Open AccessRegional Radiomics Similarity Networks Reveal Distinct Subtypes and Abnormality Patterns in Mild Cognitive Impairment (Adv. Sci. 12/2022)
Author(s) -
Zhao Kun,
Zheng Qiang,
Dyrba Martin,
Rittman Timothy,
Li Ang,
Che Tongtong,
Chen Pindong,
Sun Yuqing,
Kang Xiaopeng,
Li Qiongling,
Liu Bing,
Liu Yong,
Li Shuyu
Publication year - 2022
Publication title -
advanced science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.388
H-Index - 100
ISSN - 2198-3844
DOI - 10.1002/advs.202270073
Subject(s) - radiomics , abnormality , cognitive impairment , similarity (geometry) , cognition , risk stratification , non negative matrix factorization , medicine , psychology , neuroscience , computer science , artificial intelligence , matrix decomposition , psychiatry , radiology , eigenvalues and eigenvectors , physics , quantum mechanics , image (mathematics)
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.