Dandan Cheng
Papers
1
Total Citations
29
H-Index
1
About
Dandan Cheng is a leading researcher at the intersection of artificial intelligence and neurorehabilitation, with a primary focus on developing predictive models for stroke recovery. Her most impactful work introduces a transferable deep learning prognosis model that addresses a critical gap in rehabilitation medicine: the ability to predict patient outcomes across different treatment modalities. This 2022 study, which has garnered 29 citations, tackles the fundamental challenge that recovery outcomes vary significantly depending on the rehabilitation approach, yet few models exist to forecast patient trajectories for multiple treatments. By creating a framework that can transfer learning across different rehabilitation protocols, Cheng's work enables clinicians to personalize therapy plans based on predicted recovery patterns. This contribution is particularly valuable given that the underlying mechanisms of neurorehabilitation remain incompletely understood. Her research represents a significant step toward data-driven, precision rehabilitation medicine, offering hope for more effective and individualized stroke recovery interventions.
Research Focus
Key Achievements
Top Papers
- 1