Precise diagnosis of Alzheimer’s disease based on sex-specific gray matter characteristics
Abstrak
IntroductionThere are notable sex differences in the gray matter of Alzheimer’s disease(AD) patients’ brains, but current evidence is insufficient to prove these differences aid diagnosis effectively.MethodsMultivariate analysis of variance was performed on the preprocessed gray matter of healthy female and healthy male groups to identify the gray matter clusters with significant intergroup differences. Subsequently, multiple machine learning models were employed to develop sex-specific diagnostic models for AD.ResultsWe identified 11 brain regions showing sex differences, of which 8 were sex-specific in both female and male AD patients, exhibiting significant atrophy. Graph theory analysis demonstrated that the sex-specific gray matter structural brain networks in female and male AD patients exhibited distinct network alterations. We subsequently employed five advanced machine learning algorithms to develop diagnostic models for AD based on these sex-specific gray matter clusters, resulting in a notable improvement in performance.DiscussionSex-specific gray matter characteristics can facilitate more accurate diagnosis of AD.
Topik & Kata Kunci
Penulis (24)
Jiachen Chen
Jiachen Chen
Jiachen Chen
Kaiping Wang
Kaiping Wang
Haoling Cao
Haoling Cao
Haoling Cao
Yongfeng Liang
Yongfeng Liang
Yongfeng Liang
Yongfeng Liang
Yunxia Lou
Yunxia Lou
Yunxia Lou
Yunxia Lou
Junkang Yang
Junkang Yang
Junkang Yang
Xiangtao Lin
Yuchun Tang
Yuchun Tang
Yuchun Tang
Yuchun Tang
Akses Cepat
- Tahun Terbit
- 2026
- Sumber Database
- DOAJ
- DOI
- 10.3389/fnins.2026.1755938
- Akses
- Open Access ✓