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 Articles Article Faculty Publications -Articles 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 LRE-MMF: A novel multi-modal fusion algorithm for detecting neurodegeneration in Parkinson's disease among the geriatric population Subject The topic of the resource Gerontological research; Localized region extraction; Multi-modal fusion; Neurodegeneration; Non-pharmacological treatment; Parkinson's disease; Rs-fMRI; sMRI Description An account of the resource Parkinson's disease (PD) is a prevalent neurological disorder characterized by progressive dopaminergic neuron loss, leading to both motor and non-motor symptoms. Early and accurate diagnosis is challenging due to the subtle and variable nature of early symptoms. This study aims to address these diagnostic challenges by proposing a novel method, Localized Region Extraction and Multi-Modal Fusion (LRE-MMF), designed to enhance diagnostic accuracy through the integration of structural MRI (sMRI) and resting-state functional MRI (rs-fMRI) data. The LRE-MMF method utilizes the complementary strengths of sMRI and rs-fMRI: sMRI provides detailed anatomical information, while rs-fMRI captures functional connectivity patterns. We applied this approach to a dataset consisting of 20 PD patients and 20 healthy controls (HC), all scanned with a 3 T MRI. The primary objective was to determine whether the integration of sMRI and rs-fMRI through the LRE-MMF method improves the classification accuracy between PD and HC subjects. LRE-MMF involves the division of imaging data into localized regions, followed by feature extraction and dimensionality reduction using Principal Component Analysis (PCA). The resulting features were fused and processed through a neural network to learn high-level representations. The model achieved an accuracy of 75 %, with a precision of 0.8125, recall of 0.65, and an AUC of 0.8875. The validation accuracy curves indicated good generalization, with significant brain regions identified, including the caudate, putamen, thalamus, supplementary motor area, and precuneus, as per the AAL atlas. These results demonstrate the potential of the LRE-MMF method for improving early diagnosis and understanding of PD by effectively utilizing both sMRI and rs-fMRI data. This approach could contribute to the development of more accurate diagnostic tools. 2024 The Authors Creator An entity primarily responsible for making the resource Chatterjee I.; Bansal V. Source A related resource from which the described resource is derived Experimental Gerontology, Vol-197 Publisher An entity responsible for making the resource available Elsevier 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/10.1016/j.exger.2024.112585" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.exger.2024.112585</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206236336&amp;doi=10.1016%2Fj.exger.2024.112585&amp;partnerID=40&amp;md5=64c505ba7d1df66f5702df62e9e64e92" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206236336&amp;doi=10.1016%2fj.exger.2024.112585&amp;partnerID=40&amp;md5=64c505ba7d1df66f5702df62e9e64e92</a> Rights Information about rights held in and over the resource All Open Access; Hybrid Gold Open Access Relation A related resource ISSN: 5315565; PubMed ID: 39306310; CODEN: EXGEA 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 Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Chatterjee I., Department of Computing and Mathematics, Manchester Metropolitan University, Manchester, United Kingdom, School of Technology, Woxsen University, Hyderabad, India, Centre for Research Impact &amp; Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India; Bansal V., Department of Psychology, Christ University, Bangalore, 560029, India