Capitalizing on Intelligent Pathology Algorithms in Dementia Care

Capitalizing on Intelligent Pathology Algorithms in Dementia Care | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 19 February 2026 V1 Latest version Share on Capitalizing on Intelligent Pathology Algorithms in Dementia Care Authors : Ritwik Raj Saxena 0009-0001-7876-3193 [email protected] and Ritcha Saxena Authors Info & Affiliations https://doi.org/10.22541/au.177153543.33219778/v1 66 views 71 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract The field of medical science is attempting to overcome the hurdles to develop algorithmic systems which can bring a positive shift in the paradigm of care of people with dementia, with the goal to delay the onset of the disease, to monitor its progression after its onset and to retard it, and to increase lifespans of patients and improve their quality of life. The integration of artificial intelligence (AI) into pathology has introduced avantgarde possibilities for the field of dementia research and clinical care. Pathology algorithms powered by advanced machine learning and deep learning techniques have enabled the automated analysis of complex, multimodal datasets, which comprise, inter alia, histopathological slides, neuroimaging scans, and genomic profiles. In this position paper, we show how these algorithms hold the potential to facilitate early diagnosis, improve accuracy in dementia subtype classification, and enable the personalized management of dementia by uncovering disease patterns previously inaccessible to traditional approaches. We further demonstrate that AI-driven models can provide accurate predictions and prognoses, engage in effective therapeutic response monitoring, and offer a data-driven foundation for targeted interventions. The variability and heterogeneity of data, lack of generalizability, the need for interpretability and regulatory compliance etc. present noteworthy obstacles. This paper scans over the state-of-the-art in AI pathology algorithms as applied to dementia. It emphasizes their various roles including those in imaging, in biomarker discovery, and in disease progression modeling. It also discusses ethical concerns and privacy safeguards in the use of sensitive patient data and highlights the collaborative efforts required among researchers, clinicians, and policymakers to ensure the responsible and equitable deployment of these technologies. We hypothesize that AI pathology algorithms can pave the way for innovative advancements in dementia care which are oriented around the needs of dementia patients. Supplementary Material File (example (autorecovered) 1.pdf) Download 307.83 KB Information & Authors Information Version history V1 Version 1 19 February 2026 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords computational pathology convolutional neural networks dementia digital pathology image segmentation pathology algorithms vision transformers Authors Affiliations Ritwik Raj Saxena 0009-0001-7876-3193 [email protected] Department of Computer Science, University of Missouri View all articles by this author Ritcha Saxena Department of Biomedical Sciences, University of Minnesota View all articles by this author Metrics & Citations Metrics Article Usage 66 views 71 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Ritwik Raj Saxena, Ritcha Saxena. Capitalizing on Intelligent Pathology Algorithms in Dementia Care. Authorea . 19 February 2026. DOI: https://doi.org/10.22541/au.177153543.33219778/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. 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