Attention-based MIL fuses irregular smartwatch activity, sleep, and ECG HRV data to predict discretized changes in handgrip strength and FACIT-F with balanced accuracies of 0.59-0.70 under LOSO evaluation.
Wearable Sensors and the Assessment of Frailty among Vulnerable Older Adults: An Observational Cohort Study
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1roles
background 1polarities
support 1representative citing papers
citing papers explorer
-
Frailty Estimation in Elderly Oncology Patients Using Multimodal Wearable Data and Multi-Instance Learning
Attention-based MIL fuses irregular smartwatch activity, sleep, and ECG HRV data to predict discretized changes in handgrip strength and FACIT-F with balanced accuracies of 0.59-0.70 under LOSO evaluation.