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 Jacob, Lija; Thomas, K.T.; Samuel, Libin Chacko; Thomas, Sharon Susan Title A name given to the resource Fusion Techniques for medical imaging and clinical data towards precision diagnostics and personalized care 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 Multimodal Learning Using Heterogeneous Data;pp.139-155 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/B978-0-443-27528-9.00010-3" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/B978-0-443-27528-9.00010-3</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105032936998?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105032936998?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 Jacob L., Department of Statistics and Data Science, Christ University, Karnataka, Bengaluru, India; Thomas K.T., Department of Computer Science, Christ Unversity, Karnataka, Bengaluru, India; Samuel L.C., Department of Computer Science, Christ Unversity, Karnataka, Bengaluru, India; Thomas S.S., Department of Computer Science, Christ Unversity, Karnataka, Bengaluru, India Description An account of the resource The combination of clinical data with medical imaging has created a revolution in modern healthcare, which provides a clear insight into patient's health sometimes in an earlier stage itself. Magnetic resonance imaging, computed tomography scans, ultrasounds, and X-rays are a few of the medical imaging techniques that offer high-resolution representations of the body's structure and physiological processes. Clinical data, such as physical examinations, test findings, and medical histories, help to contextualize these photographs, which enhances treatment planning and broadens diagnostic discoveries. Fusion approaches combine data from multiple sources to create a unified dataset, making diagnoses more accurate and treatments more personalized. This chapter emphasizes the importance of the fusion of heterogeneous medical data along with various fusion techniques, including deep learning and attention mechanisms, to align medical images with clinical data for meaningful insights. By using fusion techniques, healthcare professionals can make real-time decisions, identify diseases with better accuracy, and derive insights that can lead to actionable treatment or management strategies. Advanced fusion methods enable healthcare providers to obtain a holistic view of a patient's health, allowing advancements in precision medicine and customized treatment plans. 2026 Elsevier Inc. All rights reserved. Subject The topic of the resource attention mechanism; Clinical data fusion; deep learning; disease classification; healthcare; healthcare systems; image-to-clinical data alignment; personalized medicine; personalized treatment; precision medicine Publisher An entity responsible for making the resource available Elsevier Relation A related resource ISBN: 978-044327528-9; 978-044327529-6; 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