Interpretable Deep Clustering Survival Machines for Alzheimer's Disease Risk Groups Discovery
Bojian Hou, Zixuan Wen, Jingxuan Bao, Richard Zhang, Boning Tong, Shu Yang, Junhao Wen, Yuhan Cui, Jason H Moore, Andrew J Saykin, Heng Huang, Paul M Thompson, Marylyn D Ritchie, Christos Davatzikos, Li Shen, Alzheimer's Disease Neuroimaging Initiative · 2025
Read Interpretable Deep Clustering Survival Machines for Alzheimer's Disease Risk Groups Discovery by Bojian Hou, Zixuan Wen, Jingxuan Bao, Richard Zhang, Boning Tong, Shu Yang, Junhao Wen, Yuhan Cui, Jason H Moore, Andrew J Saykin, Heng Huang, Paul M Thompson, Marylyn D Ritchie, Christos Davatzikos, Li Shen, Alzheimer's Disease Neuroimaging Initiative (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11715042.txt.
Description
Bojian Hou and co-authors present a 2025 method for sorting Alzheimer's risk in people with mild memory loss. Not everyone with mild cognitive impairment goes on to develop the disease. Finding who will change, and when, could guide drug trials and early care. Older grouping methods sorted patients without using time-to-event data, which wastes key facts.
Their method, called Deep Clustering Survival Machines, groups patients and predicts risk at the same time. It blends two styles of model and fits a survival curve for each group. The team applied it to brain scan data from a large Alzheimer's study network. Because the method can be read and explained, doctors can see why a patient lands in a given risk group.
Catalog record
| CREATOR | Bojian Hou, Zixuan Wen, Jingxuan Bao, Richard Zhang, Boning Tong, Shu Yang, Junhao Wen, Yuhan Cui, Jason H Moore, Andrew J Saykin, Heng Huang, Paul M Thompson, Marylyn D Ritchie, Christos Davatzikos, Li Shen, Alzheimer's Disease Neuroimaging Initiative |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 3 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |