scholarly journals Temporal Segmentation for Capturing Snapshots of Patient Histories in Korean Clinical Narrative

2018 ◽  
Vol 24 (3) ◽  
pp. 179 ◽  
Author(s):  
Wangjin Lee ◽  
Jinwook Choi
Author(s):  
Guoliang Luo ◽  
Zhigang Deng ◽  
Xin Zhao ◽  
Xiaogang Jin ◽  
Wei Zeng ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fatemeh Hadaeghi ◽  
Björn-Philipp Diercks ◽  
Daniel Schetelig ◽  
Fabrizio Damicelli ◽  
Insa M. A. Wolf ◽  
...  

AbstractAdvances in high-resolution live-cell $$\hbox {Ca}^{2+}$$ Ca 2 + imaging enabled subcellular localization of early $$\hbox {Ca}^{2+}$$ Ca 2 + signaling events in T-cells and paved the way to investigate the interplay between receptors and potential target channels in $$\hbox {Ca}^{2+}$$ Ca 2 + release events. The huge amount of acquired data requires efficient, ideally automated image processing pipelines, with cell localization/segmentation as central tasks. Automated segmentation in live-cell cytosolic $$\hbox {Ca}^{2+}$$ Ca 2 + imaging data is, however, challenging due to temporal image intensity fluctuations, low signal-to-noise ratio, and photo-bleaching. Here, we propose a reservoir computing (RC) framework for efficient and temporally consistent segmentation. Experiments were conducted with Jurkat T-cells and anti-CD3 coated beads used for T-cell activation. We compared the RC performance with a standard U-Net and a convolutional long short-term memory (LSTM) model. The RC-based models (1) perform on par in terms of segmentation accuracy with the deep learning models for cell-only segmentation, but show improved temporal segmentation consistency compared to the U-Net; (2) outperform the U-Net for two-emission wavelengths image segmentation and differentiation of T-cells and beads; and (3) perform on par with the convolutional LSTM for single-emission wavelength T-cell/bead segmentation and differentiation. In turn, RC models contain only a fraction of the parameters of the baseline models and reduce the training time considerably.


2018 ◽  
Vol 29 (5) ◽  
pp. 891-913
Author(s):  
Cem Direkoǧlu ◽  
Noel E. O’Connor

1992 ◽  
Vol 79 (10) ◽  
pp. 479-480 ◽  
Author(s):  
M. Vollrath ◽  
J. Kazenwadel ◽  
H.-P. Kr�ger

1997 ◽  
Vol 12 (S2) ◽  
pp. 120s-120s
Author(s):  
F. Ouartier ◽  
P. Bovet ◽  
P. Baud

2014 ◽  
Vol 543-547 ◽  
pp. 2418-2421
Author(s):  
Yong Wang

In this paper we introduce cross tree and block mathematical principles into the design of database system, divide the time sequence and storage space of computer database system, establish the mathematical model and algorithm of computer resources database system, and design the test database system. In this paper, we use high performance interface of Display Port, by way of coupling to communicate on two port control, and use RHEL 6.2 Linux virtual machine to do simulation experiment on process of database system. Through the simulation we find the API which is called by Read, Close, Mmap, Stat, Fstat is similar. It is consistent with the actual situation, and verifies the reliability of the program. Finally, we apply the database system to the network database construction of sports literature resources in the new town of Poyang Lake area. It reaches the effect that sport resources are shared by all. It provides technical support for the application of computer database system.


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