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Cancer prognosis is a critical task that involves predicting patient outcomes and survival rates.
Comprehensive genomic characterization defines human glioblastoma genes and core pathways
Cancer Genome Atlas Research Network Tissue source sites: Duke University Medical School McLendon Roger 1 Friedman Allan 2 Bigner Darrell 1, Emory University Van Meir Erwin G. 3 4 5 Brat Daniel J. 5 6 M. Mastrogianakis Gena 3 Olson Jeffrey J. 3 4 5, Henry Ford Hospital Mikkelsen Tom 7 Lehman Norman 8, MD Anderson Cancer Center Aldape Ken 9 Alfred Yung WK 10 Bogler Oliver 11, University of California San Francisco VandenBerg Scott 12 Berger Mitchel 13 Prados Michael 13, et al · 2008
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Trends in cancer prognosis in a population-based cohort survey: can recent advances in cancer therapy affect the prognosis?
Eri Kawabata-Shoda, Hadrien Charvat, Ai Ikeda, Manami Inoue, Norie Sawada, Motoki Iwasaki, Shizuka Sasazuki, Taichi Shimazu, Taiki Yamaji, Hiromichi Kimura, et al · 2015
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Machine learning applications in cancer prognosis and prediction
Konstantina Kourou, Themis P Exarchos, Konstantinos P Exarchos, Michalis V Karamouzis, and Dimitrios I Fotiadis · 2015
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Attention is all you need
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Bert: Pre-training of deep bidirectional transformers
Jacob Devlin et al · 2018
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Multimodal transformer for unaligned multimodal language sequences
Yao-Hung Hubert Tsai, Shaojie Bai, Paul Pu Liang, J Zico Kolter, Louis-Philippe Morency, and Ruslan Salakhutdinov · 2019
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Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks
Jiasen Lu et al · 2019
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Lxmert: Learning cross-modality encoder representations from transformers
Hao Tan and Mohit Bansal · 2019
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Language models are unsupervised multitask learners
Alec Radford et al · 2019
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The application of deep learning in cancer prognosis prediction
Wan Zhu, Longxiang Xie, Jianye Han, and Xiangqian Guo · 2020
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Clinical applications of continual learning machine learning
Cecilia S Lee and Aaron Y Lee · 2020
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Integrating multimodal information in large pretrained transformers
Wasifur Rahman, Md Kamrul Hasan, Sangwu Lee, Amir Zadeh, Chengfeng Mao, Louis-Philippe Morency, and Ehsan Hoque · 2020
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Language models are few-shot learners
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Scaling laws for neural language models
Jared Kaplan et al · 2020
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Global cancer statistics 2020: Globocan estimates of incidence and mortality worldwide for 36 cancers in 185 countries
Hyuna Sung, Jacques Ferlay, Rebecca L Siegel, Mathieu Laversanne, Isabelle Soerjomataram, Ahmedin Jemal, and Freddie Bray · 2021
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Learning transferable visual models from natural language supervision
Alec Radford et al · 2021
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On the opportunities and risks of foundation models
Rishi Bommasani et al · 2021
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Learning transferable visual models from natural language supervision
Alec Radford et al · 2021
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Zero-shot text-to-image generation
Aditya Ramesh et al · 2021
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Highly accurate protein structure prediction with alphafold
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On the dangers of stochastic parrots
Emily Bender et al · 2021
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A continual learning survey: Defying forgetting in classification tasks
Matthias De Lange, Rahaf Aljundi, Marc Masana, Sarah Parisot, Xu Jia, Aleš Leonardis, Gregory Slabaugh, and Tinne Tuytelaars · 2021
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Overcoming catastrophic forgetting in incremental few-shot learning by finding flat minima
Guangyuan Shi, Jiaxin Chen, Wenlong Zhang, Li-Ming Zhan, and Xiao-Ming Wu · 2021
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Flamingo: a visual language model for few-shot learning
Jean-Baptiste Alayrac et al · 2022
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Multi-modal medical image diagnosis
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Advances in multimodal human-computer interaction
Dongwon Kim et al · 2022
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Mbfusion: Multi-modal balanced fusion and multi-task learning for cancer diagnosis and prognosis
Ziye Zhang, Wendong Yin, Shijin Wang, Xiaorou Zheng, and Shoubin Dong · 2024
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A pathology foundation model for cancer diagnosis and prognosis prediction
Xiyue Wang, Junhan Zhao, Eliana Marostica, Wei Yuan, Jietian Jin, Jiayu Zhang, Ruijiang Li, Hongping Tang, Kanran Wang, Yu Li, et al · 2024
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Llm-guided multi-modal multiple instance learning for 5-year overall survival prediction of lung cancer
Kyungwon Kim, Yongmoon Lee, Doohyun Park, Taejoon Eo, Daemyung Youn, Hyesang Lee, and Dosik Hwang · 2024
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Multimodal whole slide foundation model for pathology
Tong Ding, Sophia J Wagner, Andrew H Song, Richard J Chen, Ming Y Lu, Andrew Zhang, Anurag J Vaidya, Guillaume Jaume, Muhammad Shaban, Ahrong Kim, et al · 2024
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Large language models for disease diagnosis: A scoping review
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High-resolution image synthesis with latent diffusion models
Robin Rombach et al · 2022
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery et al · 2022
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Rt-1: Robotics transformer for real-world control
Anthony Brohan et al · 2022
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Ethical and social risks of harm from language models
Laura Weidinger et al · 2022
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Multimodal adversarial representation learning for breast cancer prognosis prediction
Xiuquan Du and Yuefan Zhao · 2023
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Pathology-and-genomics multimodal transformer for survival outcome prediction
Kexin Ding, Mu Zhou, Dimitris N Metaxas, and Shaoting Zhang · 2023
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Shuang Zhou, Zidu Xu, Mian Zhang, Chunpu Xu, Yawen Guo, Zaifu Zhan, Sirui Ding, Jiashuo Wang, Kaishuai Xu, Yi Fang, et al · 2024
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Modality-aware integration with large language models for knowledge-based visual question answering
Junnan Dong, Qinggang Zhang, Huachi Zhou, Daochen Zha, Pai Zheng, and Xiao Huang · 2024
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Pathformer: a biological pathway informed transformer for disease diagnosis and prognosis using multi-omics data
Xiaofan Liu, Yuhuan Tao, Zilin Cai, Pengfei Bao, Hongli Ma, Kexing Li, Mengtao Li, Yunping Zhu, and Zhi John Lu · 2024
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Multimodal data integration for precision oncology: Challenges and future directions
Huajun Zhou, Fengtao Zhou, Chenyu Zhao, Yingxue Xu, Luyang Luo, and Hao Chen · 2024
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A multimodal knowledge-enhanced whole-slide pathology foundation model
Yingxue Xu, Yihui Wang, Fengtao Zhou, Jiabo Ma, Shu Yang, Huangjing Lin, Xin Wang, Jiguang Wang, Li Liang, Anjia Han, et al · 2024
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A comprehensive survey of continual learning: theory, method and application
Liyuan Wang, Xingxing Zhang, Hang Su, and Jun Zhu · 2024
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Recent advances of foundation language models-based continual learning: A survey
Yutao Yang, Jie Zhou, Xuanwen Ding, Tianyu Huai, Shunyu Liu, Qin Chen, Yuan Xie, and Liang He · 2024
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Continual learning of large language models: A comprehensive survey
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Continual learning for large language models: A survey
Tongtong Wu, Linhao Luo, Yuan-Fang Li, Shirui Pan, Thuy-Trang Vu, and Gholamreza Haffari · 2024
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Modality-inconsistent continual learning of multimodal large language models
Weiguo Pian, Shijian Deng, Shentong Mo, Yunhui Guo, and Yapeng Tian · 2024
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Modalprompt: Dual-modality guided prompt for continual learning of large multimodal models
Fanhu Zeng, Fei Zhu, Haiyang Guo, Xu-Yao Zhang, and Cheng-Lin Liu · 2024
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Llm-assisted multi-teacher continual learning for visual question answering in robotic surgery
Kexin Chen, Yuyang Du, Tao You, Mobarakol Islam, Ziyu Guo, Yueming Jin, Guangyong Chen, and Pheng-Ann Heng · 2024
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marugoto: Machine learning for medical images, 2024
Kather Lab · 2024
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Bulkrnabert: Cancer prognosis from bulk rna-seq based language models
Maxence Gélard, Guillaume Richard, Thomas Pierrot, and Paul-Henry Cournède · 2024
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Crema: Generalizable and efficient video-language reasoning via multimodal modular fusion
Shoubin Yu, Jaehong Yoon, and Mohit Bansal · 2025
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