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 Book Chapter Faculty Publications- Book Chapter 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 Indu, P.V.; Nanjundan, Preethi; Thomas, Lijo Title A name given to the resource Artificial Intelligence and Machine Learning Applications in Threat Detection 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 Protecting and Mitigating Against Cyber Threats: Deploying Artificial Intelligence and Machine Learning;pp.41-56 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1002/9781394305216.ch3" target="_blank" rel="noreferrer noopener">https://doi.org/10.1002/9781394305216.ch3</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105015729511?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105015729511?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 Indu P.V., Department of Economics and Analytics, Christ University, Pune, India; Nanjundan P., Department of Data Science, Christ University, Pune, India; Thomas L., Department of Psychology, Christ University, Pune, India Description An account of the resource Artificial intelligence (AI) and machine mastering (ML) have emerged as progressive breakthroughs in medical prognosis, especially in the area of early most cancers diagnosis. These trendy gadgets significantly enhance the accuracy and performance of tumor detection. By analyzing huge records units, synthetic intelligence structures can identify small styles and anomalies in medical imaging, which lets in malignant tumors to be recognized earlier and greater appropriately than traditional methods. AI and ML are needed to accelerate tumor analysis and category in the context of most cancers remedy. These technologies assist doctors quickly perceive any abnormalities in radiological pictures inclusive of X-rays, MRIs and CT scans. Artificial intelligence reduces the workload of clinical specialists through automating this manner, enabling faster and greater correct analysis. In addition, AI can assist tailor remedy packages contemplating a patient's specific records, maximizing treatments and predicting remedy outcomes. In addition to improving the performance and speed of diagnosis, the aggregate of AI and ML in tumor detection suggests the capability to boom the general effectiveness of cancer treatment and in the end enhance affected person consequences. 2025 Scrivener Publishing LLC. Subject The topic of the resource Artificial intelligence (AI); Banking; Education; Finance; Healthcare; Machine learning (ML); Self-driving cars; Threat detection Publisher An entity responsible for making the resource available wiley Relation A related resource ISBN: 978-139430521-6; 978-139430522-3; Language A language of the resource English Type The nature or genre of the resource Book chapter 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