35 citations · 70 across the 14 of their papers we have counts for
6 papers · 1 filter
GRAM-DTI: adaptive multimodal representation learning for drug target interaction prediction
Feng Jiang, Amina Mollaysa, Hehuan Ma +4
Drug target interaction (DTI) prediction is a cornerstone of computational drug discovery, enabling rational design, repurposing, and mechanistic insights. While deep learning has…
Text-Guided Multi-Instance Learning for Scoliosis Screening via Gait Video Analysis
Haiqing Li, Yuzhi Guo, Feng Jiang +5
Early-stage scoliosis is often difficult to detect, particularly in adolescents, where delayed diagnosis can lead to serious health issues. Traditional X-ray-based methods carry ra…
TRIDENT: Tri-Modal Molecular Representation Learning with Taxonomic Annotations and Local Correspondence
Feng Jiang, Mangal Prakash, Hehuan Ma +6
Molecular property prediction aims to learn representations that map chemical structures to functional properties. While multimodal learning has emerged as a powerful paradigm to l…
Leveraging Gait Patterns as Biomarkers: An attention-guided Deep Multiple Instance Learning Network for Scoliosis Classification
Haiqing Li, Yuzhi Guo, Feng Jiang +3
Scoliosis is a spinal curvature disorder that is difficult to detect early and can compress the chest cavity, impacting respiratory function and cardiac health. Especially for adol…
Histopathology Multi-modal Embedding for Pathology Composed Retrieval
Qifeng Zhou, Wenliang Zhong, Thao M. Dang +4
To overcome the black-box nature of predictive AI and the hallucination risks of generative models, retrieval-based models offer an interpretable, evidence-based paradigm for patho…
GoBERT: Gene Ontology Graph Informed BERT for Universal Gene Function Prediction
Yuwei Miao, Yuzhi Guo, Hehuan Ma +4
Exploring the functions of genes and gene products is crucial to a wide range of fields, including medical research, evolutionary biology, and environmental science. However, disco…