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Improving AI System Awareness of Geoscience Knowledge: Symbiotic Integration of Physical Approaches and Deep Learning 期刊论文
GEOPHYSICAL RESEARCH LETTERS, 2020, 47 (13)
作者:  Jiang, Shijie;  Zheng, Yi;  Solomatine, Dimitri
收藏  |  浏览/下载：13/0  |  提交时间：2020/06/16
artificial intelligence  deep learning  Earth science  geosystem dynamics  hydrology  predictions in ungauged basins  
Comparative assessment of environmental variables and machine learning algorithms for maize yield prediction in the US Midwest 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2020, 15 (6)
作者:  Kang, Yanghui;  Ozdogan, Mutlu;  Zhu, Xiaojin;  Ye, Zhiwei;  Hain, Christopher;  Anderson, Martha
收藏  |  浏览/下载：15/0  |  提交时间：2020/07/02
crop yields  climate impact  machine learning  deep learning  data-driven  
Physics-Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow Problems 期刊论文
WATER RESOURCES RESEARCH, 2020, 56 (5)
作者:  Tartakovsky, A. M.;  Marrero, C. Ortiz;  Perdikaris, Paris;  Tartakovsky, G. D.;  Barajas-Solano, D.
收藏  |  浏览/下载：12/0  |  提交时间：2020/07/02
deep neural networks  physics-informed machine learning  parameter estimation  learning constitutive relationships  unsaturated flow  MAP  
Deep Learning Emulation of Subgrid-Scale Processes in Turbulent Shear Flows 期刊论文
GEOPHYSICAL RESEARCH LETTERS, 2020, 47 (12)
作者:  Pal, Anikesh
收藏  |  浏览/下载：6/0  |  提交时间：2020/05/13
deep learning  turbulence  shear layers  
Reconstruction of GRACE Data on Changes in Total Water Storage Over the Global Land Surface and 60 Basins 期刊论文
WATER RESOURCES RESEARCH, 2020, 56 (4)
作者:  Sun, Zhangli;  Long, Di;  Yang, Wenting;  Li, Xueying;  Pan, Yun
收藏  |  浏览/下载：12/0  |  提交时间：2020/07/02
GRACE  spherical harmonics  mascons  machine learning  data gaps  reconstruction  
Machine-Learning-Based Analysis of the Guy-Greenbrier, Arkansas Earthquakes: A Tale of Two Sequences 期刊论文
GEOPHYSICAL RESEARCH LETTERS, 2020, 47 (6)
作者:  Park, Yongsoo;  Mousavi, S. Mostafa;  Zhu, Weiqiang;  Ellsworth, William L.;  Beroza, Gregory C.
收藏  |  浏览/下载：6/0  |  提交时间：2020/07/02
induced seismicity  earthquake cataloging  machine learning  
Ground-Based Cloud Classification Using Task-Based Graph Convolutional Network 期刊论文
GEOPHYSICAL RESEARCH LETTERS, 2020, 47 (5)
作者:  Liu, Shuang;  Li, Mei;  Zhang, Zhong;  Cao, Xiaozhong;  Durrani, Tariq S.
收藏  |  浏览/下载：7/0  |  提交时间：2020/07/02
Integrating genomic features for non-invasive early lung cancer detection 期刊论文
NATURE, 2020, 580 (7802) : 245-+
作者:  Wang, Qinyang;  Wang, Yupeng;  Ding, Jingjin;  Wang, Chunhong;  Zhou, Xuehan;  Gao, Wenqing;  Huang, Huanwei;  Shao, Feng;  Liu, Zhibo
收藏  |  浏览/下载：15/0  |  提交时间：2020/07/03

Circulating tumour DNA in blood is analysed to identify genomic features that distinguish early-stage lung cancer patients from risk-matched controls, and these are integrated into a machine-learning method for blood-based lung cancer screening.


Radiologic screening of high-risk adults reduces lung-cancer-related mortality(1,2)  however, a small minority of eligible individuals undergo such screening in the United States(3,4). The availability of blood-based tests could increase screening uptake. Here we introduce improvements to cancer personalized profiling by deep sequencing (CAPP-Seq)(5), a method for the analysis of circulating tumour DNA (ctDNA), to better facilitate screening applications. We show that, although levels are very low in early-stage lung cancers, ctDNA is present prior to treatment in most patients and its presence is strongly prognostic. We also find that the majority of somatic mutations in the cell-free DNA (cfDNA) of patients with lung cancer and of risk-matched controls reflect clonal haematopoiesis and are non-recurrent. Compared with tumour-derived mutations, clonal haematopoiesis mutations occur on longer cfDNA fragments and lack mutational signatures that are associated with tobacco smoking. Integrating these findings with other molecular features, we develop and prospectively validate a machine-learning method termed '  lung cancer likelihood in plasma'  (Lung-CLiP), which can robustly discriminate early-stage lung cancer patients from risk-matched controls. This approach achieves performance similar to that of tumour-informed ctDNA detection and enables tuning of assay specificity in order to facilitate distinct clinical applications. Our findings establish the potential of cfDNA for lung cancer screening and highlight the importance of risk-matching cases and controls in cfDNA-based screening studies.


  
A 450 million years long latitudinal gradient in age-dependent extinction 期刊论文
ECOLOGY LETTERS, 2020, 23 (3) : 439-446
作者:  Silvestro, Daniele;  Castiglione, Silvia;  Mondanaro, Alessandro;  Serio, Carmela;  Melchionna, Marina;  Piras, Paolo;  Di Febbraro, Mirko;  Carotenuto, Francesco;  Rook, Lorenzo;  Raia, Pasquale
收藏  |  浏览/下载：7/0  |  提交时间：2020/07/02
'  law of constant extinction'  deep learning  fossil occurrences  neural networks  mass extinction  
DeepCropNet: a deep spatial-temporal learning framework for county-level corn yield estimation 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2020, 15 (3)
作者:  Lin, Tao;  Zhong, Renhai;  Wang, Yudi;  Xu, Jinfan;  Jiang, Hao;  Xu, Jialu;  Ying, Yibin;  Rodriguez, Luis;  Ting, K. C.;  Li, Haifeng
收藏  |  浏览/下载：10/0  |  提交时间：2020/07/02
yield estimation  corn  LSTM  attention mechanism  multi-task learning  deep learning