{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T00:40:07Z","timestamp":1730335207678,"version":"3.28.0"},"reference-count":345,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2023,10,17]],"date-time":"2023-10-17T00:00:00Z","timestamp":1697500800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Laboratory of Energetic System Modelling (LMSE) of the University of Biskra, Algeria"},{"name":"General Directorate of Scientific Research and Technological Development (DGRSDT) in Algeria"},{"name":"Ministry of Higher Education and Scientific Research in Algeria","award":["A01L08UN070120220003"]},{"name":"University of Dubai"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"Artificial intelligence (AI) has significantly impacted thyroid cancer diagnosis in recent years, offering advanced tools and methodologies that promise to revolutionize patient outcomes. This review provides an exhaustive overview of the contemporary frameworks employed in the field, focusing on the objective of AI-driven analysis and dissecting methodologies across supervised, unsupervised, and ensemble learning. Specifically, we delve into techniques such as deep learning, artificial neural networks, traditional classification, and probabilistic models (PMs) under supervised learning. With its prowess in clustering and dimensionality reduction, unsupervised learning (USL) is explored alongside ensemble methods, including bagging and potent boosting algorithms. The thyroid cancer datasets (TCDs) are integral to our discussion, shedding light on vital features and elucidating feature selection and extraction techniques critical for AI-driven diagnostic systems. We lay out the standard assessment criteria across classification, regression, statistical, computer vision, and ranking metrics, punctuating the discourse with a real-world example of thyroid cancer detection using AI. Additionally, this study culminates in a critical analysis, elucidating current limitations and delineating the path forward by highlighting open challenges and prospective research avenues. Through this comprehensive exploration, we aim to offer readers a panoramic view of AI\u2019s transformative role in thyroid cancer diagnosis, underscoring its potential and pointing toward an optimistic future.<\/jats:p>","DOI":"10.3390\/systems11100519","type":"journal-article","created":{"date-parts":[[2023,10,17]],"date-time":"2023-10-17T12:25:09Z","timestamp":1697545509000},"page":"519","source":"Crossref","is-referenced-by-count":20,"title":["AI in Thyroid Cancer Diagnosis: Techniques, Trends, and Future Directions"],"prefix":"10.3390","volume":"11","author":[{"given":"Yassine","family":"Habchi","sequence":"first","affiliation":[{"name":"Institute of Technology, University Center Salhi Ahmed, BP 58 Naama, Naama 45000, Algeria"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-8904-5587","authenticated-orcid":false,"given":"Yassine","family":"Himeur","sequence":"additional","affiliation":[{"name":"College of Engineering and Information Technology, University of Dubai, Dubai 14143, United Arab Emirates"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-9532-2453","authenticated-orcid":false,"given":"Hamza","family":"Kheddar","sequence":"additional","affiliation":[{"name":"LSEA Laboratory, Electrical Engineering Department, University of Medea, Medea 26000, Algeria"}]},{"given":"Abdelkrim","family":"Boukabou","sequence":"additional","affiliation":[{"name":"Department of Electronics, University of Jijel, BP 98 Ouled Aissa, Jijel 18000, Algeria"}]},{"ORCID":"http:\/\/orcid.org\/0000-0003-3017-9243","authenticated-orcid":false,"given":"Shadi","family":"Atalla","sequence":"additional","affiliation":[{"name":"College of Engineering and Information Technology, University of Dubai, Dubai 14143, United Arab Emirates"}]},{"given":"Ammar","family":"Chouchane","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, University of Yahia Fares Medea, Medea 26000, Algeria"}]},{"given":"Abdelmalik","family":"Ouamane","sequence":"additional","affiliation":[{"name":"Laboratory of LI3C, Mohamed Khider University, Biskra 07000, Algeria"}]},{"ORCID":"http:\/\/orcid.org\/0000-0003-2784-5188","authenticated-orcid":false,"given":"Wathiq","family":"Mansoor","sequence":"additional","affiliation":[{"name":"College of Engineering and Information Technology, University of Dubai, Dubai 14143, United Arab Emirates"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Himeur, Y., Al-Maadeed, S., Varlamis, I., Al-Maadeed, N., Abualsaud, K., and Mohamed, A. 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