Výsledky vyhledávání - "Liang, Shunpan"

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Medication Recommendation via Dual Molecular Modalities and Multi-Step Enhancement

Autor: Mu, Shi, Li, Chen, Li, Xiang, Liang, Shunpan

Existing works based on molecular knowledge neglect the 3D geometric structure of molecules and fail to learn the high-dimensional information of medications, leading to structural confusion. Additionally, it does not extract key substructures from a

Externí odkaz: http://arxiv.org/abs/2405.20358

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CausalMed: Causality-Based Personalized Medication Recommendation Centered on Patient health state

Autor: Li, Xiang, Liang, Shunpan, Lei, Yu, Li, Chen, Hou, Yulei, Ma, Tengfei

Medication recommendation systems are developed to recommend suitable medications tailored to specific patient. Previous researches primarily focus on learning medication representations, which have yielded notable advances. However, these methods ar

Externí odkaz: http://arxiv.org/abs/2404.12228

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Knowledge-Aware Multi-Intent Contrastive Learning for Multi-Behavior Recommendation

Autor: Liang, Shunpan, Zhao, Junjie, Li, Chen, Lei, Yu

Multi-behavioral recommendation optimizes user experiences by providing users with more accurate choices based on their diverse behaviors, such as view, add to cart, and purchase. Current studies on multi-behavioral recommendation mainly explore the

Externí odkaz: http://arxiv.org/abs/2404.11993

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CIDGMed: Causal Inference-Driven Medication Recommendation with Enhanced Dual-Granularity Learning

Autor: Liang, Shunpan, Li, Xiang, Mu, Shi, Li, Chen, Lei, Yu, Hou, Yulei, Ma, Tengfei

Medication recommendation aims to integrate patients' long-term health records to provide accurate and safe medication combinations for specific health states. Existing methods often fail to deeply explore the true causal relationships between diseas

Externí odkaz: http://arxiv.org/abs/2403.00880

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StratMed: Relevance Stratification for Low-resource Medication Recommendation

Autor: Li, Xiang, Liang, Shunpan, Ma, Tengfei, Hou, Yulei

With the growing imbalance between limited medical resources and escalating demands, AI-based clinical tasks have become paramount. Medication recommendation, as a sub-domain, aims to amalgamate longitudinal patient history with medical knowledge, as

Externí odkaz: http://arxiv.org/abs/2308.16781

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