Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Upreti, Kamal; Hunekari, Sheela; Upreti, Shitiz; Rai, Ashish Kumar; Alam, Mohammad Shabbir; Nasir, Mohammad Shahnawaz Title A name given to the resource A Study on Gynecological Cancers Using Artificial Intelligence: A Revolutionary Approach Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025;pp.259-263 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/IC363308.2025.10957236" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/IC363308.2025.10957236</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105003909686?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105003909686?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Upreti K., Christ University, Dept. of Computer Science, Delhi- NCR Campus, Ghaziabad, India; Hunekari S., School of Engineering and Technology, Pimpri Chinchwad University, Maharashtra, India; Upreti S., Maharishi Markandeshwar (Deemed to be University), Department of Management, Mullana, Haryana, Ambala, India; Rai A.K., Ramchandra Chandravansi University, Faculty of Commerce &amp; Management, Jharkhand, India; Alam M.S., Cmj University, Dept. of Computer Science, India; Nasir M.S., Cmj University, Dept. of Computer Science, India Description An account of the resource An examination of the role of artificial intelligence (AI) in ovarian, cervical, and breast cancer early detection and management is presented in this paper. Artificial intelligence (AI) can improve diagnostic accuracy, streamline treatment protocols, and facilitate personalized medicine approaches by leveraging advancements in machine learning (ML) and deep learning (DL). Various Artificial Intelligence models have demonstrated success in improving the outcomes of cancer diagnostics, including their ability to distinguish benign from malignant tumors. Technology challenges and ethical issues related to the integration of AI into clinical practice are also discussed in the review. Specifically, we want to illustrate how artificial intelligence can lead to better prognoses and reduced mortality rates for cancer patients by enhancing early detection capabilities. 2025 IEEE. Subject The topic of the resource analysis; artificial intelligence; detection; Gynecological cancer; prediction Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833152749-5; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online