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 Conference Papers 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/. Title A name given to the resource An Efficient Quantum Transfer Learning for Cancer Prediction Using Tumour Markers: New Era of Computer in Medical Subject The topic of the resource accuracy; antigen; biomarkers; diagnosis; ovarian cancer; prediction; prognosis; Quantum learning; transfer learning; tumour Description An account of the resource Ovarian cancer prediction models or algorithms estimate a person's risk of getting the disease based on different variables, such as their medical history, genetics, and biomarkers. Early identification and intervention will enhance patient successive diagnosis outcomes. Tumour markers are chemicals frequently detected in higher concentrations than usual in cancer patient's blood, urine, or tissues. They could be certain chemicals or proteins linked to the presence of tumours or cancer kinds. Tumour markers are employed for diagnosis, prognosis, and treatment response monitoring. Applying information or models from one quantum job to enhance the performance of another requires quantum transfer learning. Transferring knowledge from one domain to another seeks to increase learning effectiveness in novel quantum contexts. The main goal of efficient Quantum Transfer Learning (QTL) is to minimize the resources (computer power, data, or time) necessary to transfer between tasks successfully. In this research work, QTL is used to predict Ovarian Cancer (OC) with the assistance of biomarkers. The Quantum Transfer Learning- Ovarian Cancer (QTL-OC) achieves 93.78% accuracy and outperforms the existing techniques. 2023 IEEE. Creator An entity primarily responsible for making the resource Narendran M.; Andi H.K.; Sharma D.K.; Amarendra K.; Uma S.; Poonia R.C. Source A related resource from which the described resource is derived 2023 International Conference on Communication, Security and Artificial Intelligence, ICCSAI 2023, pp. 432-437. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICCSAI59793.2023.10421549" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICCSAI59793.2023.10421549</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186679596&amp;doi=10.1109%2FICCSAI59793.2023.10421549&amp;partnerID=40&amp;md5=b01a0309ee6aed345006b0543ea25a9a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186679596&amp;doi=10.1109%2fICCSAI59793.2023.10421549&amp;partnerID=40&amp;md5=b01a0309ee6aed345006b0543ea25a9a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835036996-0 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Narendran M., Kcg College of Technology, Department of Information Technology, Tamil Nadu, Chennai, India; Andi H.K., Asia Metropolitan University, Centre for Postgraduate Studies, Malaysia; Sharma D.K., Jaypee University of Engineering and Technology, Department of Mathematics, Madhya Pradesh, Guna, 473226, India; Amarendra K., Koneru Lakshmaiah Education Foundation, Department of Computer Science and Engineering, Andhra Pradesh, Vaddeswaram, 522502, India; Uma S., Dhanalakshmi Srinivasan College of Engineering and Technology, Department of Computer Science and Engineering, Tamil Nadu, Mamallapuram, India; Poonia R.C., Christ (Deemed to Be University), Department of Computer Science, Delhi-NCR, Uttar Pradesh, Ghaziabad, 201003, India