Fetching the paper…
Reading the bibliography…
We propose an approach for adapting the DeBERTa model for electronic health record (EHR) tasks using domain adaptation.
PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals
A L Goldberger, L A Amaral, L Glass, J M Hausdorff, P C Ivanov, R G Mark, J E Mietus, G B Moody, C K Peng, and H E Stanley · 2000
Earlier work this paper cites.
MIMIC-III, a freely accessible critical care database
Alistair E W Johnson, Tom J Pollard, Lu Shen, Li-Wei H Lehman, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, and Roger G Mark · 2016
Earlier work this paper cites.
XGBoost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin · 2016
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Axiomatic attribution for deep networks
Mukund Sundararajan, Ankur Taly, and Qiqi Yan · 2017
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Earlier work this paper cites.
Did the model understand the question?
Pramod Kaushik Mudrakarta, Ankur Taly, Mukund Sundararajan, and Kedar Dhamdhere · 2018
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Yiren Liu, Myle Ott, Nikhil Goyal, Jiajun Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 2019
Earlier work this paper cites.
Do NLP models know numbers? probing numeracy in embeddings
Eric Wallace, Yizhong Wang, Sujian Li, Sameer Singh, and Matt Gardner · 2019
Earlier work this paper cites.
Managing unstructured big data in healthcare system
Hyoun-Joong Kong · 2019
Cited alongside, same era.
Tabular data representation learning with graph convolutional networks
Jie Wang, Xingyu Jiang, and Xiaodong He · 2019
Cited alongside, same era.
Language models are Few-Shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
Cited alongside, same era.
TabTransformer: Tabular data modeling using contextual embeddings
Xin Huang, Ashish Khetan, Milan Cvitkovic, and Zohar Karnin · 2020
Cited alongside, same era.
Graph convolutional networks for multi-omics data integration and disease subtype identification
Yufan Chen, Zhe Shao, Zhiyuan Liu, and Xiaodan Zhu · 2020
Cited alongside, same era.
LIFT: Language-Interfaced Fine-Tuning for Non-Language machine learning tasks
Tuan Dinh, Yuchen Zeng, Ruisu Zhang, Ziqian Lin, Michael Gira, Shashank Rajput, Jy-Yong Sohn, Dimitris Papailiopoulos, and Kangwook Lee · 2022
Later among the works it cites.
TabLLM: Few-shot classification of tabular data with large language models
Stefan Hegselmann, Alejandro Buendia, Hunter Lang, Monica Agrawal, Xiaoyi Jiang, and David Sontag · 2022
Later among the works it cites.
PTab: Using the pre-trained language model for modeling tabular data
Guang Liu, Jie Yang, and Ledell Wu · 2022
Later among the works it cites.
Transfer learning with deep tabular models
Roman Levin, Valeriia Cherepanova, Avi Schwarzschild, Arpit Bansal, C Bayan Bruss, Tom Goldstein, Andrew Gordon Wilson, and Micah Goldblum · 2022
Later among the works it cites.
Developing a deep learning natural language processing algorithm for automated reporting of adverse drug reactions
Christopher McMaster, Julia Chan, David F L Liew, Elizabeth Su, Albert G Frauman, Wendy W Chapman, and Douglas E V Pires · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Captum: A unified and generic model interpretability library for pytorch, 2020
Narine Kokhlikyan, Vivek Miglani, Miguel Martin, Edward Wang, Bilal Alsallakh, Jonathan Reynolds, Alexander Melnikov, Natalia Kliushkina, Carlos Araya, Siqi Yan, and Orion Reblitz-Richardson · 2020
Cited alongside, same era.
Mesh-Transformer-JAX: Model-Parallel Implementation of Transformer Language Model with JAX
Ben Wang · 2021
Cited alongside, same era.
Multitask prompted training enables Zero-Shot task generalization
Victor Sanh, Albert Webson, Colin Raffel, Stephen H Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Teven Le Scao, Arun Raja, Manan Dey, M Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Fevry, Jason Alan Fries, Ryan Teehan, Stella Biderman, Leo Gao, Tali Bers, Thomas Wolf, and Alexander M Rush · 2021
Cited alongside, same era.
Revisiting deep learning models for tabular data
Yury Gorishniy, Ivan Rubachev, Valentin Khrulkov, and Artem Babenko · 2021
Cited alongside, same era.
Deberta: Decoding-enhanced bert with disentangled attention
Pengcheng He, Xiaodong Liu, Jianfeng Gao, and Weizhu Chen
Cited in the paper.
Debertav3: Improving deberta using electra-style pre-training with gradient-disentangled embedding sharing, 2021b
Pengcheng He, Jianfeng Gao, and Weizhu Chen
Cited in the paper.
MIMIC-III clinical database, 2020a
Alistair Johnson, Tom Pollard, and Roger Mark
Cited in the paper.
https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/
PubMed annual baseline · 2022
Later among the works it cites.
MIMIC-IV-ED, 2022
Alistair Johnson, Lucas Bulgarelli, Tom Pollard, Leo Anthony Celi, Roger Mark, and Steven Horng · 2022
Later among the works it cites.
metamimic: analysis of hyperparameter transferability for tabular data using mimic-iv database
Mateusz Grzyb, Zuzanna Trafas, Katarzyna Woznica, and Przemyslaw Biecek · 2023
Closest in time.
Benchmarking emergency department prediction models with machine learning and public electronic health records
Feng Xie, Jun Zhou, Jin Wee Lee, Mingrui Tan, Siqi Li, Logasan S/o Rajnthern, Marcel Lucas Chee, Bibhas Chakraborty, An-Kwok Ian Wong, Alon Dagan, Marcus Eng Hock Ong, Fei Gao, and Nan Liu · 2052
Closest in time.