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Multimodal Whole Slide Foundation Model for Pathology

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arXiv 2024年

作者： Ding, Tong Wagner, Sophia J. Song, Andrew H. Chen, Richard J. Lu, Ming Y. Zhang, Andrew Vaidya, Anurag J. Jaume, Guillaume Shaban, Muhammad Kim, Ahrong Williamson, Drew F.K. Chen, Bowen Almagro-Perez, Cristina Doucet, Paul Sahai, Sharifa Chen, Chengkuan Komura, Daisuke Kawabe, Akihiro Ishikawa, Shumpei Gerber, Georg Peng, Tingying Le, Long Phi Mahmood, Faisal Department of Pathology Mass General Brigham Harvard Medical School BostonMA United States Data Science Program Dana-Farber Cancer Institute BostonMA United States Cancer Program Broad Institute of Harvard and MIT CambridgeMA United States John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA United States Helmholtz Munich German Research Center for Environment and Health Munich Germany School of Computation Information and Technology Technical University of Munich Munich Germany Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology CambridgeMA United States Department of Pathology Pusan National University Busan Korea Republic of Department of Pathology and Laboratory Medicine Emory University School of Medicine AtlantaGA United States Harvard Data Science Initiative Harvard University CambridgeMA United States Department of Systems Biology Harvard Medical School BostonMA United States Department of Preventive Medicine Graduate School of Medicine The University of Tokyo Tokyo Japan Division of Pathology National Cancer Center Exploratory Oncology Research & Clinical Trial Center Chiba Japan

The field of computational pathology has been transformed with recent advances in foundation models that encode histopathology region-of-interests (ROIs) into versatile and transferable feature representations via self-supervised learning (SSL). However, translating these advancements to address complex clinical challenges at the patient and slide level remains constrained by limited clinical data in disease-specific cohorts, especially for rare clinical conditions. We propose TITAN, a multimodal whole slide foundation model pretrained using 335,645 WSIs via visual self-supervised learning and vision-language alignment with corresponding pathology reports and 423,122 synthetic captions generated from a multimodal generative AI copilot for pathology. Without any finetuning or requiring clinical labels, TITAN can extract general-purpose slide representations and generate pathology reports that generalize to resource-limited clinical scenarios such as rare disease retrieval and cancer prognosis. We evaluate TITAN on diverse clinical tasks and find that TITAN outperforms both ROI and slide foundation models across machine learning settings such as linear probing, few-shot and zero-shot classification, rare cancer retrieval and cross-modal retrieval, and pathology report generation. The model is publicly accessible at https://***/mahmoodlab/TITAN © 2024, CC BY-NC-ND.

关键词： Self-supervised learning

BeLDPC: Bit Errors Aware Adaptive Rate LDPC Codes for 3D TLC NAND Flash Memory

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BeLDPC: Bit Errors Aware Adaptive Rate LDPC Codes for 3D TLC...

Design, Automation and Test in Europe Conference and Exhibition

作者： Meng Zhang Fei Wu Qin Yu Weihua Liu Lanlan Cui Yahui Zhao Changsheng Xie Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of data storage systems and Technology Ministry of Education of China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9783981926347

ISBN: (纸本)9781728144689

Three-dimensional (3D) NAND flash memory has high capacity and cell storage density by using the multi-bit technology and vertical stack architecture, but degrading data reliability due to high raw bit error rates (RBER) caused by program/erase (P/E) cycles and retention periods. Low-density parity-check (LDPC) codes become more popular error-correcting technologies to improve data reliability due to strong error correction capability, but introducing more decoding iterations at higher RBER. To reduce decoding iterations, this paper proposes BeLDPC: bit errors aware adaptive rate LDPC codes for 3D triple-level cell (TLC) NAND flash memory. Firstly, bit error characteristics in 3D charge trap TLC NAND flash memory are studied on a real FPGA testing platform, including asymmetric bit flipping and temporal locality of bit errors. Then, based on these characteristics, a high-efficiency LDPC code is designed. Experimental results show BeLDPC can reduce decoding iterations under different P/E cycles and retention periods.

关键词： Iterative decoding Three-dimensional displays Error analysis Reliability Encoding Computer architecture

Improving Automatic Speech Recognition Utilizing Audio-codecs for data Augmentation

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Improving Automatic Speech Recognition Utilizing Audio-codec...

IEEE Workshop on Multimedia Signal Processing

作者： Nirayo Hailu Ingo Siegert Andreas Nürnberger Faculty of Computer Science Data and Knowledge Engineering Group Otto-von-Guericke University Magdeburg Magdeburg Germany Faculty of Electrical Engineering and Information Technology Mobile Dialog Systems Otto-von-Guericke University Magdeburg Magdeburg Germany

ISBN: (数字)9781728193205

ISBN: (纸本)9781728193236

To train end-to-end automatic speech recognition models, it requires a large amount of labeled speech data. This goal is challenging for languages with fewer resources. In contrast to the commonly used feature level data augmentation, we propose to expand the training set by using different audio codecs at the data level. The augmentation method consists of using different audio codecs with changed bit rate, sampling rate, and bit depth. The change reassures variation in the input data without drastically affecting the audio quality. Besides, we can ensure that humans still perceive the audio, and any feature extraction is possible later. To demonstrate the general applicability of the proposed augmentation technique, we evaluated it in an end-to-end automatic speech recognition architecture in four languages. After applying the method, on the Amharic, Dutch, Slovenian, and Turkish datasets, we achieved a 1.57 average improvement in the character error rates (CER) without integrating language models. The result is comparable to the baseline result, showing CER improvement of 2.78, 1.25, 1.21, and 1.05 for each language. On the Amharic dataset, we reached a syllable error rate reduction of 6.12 compared to the baseline result.

关键词： Training Codecs Speech coding Error analysis Bit rate Feature extraction Automatic speech recognition

A Green Paradigm for Internet of Things: Ambient Backscatter Communications

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China Communications 2019年第7期16卷 109-119页

作者： Wei Zhang Yao Qin Wenjing Zhao Minzheng Jia Qiang Liu Ruisi He Bo Ai Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology and also with Institute of Telecommunication Satellites China Academy of Space Technology (CAST) Beijing Key Lab of Transportation Data Analysis and Mining Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications School of Computer and Information Technology Beijing Jiaotong University Beijing 100044 China Department of Information Engineering Beijing Polytechnic College Beijing 100042 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing 100044 China

Internet of Things (IoT) has attracted extensive interest from both academia and industries, and is recognized as an ultimate infrastructure to connect everything at anytime and anywhere. The implementation of IoT generally faces the challenges from energy constraint and implementation cost. In this paper, we will introduce a new green communication paradigm, the ambient backscatter (AmBC), that could utilize the environmental wireless signals for both powering a tiny-cost device and backscattering the information symbols. Specifically, we will present the basic principles of AmBC, analyze its features and advantages, suggest its open problems, and predict its potential applications for our future IoT.

关键词： ambient backscatter (AmBC) RF-powered device Internet of Things (IoT) battery-free tag wire-less sensor

How do diseases spread at the critical state?

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Chaos, Solitons & Fractals 2025年 199卷

作者： Li-Feng Hou Shifu Wang Li Li Xin Lu Gui-Quan Sun Sino-Europe Complex Science Center School of Mathematics North University of China Shanxi Taiyuan 030051 China Complex Systems Research Center Shanxi University Taiyuan 030006 Shanxi China Department of Microbiology Laboratory Children’s Hospital Affiliated to Shandong University Jinan 250022 China School of Computer and Information Technology Shanxi University Taiyuan 030006 Shanxi China College of Systems Engineering National University of Defense Technology Changsha Hunan 410073 China Key Laboratory of Complex Systems and Data Science of Ministry of Education Taiyuan 030006 China

The transmission characteristics of infectious diseases near critical thresholds are essential for public health strategy formulation. This study employs reaction–diffusion SI with nonlinear and SIR models with saturated incidence rates, integrating optimal control theory to investigate epidemic propagation trends under critical conditions. The structural complexity of three epidemiological target states (extinction, quasi-uniform epidemic, and patterned epidemic) is quantitatively characterized using spatial entropy methods. A multi-indicator comparative analysis systematically reveals the evolutionary trends of epidemics in critical states from three dimensions: target attainability, average control intensity, and control complexity. The findings indicate that achieving a patterned epidemic state requires the lowest control intensity and spatial intervention complexity compared to extinction and quasi-uniform states, suggesting that epidemic systems in critical states are more inclined toward structured transmission patterns. The proposed framework for quantifying spatial structure and control complexity provides a theoretical basis and practical guidance for formulating spatial prevention and control strategies for infectious diseases in critical states.

关键词：

Observation of gamma rays up to 320 TeV from the middle-aged TeV pulsar wind nebula HESS J1849-000

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arXiv 2023年

作者： Amenomori, M. Asano, S. Bao, Y.W. Bi, X.J. Chen, D. Chen, T.L. Chen, W.Y. Chen, Xu Chen, Y. Cirennima Cui, S.W. Danzengluobu Ding, L.K. Fang, J.H. Fang, K. Feng, C.F. Feng, Zhaoyang Feng, Z.Y. Gao, Qi Gomi, A. Gou, Q.B. Guo, Y.Q. Guo, Y.Y. Hayashi, Y. He, H.H. He, Z.T. Hibino, K. Hotta, N. Hu, Haibing Hu, H.B. Hu, K.Y. Huang, J. Jia, H.Y. Jiang, L. Jiang, P. Jin, H.B. Kasahara, K. Katayose, Y. Kato, C. Kato, S. Kawahara, I. Kawashima, T. Kawata, K. Kozai, M. Kurashige, D. Labaciren Le, G.M. Li, A.F. Li, H.J. Li, W.J. Li, Y. Lin, Y.H. Liu, B. Liu, C. Liu, J.S. Liu, L.Y. Liu, M.Y. Liu, W. Lu, H. Meng, X.R. Meng, Y. Munakata, K. Nagaya, K. Nakamura, Y. Nakazawa, Y. Nanjo, H. Ning, C.C. Nishizawa, M. Noguchi, R. Ohnishi, M. Okukawa, S. Ozawa, S. Qian, X. Qian, X.L. Qu, X.B. Saito, T. Sakakibara, Y. Sakata, M. Sako, T. Sako, T.K. Sasaki, T. Shao, J. Shibata, M. Shiomi, A. Sugimoto, H. Takano, W. Takita, M. Tan, Y.H. Tateyama, N. Torii, S. Tsuchiya, H. Udo, S. Wang, H. Wang, S.F. Wang, Y.P. Wangdui Wu, H.R. Wu, Q. Xu, J.L. Xue, L. Yang, Z. Yao, Y.Q. Yin, J. Yokoe, Y. Yu, Y.L. Yuan, A.F. Zhai, L.M. Zhang, H.M. Zhang, J.L. Zhang, X. Zhang, X.Y. Zhang, Y. Zhang, Yi Zhang, Ying Zhao, S.P. Zhaxisangzhu Zhou, X.X. Zou, Y.H. Department of Physics Hirosaki University Hirosaki036-8561 Japan Department of Physics Shinshu University Matsumoto390-8621 Japan School of Astronomy and Space Science Nanjing University Nanjing210093 China Key Laboratory of Particle Astrophysics Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China National Astronomical Observatories Chinese Academy of Sciences Beijing100012 China Department of Mathematics and Physics Tibet University Lhasa850000 China Department of Physics Hebei Normal University Shijiazhuang050016 China University of Chinese Academy of Sciences Beijing100049 China Shandong University Qingdao266237 China Institute of Modern Physics SouthWest Jiaotong University Chengdu610031 China Faculty of Engineering Yokohama National University Yokohama240-8501 Japan Faculty of Engineering Kanagawa University Yokohama221-8686 Japan Faculty of Education Utsunomiya University Utsunomiya321-8505 Japan Faculty of Systems Engineering Shibaura Institute of Technology Omiya330-8570 Japan Institute for Cosmic Ray Research University of Tokyo Kashiwa277-8582 Japan Polar Environment Data Science Center Joint Support-Center for Data Science Research Research Organization of Information and Systems Tachikawa190-0014 Japan National Center for Space Weather China Meteorological Administration Beijing100081 China School of Information Science and Engineering Shandong Agriculture University Taian271018 China Department of Astronomy School of Physical Sciences University of Science and Technology of China Hefei230026 China College of Industrial Technology Nihon University Narashino275-8575 Japan National Institute of Informatics Tokyo101-8430 Japan National Institute of Information and Communications Technology Tokyo184-8795 Japan Department of Mechanical and Electrical Engineering Shangdong Management University Jinan250357 China College of Science China University of Petroleum Qingdao266555 China Tok

Gamma rays from HESS J1849−000, a middle-aged TeV pulsar wind nebula (PWN), are observed by the Tibet air shower array and the muon detector array. The detection significance of gamma rays reaches 4.0 σ and 4.4 σ levels above 25 TeV and 100 TeV, respectively, in units of Gaussian standard deviation σ. The energy spectrum measured between 40 TeV −16(E/40 TeV)−2.24±0.41 TeV−1 cm−2 s−1. The gamma-ray energy spectrum from the sub-TeV (E p, cut is estimated at (Equation presented), suggesting that protons are accelerated up to the PeV energy range. Our study thus proposes that HESS J1849−000 should be further investigated as a new candidate for a Galactic PeV cosmic-ray accelerator, PeVatron. © 2023, CC BY.

关键词： Gamma rays

Measurement of the Gamma-Ray Energy Spectrum beyond 100 TeV from the HESS J1843-033 Region

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arXiv 2023年

作者： Amenomori, M. Asano, S. Bao, Y.W. Bi, X.J. Chen, D. Chen, T.L. Chen, W.Y. Chen, Xu Chen, Y. Cirennima Cui, S.W. Danzengluobu Ding, L.K. Fang, J.H. Fang, K. Feng, C.F. Feng, Zhaoyang Feng, Z.Y. Gao, Qi Gomi, A. Gou, Q.B. Guo, Y.Q. Guo, Y.Y. He, H.H. He, Z.T. Hibino, K. Hotta, N. Hu, Haibing Hu, H.B. Hu, K.Y. Huang, J. Jia, H.Y. Jiang, L. Jiang, P. Jin, H.B. Kasahara, K. Katayose, Y. Kato, C. Kato, S. Kawashima, T. Kawata, K. Kozai, M. Kurashige, D. Labaciren Le, G.M. Li, A.F. Li, H.J. Li, W.J. Li, Y. Lin, Y.H. Liu, B. Liu, C. Liu, J.S. Liu, L.Y. Liu, M.Y. Liu, W. Liu, X.L. Lou, Y.-Q. Lu, H. Meng, X.R. Meng, Y. Munakata, K. Nagaya, K. Nakamura, Y. Nakazawa, Y. Nanjo, H. Ning, C.C. Nishizawa, M. Ohnishi, M. Okukawa, S. Ozawa, S. Qian, L. Qian, X. Qian, X.L. Qu, X.B. Saito, T. Sakakibara, Y. Sakata, M. Sako, T. Sako, T.K. Shao, J. Shibata, M. Shiomi, A. Sugimoto, H. Takano, W. Takita, M. Tan, Y.H. Tateyama, N. Torii, S. Tsuchiya, H. Udo, S. Wang, H. Wang, Y.P. Wangdui Wu, H.R. Wu, Q. Xu, J.L. Xue, L. Yang, Z. Yao, Y.Q. Yin, J. Yokoe, Y. Yu, N.P. Yuan, A.F. Zhai, L.M. Zhang, C.P. Zhang, H.M. Zhang, J.L. Zhang, X. Zhang, X.Y. Zhang, Y. Zhang, Yi Zhang, Ying Zhao, S.P. Zhaxisangzhu Zhou, X.X. Department of Physics Hirosaki University Hirosaki036-8561 Japan Department of Physics Shinshu University Matsumoto390-8621 Japan School of Astronomy and Space Science Nanjing University Nanjing210093 China Key Laboratory of Particle Astrophysics Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China National Astronomical Observatories Chinese Academy of Sciences Beijing100012 China Department of Mathematics and Physics Tibet University Lhasa850000 China Department of Physics Hebei Normal University Shijiazhuang050016 China University of Chinese Academy of Sciences Beijing100049 China Shandong University Qingdao266237 China Institute of Modern Physics SouthWest Jiaotong University Chengdu610031 China Faculty of Engineering Yokohama National University Yokohama240-8501 Japan Faculty of Engineering Kanagawa University Yokohama221-8686 Japan Faculty of Education Utsunomiya University Utsunomiya321-8505 Japan Faculty of Systems Engineering Shibaura Institute of Technology Omiya330-8570 Japan Institute for Cosmic Ray Research University of Tokyo Kashiwa277-8582 Japan Polar Environment Data Science Center Joint Support-Center for Data Science Research Research Organization of Information and Systems Tachikawa190-0014 Japan National Center for Space Weather China Meteorological Administration Beijing100081 China School of Information Science and Engineering Shandong Agriculture University Taian271018 China Department of Astronomy School of Physical Sciences University of Science and Technology of China Hefei230026 China Tsinghua University Beijing100084 China Joint Research Center for Astrophysics Tsinghua University Beijing100084 China Department of Astronomy Tsinghua University Beijing100084 China College of Industrial Technology Nihon University Narashino275-8575 Japan National Institute of Informatics Tokyo101-8430 Japan National Institute of Information and Communications Technology Tokyo

HESS J1843-033 is a very-high-energy gamma-ray source whose origin remains unidentified. This work presents, for the first time, the energy spectrum of gamma rays beyond 100 TeV from the HESS J1843-033 region using the data recorded by the Tibet air shower array and its underground muon detector array. A gamma-ray source with an extension of 0◦. 34 ± 0◦. 12 is successfully detected above 25 TeV at (α, δ) = (281◦. 09 ± 0◦. 10, −3◦. 76 ± 0◦. 09) near HESS J1843-033 with a statistical significance of 6.2 σ, and the source is named TASG J1844-038. The position of TASG J1844-038 is consistent with those of HESS J1843-033, eHWC J1842-035, and LHAASO J1843-0338. The measured gamma-ray energy spectrum in 25 TeV −16(E/40 TeV)−3.26±0.30 TeV−1cm−2s−1, and the spectral fit to the combined spectra of HESS J1843-033, LHAASO J1843-0338, and TASG J1844-038 implies the existence of a cutoff at 49.5 ± 9.0 TeV. Associations of TASG J1844-038 with SNR G28.6-0.1 and PSR J1844-0346 are also discussed in detail for the first time. © 2023, CC BY.

关键词： Cosmology

Causal Structure Discovery from Distributions Arising from Mixtures of DAGs

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arXiv 2020年

作者： Saeed, Basil Panigrahi, Snigdha Uhler, Caroline Laboratory for Information and Decision Systems Institute for Data Systems and Society Massachusetts Institute of Technology CambridgeMA United States Department of Statistics University of Michigan Ann ArborMI United States Department of Biosystems Science and Engineering ETH Zurich Switzerland

We consider distributions arising from a mixture of causal models, where each model is represented by a directed acyclic graph (DAG). We provide a graphical representation of such mixture distributions and prove that this representation encodes the conditional independence relations of the mixture distribution. We then consider the problem of structure learning based on samples from such distributions. Since the mixing variable is latent, we consider causal structure discovery algorithms such as FCI that can deal with latent variables. We show that such algorithms recover a "union" of the component DAGs and can identify variables whose conditional distribution across the component DAGs vary. We demonstrate our results on synthetic and real data showing that the inferred graph identifies nodes that vary between the different mixture components. As an immediate application, we demonstrate how retrieval of this causal information can be used to cluster samples according to each mixture component. Copyright © 2020, The Authors. All rights reserved.

关键词： Mixtures

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Guest Editors

Journal of Discrete Mathematical sciences and Cryptography 2021年第8期24卷 ii页

作者： Poonia, Ramesh Chandra Paulose, Joy Dass, Pranav Singh, Vijander Saudagar, Abdul Khader Jilani Diván, Ing. Mario José Department of Computer Science CHRIST (Deemed to be University) Karnataka Bangalore India Department of Computer Science CHRIST (Deemed to be University) Karnataka Bangalore India Department of Computer Science and Engineering Bharati Vidyapeeth’s College of Engineering New Delhi India Department of Computer Science and Engineering Manipal University Jaipur India Information Systems Department College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University (IMSIU) Riyadh Saudi Arabia Data Science Research Group Economy School Universidad Nacional de La Pampa Coronel Gil 353La Pampa Primer Piso - Santa Rosa CP 6300 Argentina