Zobrazeno 1 - 10
of 83
pro vyhledávání: '"Peng, Xueping"'
Next Basket Recommender Systems (NBRs) function to recommend the subsequent shopping baskets for users through the modeling of their preferences derived from purchase history, typically manifested as a sequence of historical baskets. Given their wide
Externí odkaz:
http://arxiv.org/abs/2312.02550
By summarizing longer consumer health questions into shorter and essential ones, medical question answering (MQA) systems can more accurately understand consumer intentions and retrieve suitable answers. However, medical question summarization is ver
Externí odkaz:
http://arxiv.org/abs/2304.07437
Next basket recommender systems (NBRs) aim to recommend a user's next (shopping) basket of items via modeling the user's preferences towards items based on the user's purchase history, usually a sequence of historical baskets. Due to its wide applica
Externí odkaz:
http://arxiv.org/abs/2209.02892
News recommender systems are essential for helping users to efficiently and effectively find out those interesting news from a large amount of news. Most of existing news recommender systems usually learn topic-level representations of users and news
Externí odkaz:
http://arxiv.org/abs/2110.05792
Sequential diagnosis prediction on the Electronic Health Record (EHR) has been proven crucial for predictive analytics in the medical domain. EHR data, sequential records of a patient's interactions with healthcare systems, has numerous inherent char
Externí odkaz:
http://arxiv.org/abs/2109.03069
Autor:
Peng, Xueping, Long, Guodong, Wang, Sen, Jiang, Jing, Clarke, Allison, Schlegel, Clement, Zhang, Chengqi
Healthcare representation learning on the Electronic Health Records is crucial for downstream medical prediction tasks in health informatics. Many NLP techniques, such as RNN and self-attention, have been adapted to learn medical representations from
Externí odkaz:
http://arxiv.org/abs/2107.09288
Electronic health records (EHRs) are longitudinal records of a patient's interactions with healthcare systems. A patient's EHR data is organized as a three-level hierarchy from top to bottom: patient journey - all the experiences of diagnoses and tre
Externí odkaz:
http://arxiv.org/abs/2009.13252
Understanding patients' journeys in healthcare system is a fundamental prepositive task for a broad range of AI-based healthcare applications. This task aims to learn an informative representation that can comprehensively encode hidden dependencies a
Externí odkaz:
http://arxiv.org/abs/2006.10516
Publikováno v:
In Computers and Electrical Engineering September 2023 110
Autor:
Shi, Wei, Liu, Jingjing, Zhu, Ying, Zhao, Lin, Wang, Yonggang, Cheng, Zhaohuan, Peng, Xueping, Shi, Xiaoyan, Yu, Yunbo, He, Hong
Publikováno v:
In Journal of Rare Earths September 2023 41(9):1336-1343