3 citations · 5 across the 7 of their papers we have counts for
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cs.AI2023
A Quantitatively Interpretable Model for Alzheimer's Disease Prediction Using Deep Counterfactuals
Kwanseok Oh, Da-Woon Heo, Ahmad Wisnu Mulyadi +4
Deep learning (DL) for predicting Alzheimer's disease (AD) has provided timely intervention in disease progression yet still demands attentive interpretability to explain how their…
cs.AI2023★ 1 cited
Deep Geometric Learning with Monotonicity Constraints for Alzheimer's Disease Progression
Seungwoo Jeong, Wonsik Jung, Junghyo Sohn +1
Alzheimer's disease (AD) is a devastating neurodegenerative condition that precedes progressive and irreversible dementia; thus, predicting its progression over time is vital for c…