Applying machine learning to assist in the morphometric assessment of brain arteriolosclerosis through automation

Applying machine learning to assist in the morphometric assessment of brain arteriolosclerosis through automation

Objective quantification of brain arteriolosclerosis remains an area of ongoing refinement in neuropathology, with current methods primarily utilizing semi-quantitative scales completed through manual histological examination. These approaches offer modest inter-rater reliability and do not provide...

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Main Authors: Jerry J. Lou, Peter Chang, Kiana D. Nava, Chanon Chantaduly, Hsin-Pei Wang, William H. Yong, Viharkumar Patel, Ajinkya J. Chaudhari, La Rissa Vasquez, Edwin Monuki, Elizabeth Head, Harry V. Vinters, Shino Magaki, Danielle J. Harvey, Chen-Nee Chuah, Charles S. DeCarli, Christopher K. Williams, Michael Keiser, Brittany N. Dugger
Format: Article
Language:English
Published: University of Münster / Open Journals System 2025-06-01
Series:Free Neuropathology
Subjects:
Machine learning
Artificial intelligence
Neuropathology
Arteriolosclerosis
Blood vessel
Morphometry
Online Access:https://www.uni-muenster.de/Ejournals/index.php/fnp/article/view/6387
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https://www.uni-muenster.de/Ejournals/index.php/fnp/article/view/6387

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