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Your search keyword '"Deng, Jieyao"' showing total 6 results
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6 results on '"Deng, Jieyao"'

2. Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease

Author

Allen, Genevera I, Amoroso, Nicola, Anghel, Catalina, Balagurusamy, Venkat, Bare, Christopher J, Beaton, Derek, Bellotti, Roberto, Bennett, David A, Boehme, Kevin L, Boutros, Paul C, Caberlotto, Laura, Caloian, Cristian, Campbell, Frederick, Neto, Elias Chaibub, Chang, Yu‐Chuan, Chen, Beibei, Chen, Chien‐Yu, Chien, Ting‐Ying, Clark, Tim, Das, Sudeshna, Davatzikos, Christos, Deng, Jieyao, Dillenberger, Donna, Dobson, Richard JB, Dong, Qilin, Doshi, Jimit, Duma, Denise, Errico, Rosangela, Erus, Guray, Everett, Evan, Fardo, David W, Friend, Stephen H, Fröhlich, Holger, Gan, Jessica, St George‐Hyslop, Peter, Ghosh, Satrajit S, Glaab, Enrico, Green, Robert C, Guan, Yuanfang, Hong, Ming‐Yi, Huang, Chao, Hwang, Jinseub, Ibrahim, Joseph, Inglese, Paolo, Iyappan, Anandhi, Jiang, Qijia, Katsumata, Yuriko, Kauwe, John SK, Klein, Arno, Kong, Dehan, Krause, Roland, Lalonde, Emilie, Lauria, Mario, Lee, Eunjee, Lin, Xihui, Liu, Zhandong, Livingstone, Julie, Logsdon, Benjamin A, Lovestone, Simon, Ma, Tsung‐wei, Malhotra, Ashutosh, Mangravite, Lara M, Maxwell, Taylor J, Merrill, Emily, Nagorski, John, Namasivayam, Aishwarya, Narayan, Manjari, Naz, Mufassra, Newhouse, Stephen J, Norman, Thea C, Nurtdinov, Ramil N, Oyang, Yen‐Jen, Pawitan, Yudi, Peng, Shengwen, Peters, Mette A, Piccolo, Stephen R, Praveen, Paurush, Priami, Corrado, Sabelnykova, Veronica Y, Senger, Philipp, Shen, Xia, Simmons, Andrew, Sotiras, Aristeidis, Stolovitzky, Gustavo, Tangaro, Sabina, Tateo, Andrea, Tung, Yi‐An, Tustison, Nicholas J, Varol, Erdem, Vradenburg, George, Weiner, Michael W, Xiao, Guanghua, Xie, Lei, Xie, Yang, Xu, Jia, Yang, Hojin, Zhan, Xiaowei, Zhou, Yunyun, Zhu, Fan, and Zhu, Hongtu

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Acquired Cognitive Impairment, Prevention, Neurodegenerative, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Dementia, Alzheimer's Disease, Aging, Brain Disorders, Neurological, Alzheimer Disease, Apolipoproteins E, Biomarkers, Cognition Disorders, Computational Biology, Databases, Bibliographic, Humans, Predictive Value of Tests, Azheimer's disease, Crowdsource, Big data, Bioinformatics, Cognitive decline, Imaging, Genetics, Alzheimer's Disease Neuroimaging Initiative, Geriatrics, Clinical sciences, Biological psychology
Abstract

Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.

Published
2016

3. Design and Fabrication of Ultralow Temperature Vibration Sensor Based on Self-Excited Vibration Resonance Frequency Test

Author

An, Daren, Cui, Ke, An, Qi, Guo, Xiaolin, Deng, Jieyao, Xie, Huikai, Shen, Chong, and Cao, Huiliang

Abstract

In the field of aerospace, deep space exploration is becoming more and more frequent, and the temperature deep in the universe is getting lower and lower. Specialized equipment for vibration monitoring of instruments under harsh conditions of ultralow temperature is scarce, and how to design a vibration sensor to solve the vibration monitoring in ultralow temperature environments is an urgent problem. In this article, we propose a novel testing methodology known as self-excited vibration resonance frequency test (SEVFT) of piezoelectric sheet in ultralow temperature, which contributes to the ultralow temperature survival verification of piezoelectric materials for ultralow temperature vibration sensors. The method proves that the PZT-7A piezoelectric material can work in ultralow temperature environments. The sensitivity of the ultralow temperature vibration sensor was obtained by vibration test as well as temperature test to be 5.08 mV/g. It can work normally at −197 °C-RT with small output signal noise. The ultralow temperature vibration sensor designed in this article has low cost and good low-temperature resistance. It can be widely used in structural health monitoring of instruments and equipment in ultralow temperature environments.

Published
2024
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6. DrugE-Rank: Predicting Drug-Target Interactions by Learning to Rank.

Author

Deng J, Yuan Q, Mamitsuka H, and Zhu S

Subjects
Drug Approval, United States, United States Food and Drug Administration, User-Computer Interface, Algorithms, Drug Interactions
Abstract

Identifying drug-target interactions is crucial for the success of drug discovery. Approaches based on machine learning for this problem can be divided into two types: feature-based and similarity-based methods. By utilizing the "Learning to rank" framework, we propose a new method, DrugE-Rank, to combine these two different types of methods for improving the prediction performance of new candidate drugs and targets. DrugE-Rank is available at http://datamining-iip.fudan.edu.cn/service/DrugE-Rank/ .

Published
2018
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