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 Analysis Conducted Retrospectively on the Use: Artificial Intelligence in the Detection of Uterine Fibroid Subject The topic of the resource DCNN; Deep Learning; Fibroids; Magnetic resonance imaging; Ultrasonography Description An account of the resource The most frequent benign pelvic tumors in women of age of conception are uterine fibroids, sometimes referred to as leiomyomas. Ultrasonography is presently the first imaging modality utilized as clinical identification of uterine fibroids since it has a high degree of specificity and sensitivity and is less expensive and more widely accessible than CT and MRI examination. However, certain issues with ultrasound based uterine fibroid diagnosis persist. The main problem is the misunderstanding of pelvic and adnexal masses, as well as subplasmic and large fibroids. The specificity of fibroid detection is impacted by the existing absence of standardized image capture views and the variations in performance amongst various ultrasound machines. Furthermore, the proficiency and expertise of ultra sonographers determines the accuracy of the ultrasound diagnosis of uterine fibroids. In this work, we created a Deep convolutional neural networks (DCNN) model that automatically identifies fibroids in the uterus in ultrasound pictures, distinguishes between their presence and absence, and has been internally as well as externally validated in order to increase the reliability of the ultrasound examinations for uterine fibroids. Additionally, we investigated whether Deep convolutional neural networks model may help junior ultrasound practitioners perform better diagnostically by comparing it to eight ultrasound practitioners at different levels of experience. 2024 IEEE. Creator An entity primarily responsible for making the resource Kaushik R.; Sharma K.P.; Malik S.; Shanbhog M. Source A related resource from which the described resource is derived 2024 11th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2024 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 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICRITO61523.2024.10522120" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICRITO61523.2024.10522120</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193846764&amp;doi=10.1109%2FICRITO61523.2024.10522120&amp;partnerID=40&amp;md5=67fe94a68db99724c0847cd071bae735" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193846764&amp;doi=10.1109%2fICRITO61523.2024.10522120&amp;partnerID=40&amp;md5=67fe94a68db99724c0847cd071bae735</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835035035-7 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 Kaushik R., Christ(Deemed to Be Univeristy), Delhi Ncr Campus, Department of Computer Science, Ghaziabad, India; Sharma K.P., Gla University, Department of Computer Engineering and Application, Mathura, India; Malik S., Christ(Deemed to Be Univeristy), Delhi Ncr Campus, Department of Computer Science, Ghaziabad, India; Shanbhog M., Christ(Deemed to Be Univeristy), Delhi Ncr Campus, Department of Computer Science, Ghaziabad, India