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Pre-trained language models (PLMs) have been the de facto paradigm for most natural language processing (NLP) tasks.
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Overview of the epigenetics and post-translational modifications (epi) task of bionlp shared task 2011
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Overview of the infectious diseases (id) task of bionlp shared task 2011
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Biocause: annotating and analysing causality in the biomedical domain
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Overview of bionlp shared task 2013
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Chemdner: the drugs and chemical names extraction challenge
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Overview of the cancer genetics and pathway curation tasks of bionlp shared task 2013
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An overview of the bioasq large-scale biomedical semantic indexing and question answering competition
G. Tsatsaronis, G. Balikas, P. Malakasiotis, I. Partalas, M. Zschunke, M. R. Alvers, D. Weissenborn, A. Krithara, S. Petridis, D. Polychronopoulos, et al · 2015
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Survey of natural language processing techniques in bioinformatics
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Recognizing question entailment for medical question answering
A. B. Abacha and D. Demner-Fushman · 2016
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Preparing a collection of radiology examinations for distribution and retrieval
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Preparing a collection of radiology examinations for distribution and retrieval
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Gaussian error linear units (gelus)
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Mimic-iii, a freely accessible critical care database
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Biocreative v cdr task corpus: a resource for chemical disease relation extraction
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Squad: 100,000+ questions for machine comprehension of text
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Neural machine translation of rare words with subword units
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Biocreative vi precision medicine track: creating a training corpus for mining protein-protein interactions affected by mutations
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Matchzoo: a toolkit for deep text matching
Y. Fan, L. Pang, J. Hou, J. Guo, Y. Lan, and X. Cheng · 2017
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Capturing the patient’s perspective: a review of advances in natural language processing of health-related text
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Overview of the biocreative vi chemical-protein interaction track
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Imagenet classification with deep convolutional neural networks
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Biosses: a semantic sentence similarity estimation system for the biomedical domain
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Attention is all you need
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin · 2017
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Men also like shopping: reducing gender bias amplification using corpus-level constraints
J. Zhao, T. Wang, M. Yatskar, V. Ordonez, and K.-W. Chang · 2017
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Learning protein sequence embeddings using information from structure
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A discourse-aware attention model for abstractive summarization of long documents
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Bert: pre-training of deep bidirectional transformers for language understanding
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Cas: french corpus with clinical cases
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Unsupervised multimodal representation learning across medical images and reports
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Sentencepiece: A simple and language independent subword tokenizer and detokenizer for neural text processing
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The mythos of model interpretability: in machine learning, the concept of interpretability is both important and slippery
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A corpus with multi-level annotations of patients, interventions and outcomes to support language processing for medical literature
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Emrqa: a large corpus for question answering on electronic medical records
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Radiology objects in context (roco): a multimodal image dataset
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Improving language understanding by generative pre-training
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Lessons from natural language inference in the clinical domain
A. Romanov and C. Shivade · 2018
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Effective use of bidirectional language modeling for transfer learning in biomedical named entity recognition
D. S. Sachan, P. Xie, M. Sachan, and E. P. Xing · 2018
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In-domain context-aware token embeddings improve biomedical named entity recognition
G. Sheikhshab, I. Birol, and A. Sarkar · 2018
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Glue: a multi-task benchmark and analysis platform for natural language understanding
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Clinical information extraction applications: a literature review
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Task-oriented dialogue system for automatic diagnosis
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A broad-coverage challenge corpus for sentence understanding through inference
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Mining electronic health records (ehrs) a survey
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Multi-scale attentive interaction networks for chinese medical question answer selection
S. Zhang, X. Zhang, H. Wang, L. Guo, and S. Liu · 2018
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Clinical concept extraction with contextual word embedding
H. Zhu, I. C. Paschalidis, and A. M. Tahmasebi · 2018
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Overview of the mediqa 2019 shared task on textual inference, question entailment and question answering
A. B. Abacha, C. Shivade, and D. Demner-Fushman · 2019
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Rethinking complex neural network architectures for document classification
A. Adhikari, A. Ram, R. Tang, and J. Lin · 2019
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Pharmaconer: pharmacological substances, compounds and proteins named entity recognition track
A. G. Agirre, M. Marimon, A. Intxaurrondo, O. Rabal, M. Villegas, and M. Krallinger · 2019
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Unified rational protein engineering with sequence-only deep representation learning
E. C. Alley, G. Khimulya, S. Biswas, M. AlQuraishi, and G. M. Church · 2019
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Publicly available clinical bert embeddings
E. Alsentzer, J. Murphy, W. Boag, W.-H. Weng, D. Jindi, T. Naumann, and M. McDermott · 2019
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Publicly available clinical Bert embeddings
E. Alsentzer, J. R. Murphy, W. Boag, W. Weng, D. Jin, T. Naumann, and M. B. A. McDermott · 2019
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Scibert: A pretrained language model for scientific text
I. Beltagy, K. Lo, and A. Cohan · 2019
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Learning protein sequence embeddings using information from structure
T. Bepler and B. Berger · 2019
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Evaluation of five sentence similarity models on electronic medical records
Q. Chen, J. Du, S. Kim, W. J. Wilbur, and Z. Lu · 2019
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Biosentvec: creating sentence embeddings for biomedical texts
Q. Chen, Y. Peng, and Z. Lu · 2019
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A general approach for improving deep learning-based medical relation extraction using a pre-trained model and fine-tuning
T. Chen, M. Wu, and H. Li · 2019
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Pre-training with whole word masking for chinese bert
Y. Cui, W. Che, T. Liu, B. Qin, Z. Yang, S. Wang, and G. Hu · 2019
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Bert: pre-training of deep bidirectional transformers for language understanding
J. Devlin, M. Chang, K. Lee, and K. Toutanova · 2019
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Extracting symptoms and their status from clinical conversations
N. Du, K. Chen, A. Kannan, L. Tran, Y. Chen, and I. Shafran · 2019
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End-to-end named entity recognition and relation extraction using pre-trained language models
J. Giorgi, X. Wang, N. Sahar, W. Y. Shin, G. D. Bader, and B. Wang · 2019
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Modeling aspects of the language of life through transfer-learning protein sequences
M. Heinzinger, A. Elnaggar, Y. Wang, C. Dallago, D. Nechaev, F. Matthes, and B. Rost · 2019
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Modeling the language of life–deep learning protein sequences
M. Heinzinger, A. Elnaggar, Y. Wang, C. Dallago, D. Nechaev, F. Matthes, and B. Rost · 2019
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Clinicalbert: modeling clinical notes and predicting hospital readmission
K. Huang, J. Altosaar, and R. Ranganath · 2019
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Clinical xlnet: modeling sequential clinical notes and predicting prolonged mechanical ventilation
K. Huang, A. Singh, S. Chen, E. Moseley, C. ying Deng, N. George, and C. Lindvall · 2019
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Probing biomedical embeddings from language models
Q. Jin, B. Dhingra, W. Cohen, and X. Lu · 2019
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Pubmedqa: a dataset for biomedical research question answering
Q. Jin, B. Dhingra, Z. Liu, W. Cohen, and X. Lu · 2019
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Proceedings of the 5th workshop on bionlp open shared tasks
K. Jin-Dong, N. Claire, B. Robert, and D. Louise · 2019
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Mimic-cxr, a de-identified publicly available database of chest radiographs with free-text reports
A. E. Johnson, T. J. Pollard, S. J. Berkowitz, N. R. Greenbaum, M. P. Lungren, C.-y. Deng, R. G. Mark, and S. Horng · 2019
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Mimic-cxr-jpg, a large publicly available database of labeled chest radiographs
A. E. Johnson, T. J. Pollard, N. R. Greenbaum, M. P. Lungren, C.-y. Deng, Y. Peng, Z. Lu, R. G. Mark, S. J. Berkowitz, and S. Horng · 2019
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How to pre-train your model? comparison of different pre-training models for biomedical question answering
S. Kamath, B. Grau, and Y. Ma · 2019
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A survey of word embeddings for clinical text
F. K. Khattak, S. Jeblee, C. Pou-Prom, M. Abdalla, C. Meaney, and F. Rudzicz · 2019
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Critical assessment of methods of protein structure prediction (casp)—round xiii
A. Kryshtafovych, T. Schwede, M. Topf, K. Fidelis, and J. Moult · 2019
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Albert: a lite bert for self-supervised learning of language representations
Z. Lan, M. Chen, S. Goodman, K. Gimpel, P. Sharma, and R. Soricut · 2019
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M. Lewis, Y. Liu, N. Goyal, M. Ghazvininejad, A. Mohamed, O. Levy, V. Stoyanov, and L. Zettlemoyer · 2019
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Fine-tuning bidirectional encoder representations from transformers (bert)–based models on large-scale electronic health record notes: an empirical study
F. Li, Y. Jin, W. Liu, B. P. S. Rawat, P. Cai, and H. Yu · 2019
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Visualbert: A simple and performant baseline for vision and language
L. H. Li, M. Yatskar, D. Yin, C.-J. Hsieh, and K.-W. Chang · 2019
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A bert-based universal model for both within-and cross-sentence clinical temporal relation extraction
C. Lin, T. Miller, D. Dligach, S. Bethard, and G. Savova · 2019
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Enhancing dialogue symptom diagnosis with global attention and symptom graph
X. Lin, X. He, Q. Chen, H. Tou, Z. Wei, and T. Chen · 2019
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Roberta: a robustly optimized bert pretraining approach
Y. Liu, M. Ott, N. Goyal, J. Du, M. Joshi, D. Chen, O. Levy, M. Lewis, L. Zettlemoyer, and V. Stoyanov · 2019
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Self-supervised contextual language representation of radiology reports to improve the identification of communication urgency, 2019
X. Meng, C. H. Ganoe, R. T. Sieberg, Y. Y. Cheung, and S. Hassanpour · 2019
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Crowdbreaks: tracking health trends using public social media data and crowdsourcing
M. M. Müller and M. Salathé · 2019
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Results of the seventh edition of the bioasq challenge
A. Nentidis, K. Bougiatiotis, A. Krithara, and G. Paliouras · 2019
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Transfer learning in biomedical natural language processing: an evaluation of bert and elmo on ten benchmarking datasets
Y. Peng, S. Yan, and Z. Lu · 2019
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Language models as knowledge bases?
F. Petroni, T. Rocktäschel, S. Riedel, P. Lewis, A. Bakhtin, Y. Wu, and A. Miller · 2019
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Evaluating protein transfer learning with tape
R. Rao, N. Bhattacharya, N. Thomas, Y. Duan, X. Chen, J. Canny, P. Abbeel, and Y. S. Song · 2019
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Pre-training of graph augmented transformers for medication recommendation
J. Shang, T. Ma, C. Xiao, and J. Sun · 2019
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Perturbed masking: parameter-free probing for analyzing and interpreting bert
Z. Wu, Y. Chen, B. Kao, and Q. Liu · 2020
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Generative adversarial regularized mutual information policy gradient framework for automatic diagnosis
Y. Xia, J. Zhou, Z. Shi, C. Lu, and H. Huang · 2020
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Medical knowledge-enriched textual entailment framework
S. Yadav, V. Pallagani, and A. Sheth · 2020
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On the generation of medical dialogues for covid-19
W. Yang, G. Zeng, B. Tan, Z. Ju, S. Chakravorty, X. He, S. Chen, X. Yang, Q. Wu, Z. Yu, et al · 2020
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Clinical concept extraction using transformers
X. Yang, J. Bian, W. R. Hogan, and Y. Wu · 2020
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alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
S. Sharma and R. D. J. au2 · 2019
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Incorporating domain knowledge into medical NLI using knowledge graphs
S. Sharma, B. Santra, A. Jana, S. Tokala, N. Ganguly, and P. Goyal · 2019
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Enhancing clinical concept extraction with contextual embeddings
Y. Si, J. Wang, H. Xu, and K. Roberts · 2019
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How to fine-tune bert for text classification?
C. Sun, X. Qiu, Y. Xu, and X. Huang · 2019
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Mitigating gender bias in natural language processing: literature review
T. Sun, A. Gaut, S. Tang, Y. Huang, M. ElSherief, J. Zhao, D. Mirza, E. Belding, K.-W. Chang, and W. Y. Wang · 2019
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Lxmert: Learning cross-modality encoder representations from transformers
H. Tan and M. Bansal · 2019
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Biomedical relation extraction with pre-trained language representations and minimal task-specific architecture
A. Thillaisundaram and T. Togia · 2019
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X. Yang, X. He, H. Zhang, Y. Ma, J. Bian, and Y. Wu · 2020
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Xlnet: generalized autoregressive pretraining for language understanding, 2020
Z. Yang, Z. Dai, Y. Yang, J. Carbonell, R. Salakhutdinov, and Q. V. Le · 2020
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Coder: knowledge infused cross-lingual medical term embedding for term normalization
Z. Yuan, Z. Zhao, and S. Yu · 2020
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Big bird: transformers for longer sequences
M. Zaheer, G. Guruganesh, A. Dubey, J. Ainslie, C. Alberti, S. Ontanon, P. Pham, A. Ravula, Q. Wang, L. Yang, et al · 2020
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Meddialog: a large-scale medical dialogue dataset
G. Zeng, W. Yang, Z. Ju, Y. Yang, S. Wang, R. Zhang, M. Zhou, J. Zeng, X. Dong, R. Zhang, et al · 2020
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Hurtful words: quantifying biases in clinical contextual word embeddings
H. Zhang, A. X. Lu, M. Abdalla, M. McDermott, and M. Ghassemi · 2020
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Conceptualized representation learning for chinese biomedical text mining
N. Zhang, Q. Jia, K. Yin, L. Dong, F. Gao, and N. Hua · 2020
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Multi-stage pre-training for low-resource domain adaptation, 2020
R. Zhang, R. G. Reddy, M. A. Sultan, V. Castelli, A. Ferritto, R. Florian, E. S. Kayi, S. Roukos, A. Sil, and T. Ward · 2020
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Ternarybert: distillation-aware ultra-low bit bert, 2020
W. Zhang, L. Hou, Y. Yin, L. Shang, X. Chen, X. Jiang, and Q. Liu · 2020
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Contrastive learning of medical visual representations from paired images and text
Y. Zhang, H. Jiang, Y. Miura, C. D. Manning, and C. P. Langlotz · 2020
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Mie: a medical information extractor towards medical dialogues
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Abioner: a bert-based model for arabic biomedical named-entity recognition
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Highly accurate protein structure prediction with alphafold
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Ammu–a survey of transformer-based biomedical pretrained language models
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Learning transferable visual models from natural language supervision
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Fine-tuning large neural language models for biomedical natural language processing
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Adapting pretrained vision-language foundational models to medical imaging domains
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