{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T02:47:23Z","timestamp":1790390843999,"version":"4.1.0"},"reference-count":38,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2024,12,24]],"date-time":"2024-12-24T00:00:00Z","timestamp":1734998400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"United Arab Emirates University, UAEU Strategic Research Grant G00003676","award":["Fund No.: 12R136"],"award-info":[{"award-number":["Fund No.: 12R136"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background: Neurodegenerative diseases (NGD) encompass a range of progressive neurological conditions, such as Alzheimer\u2019s disease (AD) and Parkinson\u2019s disease (PD), characterised by the gradual deterioration of neuronal structure and function. This degeneration manifests as cognitive decline, movement impairment, and dementia. Our focus in this investigation is on PD, a neurodegenerative disorder characterized by the loss of dopamine-producing neurons in the brain, leading to motor disturbances. Early detection of PD is paramount for enhancing quality of life through timely intervention and tailored treatment. However, the subtle nature of initial symptoms, like slow movements, tremors, muscle rigidity, and psychological changes, often reduce daily task performance and complicate early diagnosis. Method: To assist medical professionals in timely diagnosis of PD, we introduce a cutting-edge Multimodal Diagnosis framework (PMMD). Based on deep learning techniques, the PMMD framework integrates imaging, handwriting, drawing, and clinical data to accurately detect PD. Notably, it incorporates cross-modal attention, a methodology previously unexplored within the area, which facilitates the modelling of interactions between different data modalities. Results: The proposed method exhibited an accuracy of 96% on the independent tests set. Comparative analysis against state-of-the-art models, along with an in-depth exploration of attention mechanisms, highlights the efficacy of PMMD in PD classification. Conclusions: The obtained results highlight exciting new prospects for the use of handwriting as a biomarker, along with other information, for optimal model performance. PMMD\u2019s success in integrating diverse data sources through cross-modal attention underscores its potential as a robust diagnostic decision support tool for accurately diagnosing PD.<\/jats:p>","DOI":"10.3390\/diagnostics15010004","type":"journal-article","created":{"date-parts":[[2024,12,24]],"date-time":"2024-12-24T04:45:49Z","timestamp":1735015549000},"page":"4","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Parkinson\u2019s Disease Prediction: An Attention-Based Multimodal Fusion Framework Using Handwriting and Clinical Data"],"prefix":"10.3390","volume":"15","author":[{"given":"Sabrina","family":"Benredjem","sequence":"first","affiliation":[{"name":"Laboratory of Mathematics, Informatics and Systems (LAMIS), Echahid Cheikh Larbi Tebessi University, Tebessa 12002, Algeria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4791-4227","authenticated-orcid":false,"given":"Tahar","family":"Mekhaznia","sequence":"additional","affiliation":[{"name":"Laboratory of Mathematics, Informatics and Systems (LAMIS), Echahid Cheikh Larbi Tebessi University, Tebessa 12002, Algeria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0266-1027","authenticated-orcid":false,"given":"Rawad","family":"Abdulghafor","sequence":"additional","affiliation":[{"name":"Faculty of Computer Studies (FCS), Arab Open University\u2013Oman, P.O. Box 1596, Muscat 130, Oman"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6661-8469","authenticated-orcid":false,"given":"Sherzod","family":"Turaev","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Software Engineering, College of Information Technology, United Arab Emirates University, Al Ain 15551, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3185-8806","authenticated-orcid":false,"given":"Akram","family":"Bennour","sequence":"additional","affiliation":[{"name":"Laboratory of Mathematics, Informatics and Systems (LAMIS), Echahid Cheikh Larbi Tebessi University, Tebessa 12002, Algeria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bourmatte","family":"Sofiane","sequence":"additional","affiliation":[{"name":"Independent Researcher, Ain Mlila 04002, Algeria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdulaziz","family":"Aborujilah","sequence":"additional","affiliation":[{"name":"Department of Management Information System, College of Commerce & Business Administration, Dhofar University, Salalah 211, Oman"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7172-8224","authenticated-orcid":false,"given":"Mohamed","family":"Al Sarem","sequence":"additional","affiliation":[{"name":"Department of Information Technology, Aylol University College, Yarim 547, Yemen"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1038\/s41531-022-00280-4","article-title":"A nationwide study of the incidence, prevalence and mortality of Parkinson\u2019s disease in the Norwegian population","volume":"8","author":"Brakedal","year":"2022","journal-title":"npj Park. 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