D4Care: A Deep Dynamic Memory-Driven Cross-Modal Feature Representation Network for Clinical Outcome Prediction
With the advancement of information technology, artificial intelligence (AI) has demonstrated significant potential in clinical prediction, helping to improve the level of intelligent medical care. Current clinical practice primarily relies on patients’ time series data and clinical notes to predict...
Saved in:
| Main Authors: | Binyue Chen, Guohua Liu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/11/6054 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
DCLMA: Deep correlation learning with multi-modal attention for visual-audio retrieval
by: Jiwei Zhang, et al.
Published: (2025-09-01) -
Multi-Modal Fusion of Routine Care Electronic Health Records (EHR): A Scoping Review
by: Zina Ben-Miled, et al.
Published: (2025-01-01) -
An effective multi-step feature selection framework for clinical outcome prediction using electronic medical records
by: Hongnian Wang, et al.
Published: (2025-02-01) -
The modulation of selective attention and divided attention on cross-modal congruence
by: Honghui Xu, et al.
Published: (2025-04-01) -
COPD-MMDDxNet: a multimodal deep learning framework for accurate COPD diagnosis using electronic medical records
by: Yuanyuan Yi, et al.
Published: (2025-07-01)