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researcher

Lequan Yu

4 papers hereh-index 455 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author1

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.LG1
  • eess.SP1
same name
  • Lequan Yu — 10 papers, h 4
  • Lequan Yu — 10 papers, h 7
  • Lequan Yu — 5 papers, h 3
  • Lequan Yu — 5 papers, h 3
  • Lequan Yu — 5 papers, h 3
  • Lequan Yu — 3 papers, h 6

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.CV2026

Context-driven Missing-Modality Learning for Robust Medical Diagnosis with Image-Tabular Data

Tianling Liu, Lequan Yu, Tong Han +1

While multimodal data integrating diverse imaging and clinical tabular records is crucial for accurate medical diagnosis, the arbitrary absence of specific modalities is prevalent…

cs.CV2026

CFCML: A Coarse-to-Fine Crossmodal Learning Framework For Disease Diagnosis Using Multimodal Images and Tabular Data

Tianling Liu, Hongying Liu, Fanhua Shang +3

In clinical practice, crossmodal information including medical images and tabular data is essential for disease diagnosis. There exists a significant modality gap between these dat…

cs.LG2025

CTPD: Cross-Modal Temporal Pattern Discovery for Enhanced Multimodal Electronic Health Records Analysis

Fuying Wang, Feng Wu, Yihan Tang +1

Integrating multimodal Electronic Health Records (EHR) data, such as numerical time series and free-text clinical reports, has great potential in predicting clinical outcomes. Howe…

eess.SP2025

From Token to Rhythm: A Multi-Scale Approach for ECG-Language Pretraining

Fuying Wang, Jiacheng Xu, Lequan Yu

Electrocardiograms (ECGs) play a vital role in monitoring cardiac health and diagnosing heart diseases. However, traditional deep learning approaches for ECG analysis rely heavily…

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