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The success of Multimodal Large Language Models (MLLMs) in the medical auxiliary field shows great potential, allowing patients to engage in conversations using physiological signal data.
Publicly available clinical BERT embeddings
Alsentzer, E.; Murphy, J. R.; Boag, W.; Weng, W.-H.; Jin, D.; Naumann, T.; and McDermott, M. 2019 · 1904
Earlier work this paper cites.
Bleu: a method for automatic evaluation of machine translation
Papineni, K.; Roukos, S.; Ward, T.; and Zhu, W.-J. 2002 · 2002
Earlier work this paper cites.
Arrhythmia Recognition: The Art of Interpretation
Miller, G. T.; and Garcia, T. B. 2003 · 2003
Earlier work this paper cites.
The Washington Manual Cardiology Subspecialty Consult
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Earlier work this paper cites.
ROUGE: A Package for Automatic Evaluation of Summaries
Lin, C.-Y. 2004 · 2004
Earlier work this paper cites.
Recommendations for the standardization and interpretation of the electrocardiogram
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Earlier work this paper cites.
Do your patients trust you?: a sociological understanding of the implications of patient mistrust in healthcare professionals
Meyer, S. B.; and Ward, P. R. 2008 · 2008
Earlier work this paper cites.
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Earlier work this paper cites.
Meteor 1.3: Automatic metric for reliable optimization and evaluation of machine translation systems
Denkowski, M.; and Lavie, A. 2011 · 2011
Earlier work this paper cites.
SCP-ECG V3. 0: An enhanced standard communication protocol for computer-assisted electrocardiography
Rubel, P.; Pani, D.; Schloegl, A.; Fayn, J.; Badilini, F.; Macfarlane, P. W.; and Varri, A. 2016 · 2016
Earlier work this paper cites.
The ECG In Practice
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Earlier work this paper cites.
Attention is All you Need
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Earlier work this paper cites.
Manual of Cardiovascular Medicine
Griffin, B. P. 2018 · 2018
Earlier work this paper cites.
An open access database for evaluating the algorithms of electrocardiogram rhythm and morphology abnormality detection
Liu, F.; Liu, C.; Zhao, L.; Zhang, X.; Wu, X.; Xu, X.; Liu, Y.; Ma, C.; Wei, S.; He, Z.; et al. 2018 · 2018
Earlier work this paper cites.
The ECG Made Easy
Hampton, J.; and Hampton, J. 2019 · 2019
Earlier work this paper cites.
Medical Student Survival Skills: ECG
Jevon, P.; and Gupta, J. 2019 · 2019
Earlier work this paper cites.
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Rajbhandari, S.; Rasley, J.; Ruwase, O.; and He, Y. 2020 · 2020
Earlier work this paper cites.
PTB-XL, a large publicly available electrocardiography dataset
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Earlier work this paper cites.
Optimal multi-stage arrhythmia classification approach
Zheng, J.; Chu, H.; Struppa, D.; Zhang, J.; Yacoub, S. M.; El-Askary, H.; Chang, A.; Ehwerhemuepha, L.; Abudayyeh, I.; Barrett, A.; et al. 2020 · 2020
Earlier work this paper cites.
Exploring simple siamese representation learning
Chen, X.; and He, K. 2021 · 2021
Earlier work this paper cites.
An empirical study of training self-supervised vision transformers
Chen, X.; Xie, S.; and He, K. 2021 · 2021
Earlier work this paper cites.
Lora: Low-rank adaptation of large language models
Hu, E. J.; Shen, Y.; Wallis, P.; Allen-Zhu, Z.; Li, Y.; Wang, S.; Wang, L.; and Chen, W. 2021 · 2021
Earlier work this paper cites.
Align before Fuse: Vision and Language Representation Learning with Momentum Distillation
Li, J.; Selvaraju, R. R.; Gotmare, A. D.; Joty, S.; Xiong, C.; and Hoi, S. 2021 · 2021
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NeuroKit2: A Python toolbox for neurophysiological signal processing
Makowski, D.; Pham, T.; Lau, Z. J.; Brammer, J. C.; Lespinasse, F.; Pham, H.; Schölzel, C.; and Chen, S. H. A. 2021 · 2021
Cited alongside, same era.
Learning transferable visual models from natural language supervision
Radford, A.; Kim, J. W.; Hallacy, C.; Ramesh, A.; Goh, G.; Agarwal, S.; Sastry, G.; Askell, A.; Mishkin, P.; Clark, J.; et al. 2021 · 2021
Cited alongside, same era.
ECG Workout: Exercises in Arrhythmia Interpretation
Huff, J., ed. 2022 · 2022
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A large-scale multi-label 12-lead electrocardiogram database with standardized diagnostic statements
Liu, H.; Chen, D.; Chen, D.; Zhang, X.; Li, H.; Bian, L.; Shu, M.; and Wang, Y. 2022 · 2022
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Judging LLM-as-a-judge with MT-Bench and Chatbot Arena
Zheng, L.; Chiang, W.-L.; Sheng, Y.; Zhuang, S.; Wu, Z.; Zhuang, Y.; Lin, Z.; Li, Z.; Li, D.; Xing, E. P.; Zhang, H.; Gonzalez, J. E.; and Stoica, I. 2023 · 2023
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Interpretable Pre-Trained Transformers for Heart Time-Series Data
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From Local to Global: A Graph RAG Approach to Query-Focused Summarization
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LinkBERT: Pretraining Language Models with Document Links
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CoCa: Contrastive Captioners are Image-Text Foundation Models
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Contrastive Learning of Medical Visual Representations from Paired Images and Text
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A large scale 12-lead electrocardiogram database for arrhythmia study (version 1.0.0)
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Use of Artificial Intelligence Chatbots in Interpretation of Pathology Reports
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The Limits of Fair Medical Imaging AI in Real-World Generalization
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Knowledge-Driven AI-Generated Data for Accurate and Interpretable Breast Ultrasound Diagnoses
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A Survey of Large Language Models in Medicine: Progress, Application, and Challenge
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