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原创 MedRAG: Enhancing Retrieval-augmented Generation with Knowledge Graph-Elicited Reasoning for Healthc

Retrieval-augmented generation (RAG) is a well-suited technique for retrieving privacy-sensitive Electronic Health Records (EHR).

2025-03-28 10:40:03 699

原创 Debiased, Longitudinal and Coordinated Drug Recommendation through Multi-Visit Clinic Records

AI-empowered drug recommendation has become an important task in healthcare research areas, which offers an additional perspective to assist human doctors with more accurate and more efficient drug prescriptions.

2025-02-14 17:51:44 807

原创 Large Language Model Distilling Medication Recommendation Model

Abstract—The recommendation of medication is a vital aspect of intelligent healthcare systems, as it involves prescribing the most suitable drugs based on a patient’s specific health needs. Unfortunately, many sophisticated models currently in use tend to

2025-02-14 15:41:10 1659

原创 SMR: Medical Knowledge Graph Embedding for Safe Medicine Recommendation

Most of the existing medicine recommendation systems that are mainly based on electronic medical records (EMRs) are significantly assisting doctors to make better clinical decisions benefiting both patients and caregivers.

2025-01-15 18:33:36 208

原创 PREMIER-Personalizing Medication Recommendation with a Graph-Based Approach

The broad adoption of electronic health records (EHRs) has led to vast amounts of data being accumulated on a patient’s history, diagnosis, prescriptions, and lab tests.

2025-01-15 18:30:15 126

原创 CompNet-Order-free Medicine Combination Prediction with Graph Convolutional Reinforcement Learning

Medicine Combination Prediction (MCP) based on Electronic Health Record (EHR) can assist doctors to prescribe medicines for complex patients.

2025-01-15 18:23:16 107

原创 Dual Memory Neural Computer for Asynchronous Two-view Sequential Learning

One of the core tasks in multi-view learning is to capture relations among views.

2025-01-14 15:51:55 122

原创 Bias and Debias in Recommender System: A Survey and Future Directions

While recent years have witnessed a rapid growth of research papers on recommender system (RS), most of the papers focus on inventing machine learning models to better fit user behavior data. However, user behavior data is observational rather than experim

2025-01-14 15:48:29 104

原创 REFINE: A Fine-Grained Medication Recommendation System Using Deep Learning and Personalized Drug In

Patients with co-morbidities often require multiple medications to manage their conditions.

2025-01-14 15:45:43 347

原创 MICRON-Change Matters: Medication Change Prediction with Recurrent Residual Networks

Deep learning is revolutionizing predictive healthcare, including recommending medications to patients with complex health conditions.

2025-01-14 15:44:31 372

原创 4SDrug: Symptom-based Set-to-set Small and Safe Drug Recommendation

Drug recommendation is an important task of AI for healthcare. To recommend proper drugs, existing methods rely on various clinical records (e.g., diagnosis and procedures), which are commonly found in data such as electronic health records (EHRs).

2025-01-14 15:42:44 404

原创 MoleRec: Combinatorial Drug Recommendation with Substructure-Aware Molecular Representation Learnin

Combinatorial drug recommendation involves recommending a personalized combination of medication (drugs) to a patient over his/her longitudinal history, which essentially aims at solving a combinatorial optimization problem that pursues high accuracy under

2025-01-13 13:33:08 182

原创 COGNet:Conditional Generation Net for Medication Recommendation

Medication recommendation targets to provide a proper set of medicines according to patients’ diagnoses, which is a critical task in clinics.

2025-01-13 12:56:46 1091

原创 SafeDrug: Dual Molecular Graph Encoders for Recommending Effective and Safe Drug Combinations

Medication recommendation is an essential task of AI for healthcare. Existing works focused on recommending drug combinations for patients with complex health conditions solely based on their electronic health records.

2025-01-13 11:05:33 874

原创 LEAP: Learning to Prescribe Effective and Safe Treatment Combinations for Multimorbidity

Managing patients with complex multimorbidity has long been recognized as a difficult problem due to complex disease and medication dependencies and the potential risk of adverse drug interactions.

2025-01-12 14:07:20 278

原创 RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism

准确性和可解释性是成功预测模型的两个主要特征。通常，为了追求准确性，人们不得不选择像循环神经网络（RNN）这样复杂的黑箱模型，而如果选择准确性稍低但更具可解释性的传统模型，如逻辑回归。这种权衡在医学领域带来了挑战，因为在医学中准确性和可解释性都很重要。我们通过开发适用于电子健康记录（EHR）数据的逆时间注意力模型（RETAIN）来应对这一挑战。

2025-01-11 22:04:32 871

原创 G-Bert Pre-training of Graph Augmented Transformers for Medication Recommendation

Medication recommendation is an important healthcare application. It is commonly formulated as a temporal prediction task.

2025-01-11 19:48:16 704

原创 GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination

深度学习的最新进展正在使医疗保健领域发生革命性变化，包括为药物推荐提供解决方案，特别是为健康状况复杂的患者推荐联合用药。

2025-01-11 13:43:42 949

原创 Deep Learning for Medication Recommendation: A Systematic Survey

Making medication prescriptions in response to the patient’s diagnosis is a challenging task. The number of pharmaceutical companies, their inventory of medicines, and the recommended dosage confront a doctor with the well-known problem of information an

2024-12-30 16:33:20 729

原创 KGAT: Knowledge Graph Attention Network for Recommendation

To provide more accurate, diverse, and explainable recommendation, it is compulsory to go beyond modeling user-item interactions and take side information into account

2024-12-19 16:09:19 666

原创 DKN: Deep Knowledge-Aware Network for News Recommendation

Online news recommender systems aim to address the information explosion of news and make personalized recommendation for users. In general, news language is highly condensed, full of knowledge entities and common sense.

2024-12-19 16:01:44 814

原创 BPR: Bayesian Personalized Ranking from Implicit Feedback

Item recommendation is the task of predicting a personalized ranking on a set of items (e.g. websites, movies, products).

2024-12-17 20:07:51 989

原创 Knowledge Graph Convolutional Networks for Recommender

To alleviate sparsity and cold start problem of collaborative filtering based recommender systems, researchers and engineers usually collect attributes of users and items, and design delicate algorithms to exploit these additional information.

2024-12-16 21:30:26 1879

原创 Neural Collaborative Filtering∗

In recent years, deep neural networks have yielded immense success on speech recognition, computer vision and natural language processing.

2024-12-16 18:40:28 1081

原创 LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation

However, we empirically find that the two most common designs in GCNs — feature transformation and nonlinear activation — contribute little to the performance of collaborative filtering. Even worse, including them adds to the difficulty of training and deg

2024-12-16 09:23:25 1104

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