journal article·2022-04Open access

Regional Radiomics Similarity Networks Reveal Distinct Subtypes and Abnormality Patterns in Mild Cognitive Impairment (Adv. Sci. 12/2022)

Kun Zhao, Qiang Zheng, Martin Dyrba, Timothy Rittman, Ang Li, Tongtong Che, Pindong Chen, Yuqing Sun, Xiaopeng Kang, Qiongling Li, Bing Liu, Yong Liu, Shuyu Li, for the Alzheimer's Disease Neuroimaging Initiative

Advanced Science· Volume 9· Issue 12

Abstract

Regional Radiomics Similarity Networks Reveal Distinct Subtypes in the Mild Cognitive Impairment In article number 2104538 by Kun Zhao, Yong Liu, Shuyu Li, and co‐workers, two mild cognitive impairment (MCI) subtypes are identified by employing nonnegative matrix factorization on the regional radiomics similarity network (R2SN). The two MCI subtypes show specific distinct abnormal patterns in clinical manifestation and clinical outcomes. The stratification into the two subtypes provides a new insight for risk assessment and precise early intervention for MCI patients. [Image: see text]
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Research context

OpenAlex topics: Radiomics and Machine Learning in Medical Imaging

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