Care Applications: a Solution Based on the Internet of Things Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies August 2011 ACM 1\u20135.","DOI":"10.1145\/2093698.2093829"},{"key":"e_1_2_13_46_2","first-page":"243","article-title":"The Internet of Things: a Survey","volume":"20","author":"Li S.","year":"2018","journal-title":"Information Systems Frontiers"},{"key":"e_1_2_13_47_2","doi-asserted-by":"publisher","DOI":"10.1109\/jsyst.2015.2460747"},{"key":"e_1_2_13_48_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2020.107181"},{"key":"e_1_2_13_49_2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2017.2724037"},{"key":"e_1_2_13_50_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jksuci.2020.05.011"},{"key":"e_1_2_13_51_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2016.01.009"},{"key":"e_1_2_13_52_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-020-01838-7"},{"key":"e_1_2_13_53_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-016-0387-y"},{"key":"e_1_2_13_54_2","doi-asserted-by":"publisher","DOI":"10.1155\/2024\/6688934"},{"key":"e_1_2_13_55_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2017.07.005"},{"key":"e_1_2_13_56_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-48995-4"},{"key":"e_1_2_13_57_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-018-0316-z"},{"key":"e_1_2_13_58_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-019-1799-6"},{"key":"e_1_2_13_59_2","article-title":"Multi-Modal Deep Learning Model for Survival Prediction of Breast Cancer","volume":"10","author":"Zhang X.","year":"2020","journal-title":"Scientific Reports"},{"key":"e_1_2_13_60_2","doi-asserted-by":"crossref","unstructured":"VocaturoE.andZumpanoE. Artificial Intelligence Approaches on Ultrasound for Breast Cancer Diagnosis 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) June 2021 Houston TX USA 3116\u20133121 https:\/\/doi.org\/10.1109\/BIBM52615.2021.9669690.","DOI":"10.1109\/BIBM52615.2021.9669690"},{"key":"e_1_2_13_61_2","unstructured":"Wisconsin (Diagnostic) Dataset 2024."},{"key":"e_1_2_13_62_2","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"}],"container-title":["International Journal of Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/int\/8884481","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1155\/int\/8884481","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/int\/8884481","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T18:02:06Z","timestamp":1772992926000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/int\/8884481"}},"subtitle":[],"editor":[{"given":"Eugenio","family":"Vocaturo","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2025,1]]},"references-count":62,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["10.1155\/int\/8884481"],"URL":"https:\/\/doi.org\/10.1155\/int\/8884481","archive":["Portico"],"relation":{},"ISSN":["0884-8173","1098-111X"],"issn-type":[{"value":"0884-8173","type":"print"},{"value":"1098-111X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1]]},"assertion":[{"value":"2024-10-20","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-06-16","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-05","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"8884481"}}