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The integration of multimodal Electronic Health Records (EHR) data has significantly advanced clinical predictive capabilities.
The mystery of the Z-score
Alexander E Curtis, Tanya A Smith, Bulat A Ziganshin, and John A Elefteriades. 2016 · 2016
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GRAM: graph-based attention model for healthcare representation learning. In Proceedings of the 23rd ACM SIGKDD international conference on knowledge discovery and data mining . 787–795
Edward Choi, Mohammad Taha Bahadori, Le Song, Walter F Stewart, and Jimeng Sun. 2017 · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2017 · 2017
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Tensor fusion network for multimodal sentiment analysis
Amir Zadeh, Minghai Chen, Soujanya Poria, Erik Cambria, and Louis-Philippe Morency. 2017 · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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Kame: Knowledge-based attention model for diagnosis prediction in healthcare. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management . 743–752
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Deep learning for healthcare: review, opportunities and challenges
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Scalable and accurate deep learning with electronic health records
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Aming Wu and Yahong Han. 2018 · 2018
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Pytorch: An imperative style, high-performance deep learning library
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, et al · 2020
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Integrating multimodal information in large pretrained transformers. In Proceedings of the conference. Association for Computational Linguistics. Meeting , Vol. 2020. NIH Public Access, 2359
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Predicting in-hospital mortality by combining clinical notes with time-series data. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 . 4026–4031
Iman Deznabi, Mohit Iyyer, and Madalina Fiterau. 2021 · 2021
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Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare. In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21 , Zhi-Hua Zhou (Ed.). International Joint Conferences on Artificial Intelligence Organization, 3529–3535
Chang Lu, Chandan K Reddy, Prithwish Chakraborty, Samantha Kleinberg, and Yue Ning. 2021 · 2021
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How to leverage multimodal EHR data for better medical predictions?
Bo Yang and Lijun Wu. 2021 · 2021
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Medpath: Augmenting health risk prediction via medical knowledge paths. In Proceedings of the Web Conference 2021 . 1397–1409
Muchao Ye, Suhan Cui, Yaqing Wang, Junyu Luo, Cao Xiao, and Fenglong Ma. 2021a · 2021
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MedML: fusing medical knowledge and machine learning models for early pediatric COVID-19 hospitalization and severity prediction
Junyi Gao, Chaoqi Yang, Joerg Heintz, Scott Barrows, Elise Albers, Mary Stapel, Sara Warfield, Adam Cross, and Jimeng Sun. 2022 · 2022
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An empirical evaluation of sampling methods for the classification of imbalanced data
Misuk Kim and Kyu-Baek Hwang. 2022 · 2022
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Patient Health Representation Learning via Correlational Sparse Prior of Medical Features
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Graph-text multi-modal pre-training for medical representation learning. In Conference on Health, Inference, and Learning . PMLR, 261–281
The shaky foundations of large language models and foundation models for electronic health records
Michael Wornow, Yizhe Xu, Rahul Thapa, Birju Patel, Ethan Steinberg, Scott Fleming, Michael A Pfeffer, Jason Fries, and Nigam H Shah. 2023 · 2023
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Efficient Streaming Language Models with Attention Sinks
Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, and Mike Lewis. 2023 · 2023
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VecoCare: Visit Sequences-Clinical Notes Joint Learning for Diagnosis Prediction in Healthcare Data. In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI-23 , Edith Elkind (Ed.). International Joint Conferences on Artificial Intelligence Organization, 4921–4929
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KerPrint: local-global knowledge graph enhanced diagnosis prediction for retrospective and prospective interpretations. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 37. 5357–5365
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Sungjin Park, Seongsu Bae, Jiho Kim, Tackeun Kim, and Edward Choi. 2022 · 2022
Cited alongside, same era.
M3Care: Learning with Missing Modalities in Multimodal Healthcare Data. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (Washington DC, USA) (KDD ’22) . Association for Computing Machinery, New York, NY, USA, 2418–2428
Chaohe Zhang, Xu Chu, Liantao Ma, Yinghao Zhu, Yasha Wang, Jiangtao Wang, and Junfeng Zhao. 2022 · 2022
Cited alongside, same era.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
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Jinze Bai, Shuai Bai, Yunfei Chu, Zeyu Cui, Kai Dang, Xiaodong Deng, Yang Fan, Wenbin Ge, Yu Han, Fei Huang, et al · 2023
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Kinet: Incorporating relevant facts into knowledge-grounded dialog generation
Jiaqi Bai, Ze Yang, Jian Yang, Hongcheng Guo, and Zhoujun Li. 2023c · 2023
Cited alongside, same era.
Building a knowledge graph to enable precision medicine
Payal Chandak, Kexin Huang, and Marinka Zitnik. 2023 · 2023
Cited alongside, same era.
Redefining Digital Health Interfaces with Large Language Models
Fergus Imrie, Paulius Rauba, and Mihaela van der Schaar. 2023 · 2023
Cited alongside, same era.
Kwanhyung Lee, Soojeong Lee, Sangchul Hahn, Heejung Hyun, Edward Choi, Byungeun Ahn, and Joohyung Lee. 2023 · 2023
Cited alongside, same era.
Kai Yang, Yongxin Xu, Peinie Zou, Hongxin Ding, Junfeng Zhao, Yasha Wang, and Bing Xie. 2023 · 2023
Later among the works it cites.
Siren’s song in the ai ocean: A survey on hallucination in large language models
Yue Zhang, Yafu Li, Leyang Cui, Deng Cai, Lemao Liu, Tingchen Fu, Xinting Huang, Enbo Zhao, Yu Zhang, Yulong Chen, et al · 2023
Later among the works it cites.
Infusing internalized knowledge of language models into hybrid prompts for knowledgeable dialogue generation
Jiaqi Bai, Zhao Yan, Shun Zhang, Jian Yang, Hongcheng Guo, and Zhoujun Li. 2024 · 2024
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Jianlv Chen and Shitao Xiao. 2024 · 2024
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DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
DeepSeek-AI. 2024 · 2024
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A Comprehensive Benchmark for COVID-19 Predictive Modeling Using Electronic Health Records in Intensive Care
Junyi Gao, Yinghao Zhu, Wenqing Wang, Guiying Dong, Wen Tang, Hao Wang, Yasha Wang, Ewen M Harrison, and Liantao Ma. 2024 · 2024
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GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphs. In The Twelfth International Conference on Learning Representations
Pengcheng Jiang, Cao Xiao, Adam Richard Cross, and Jimeng Sun. 2024 · 2024
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Weibin Liao, Yinghao Zhu, Zixiang Wang, Xu Chu, Yasha Wang, and Liantao Ma. 2024 · 2024
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A Closer Look at AUROC and AUPRC under Class Imbalance
Matthew B. A. McDermott, Lasse Hyldig Hansen, Haoran Zhang, Giovanni Angelotti, and Jack Gallifant. 2024 · 2024
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Prompt engineering
OpenAI. 2023 · 2024
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ResLoRA: Identity Residual Mapping in Low-Rank Adaption
Shuhua Shi, Shaohan Huang, Minghui Song, Zhoujun Li, Zihan Zhang, Haizhen Huang, Furu Wei, Weiwei Deng, Feng Sun, and Qi Zhang. 2024 · 2024
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Recent Advances in Predictive Modeling with Electronic Health Records
Jiaqi Wang, Junyu Luo, Muchao Ye, Xiaochen Wang, Yuan Zhong, Aofei Chang, Guanjie Huang, Ziyi Yin, Cao Xiao, Jimeng Sun, and Fenglong Ma. 2024 · 2024
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Yinghao Zhu, Junyi Gao, Zixiang Wang, Weibin Liao, Xiaochen Zheng, Lifang Liang, Yasha Wang, Chengwei Pan, Ewen M Harrison, and Liantao Ma. 2024a · 2024
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