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Medication recommendations aim to generate safe and effective medication sets from health records. However, accurately recommending medications hinges on inferring a patient's latent clinical condition from sparse and noisy observations,…

Information Retrieval · Computer Science 2026-03-20 Xiangxu Zhang , Xiao Zhou , Hongteng Xu , Jianxun Lian

Medication recommendation systems have gained significant attention in healthcare as a means of providing tailored and effective drug combinations based on patients' clinical information. However, existing approaches often suffer from…

Machine Learning · Computer Science 2024-08-13 Zihao Zhao , Yi Jing , Fuli Feng , Jiancan Wu , Chongming Gao , Xiangnan He

A comprehensive pharmaceutical recommendation system was designed based on the patients and drugs features extracted from Drugs.com and Druglib.com. First, data from these databases were combined, and a dataset of patients and drug…

Current medical retrieval benchmarks primarily emphasize lexical or shallow semantic similarity, overlooking the reasoning-intensive demands that are central to clinical decision-making. In practice, physicians often retrieve authoritative…

Information Retrieval · Computer Science 2026-04-07 Xiangxu Zhang , Lei Li , Xiao Zhou , Zheng Liu

Background: Medication review is a structured interview of the patient, performed by the pharmacist and aimed at optimizing drug treatments. In practice, medication review is a long and cognitively-demanding task that requires specific…

Background: Polypharmacy, i.e. taking five drugs or more, is both a public health and an economic issue. Medication reviews are structured interviews of the patient by the community pharmacist, aiming at optimizing the drug treatment and…

With the advancement in the technology sector spanning over every field, a huge influx of information is inevitable. Among all the opportunities that the advancements in the technology have brought, one of them is to propose efficient…

Information Retrieval · Computer Science 2021-12-14 Sudhanshu , Narinder Singh Punn , Sanjay Kumar Sonbhadra , Sonali Agarwal

Medication recommendation using Electronic Health Records (EHR) is challenging due to complex medical data. Current approaches extract longitudinal information from patient EHR to personalize recommendations. However, existing models often…

Machine Learning · Computer Science 2023-09-27 Jiacong Mi , Yi Zu , Zhuoyuan Wang , Jieyue He

The International Classification of Diseases (ICD) serves as a definitive medical classification system encompassing a wide range of diseases and conditions. The primary objective of ICD indexing is to allocate a subset of ICD codes to a…

Computation and Language · Computer Science 2024-05-30 Xindi Wang , Robert E. Mercer , Frank Rudzicz

Predicting medications is a crucial task in many intelligent healthcare systems. It can assist doctors in making informed medication decisions for patients according to electronic medical records (EMRs). However, medication prediction is a…

Artificial Intelligence · Computer Science 2022-05-02 Yang An , Bo Jin , Xiaopeng Wei

Most existing medication recommendation models learn representations for medical concepts based on electronic health records (EHRs) and make recommendations with learnt representations. However, most medications appear in the dataset for…

Machine Learning · Computer Science 2024-02-16 Weicong Tan , Weiqing Wang , Xin Zhou , Wray Buntine , Gordon Bingham , Hongzhi Yin

The Precision Medicine Initiative states that treatments for a patient should take into account not only the patient's disease, but his/her specific genetic variation as well. The vast biomedical literature holds the potential for…

Information Retrieval · Computer Science 2019-04-22 Jiaming Qu , Yue Wang

Medication recommendation targets to provide a proper set of medicines according to patients' diagnoses, which is a critical task in clinics. Currently, the recommendation is manually conducted by doctors. However, for complicated cases,…

Machine Learning · Computer Science 2022-02-21 Rui Wu , Zhaopeng Qiu , Jiacheng Jiang , Guilin Qi , Xian Wu

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

Artificial Intelligence · Computer Science 2023-11-28 Xiang Li , Shunpan Liang , Yulei Hou , Tengfei Ma

Recent advancements in medical entity linking have been applied in the area of scientific literature and social media data. However, with the adoption of telemedicine and conversational agents such as Alexa in healthcare settings, medical…

Computation and Language · Computer Science 2020-10-13 Shaoqing Yuan , Parminder Bhatia , Busra Celikkaya , Haiyang Liu , Kyunghwan Choi

Recommender systems are designed to predict user preferences over collections of items. These systems process users' previous interactions to decide which items should be ranked higher to satisfy their desires. An ensemble recommender…

Information Retrieval · Computer Science 2023-06-23 Alireza Gharahighehi , Celine Vens , Konstantinos Pliakos

Most of the existing medication recommendation models are predicted with only structured data such as medical codes, with the remaining other large amount of unstructured or semi-structured data underutilization. To increase the utilization…

Computation and Language · Computer Science 2024-07-16 Yu-Tzu Lee

Hypertension is a medical condition that is well-established as a risk factor for many major diseases. For example, it can cause alterations in the cardiac structure and function over time that can lead to heart related morbidity and…

Medication recommendation predicts medications for patient visits, but existing methods still face two key challenges. At the model level, traditional drug recommendation methods only predict structured drug codes with limited evidence…

Computation and Language · Computer Science 2026-05-29 Xinyu Wang , Hanwei Wu , Zhenghan Tai , Sicheng Lyu , Qincheng Lu , Ziyu Zhao , Jijun Chi , Jingrui Tian , Xiao-Wen Chang , Ziyang Song

We present HiRMed (Hierarchical RAG-enhanced Medical Test Recommendation), a novel tree-structured recommendation system that leverages Retrieval-Augmented Generation (RAG) for intelligent medical test recommendations. Unlike traditional…

Information Retrieval · Computer Science 2025-01-07 Yahe Yang , Chengyue Huang
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