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Tabular data is often hidden in text, particularly in medical diagnostic reports.
Bayesian inference of individualized treatment effects using multi-task gaussian processes
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K Shailaja, Banoth Seetharamulu, and MA Jabbar · 2018
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Unsupervised cross-lingual representation learning at scale
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Big data in healthcare: management, analysis and future prospects
Sabyasachi Dash, Sushil Kumar Shakyawar, Mohit Sharma, and Sandeep Kaushik · 2019
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Machine learning in energy economics and finance: A review
Hamed Ghoddusi, Germán G Creamer, and Nima Rafizadeh · 2019
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Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 2019
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Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
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Google dataset search by the numbers
Omar Benjelloun, Shiyu Chen, and Natasha Noy · 2020
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Biobert: a pre-trained biomedical language representation model for biomedical text mining
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Deep entity matching with pre-trained language models
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Evaluation of machine learning methods to stroke outcome prediction using a nationwide disease registry
Ching-Heng Lin, Kai-Cheng Hsu, Kory R Johnson, Yang C Fann, Chon-Haw Tsai, YU Sun, Li-Ming Lien, Wei-Lun Chang, Po-Lin Chen, Cheng-Li Lin, et al · 2020
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A natural language processing pipeline of chinese free-text radiology reports for liver cancer diagnosis
Honglei Liu, Yan Xu, Zhiqiang Zhang, Ni Wang, Yanqun Huang, Yanjun Hu, Zhenghan Yang, Rui Jiang, and Hui Chen · 2020
Language models are realistic tabular data generators
Vadim Borisov, Kathrin Seßler, Tobias Leemann, Martin Pawelczyk, and Gjergji Kasneci · 2022
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Towards reasoning in large language models: A survey
Jie Huang and Kevin Chen-Chuan Chang · 2022
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Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings: a systematic review
OT Jones, RN Matin, M van der Schaar, K Prathivadi Bhayankaram, CKI Ranmuthu, MS Islam, D Behiyat, R Boscott, N Calanzani, J Emery, et al · 2022
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Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa · 2022
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Secure and robust machine learning for healthcare: A survey
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Machine learning in geo-and environmental sciences: From small to large scale
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Machine learning for clinical trials in the era of covid-19
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Preparing for the next pandemic: Transfer learning from existing diseases via hierarchical multi-modal bert models to predict covid-19 outcomes
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Model explainability in deep learning based natural language processing
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Natural language processing in medicine: a review
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Interpretable Machine Learning
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Tabular data: Deep learning is not all you need
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Efficient few-shot learning without prompts
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React: Synergizing reasoning and acting in language models
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Attention-based explainability approaches in healthcare natural language processing
Haadia Amjad, Mohammad Shehroz Ashraf, Syed Zoraiz Ali Sherazi, Saad Khan, Muhammad Moazam Fraz, Tahir Hameed, and Syed Ahmad Chan Bukhari · 2023
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The utility of chatgpt as an example of large language models in healthcare education, research and practice: Systematic review on the future perspectives and potential limitations
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