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Nini Rao
Researcher at University of Electronic Science and Technology of China
Publications - 20
Citations - 451
Nini Rao is an academic researcher from University of Electronic Science and Technology of China. The author has contributed to research in topics: Gene & Cancer. The author has an hindex of 8, co-authored 20 publications receiving 392 citations.
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Medical image fusion via an effective wavelet-based approach
TL;DR: A novel wavelet-based approach for medical image fusion is presented, which is developed by taking into not only account the characteristics of human visual system (HVS) but also the physical meaning of the wavelet coefficients.
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The Reorganization of Human Brain Networks Modulated by Driving Mental Fatigue
TL;DR: Results indicate that functional networkTopology can shift the network topology structure toward a more economic but less efficient configuration, which suggests low wiring costs in functional networks and disruption of the effective interactions between and across cortical regions during mental fatigue states.
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Predicting protein folding rates using the concept of Chou's pseudo amino acid composition
TL;DR: In this study, amino acid sequence order was used to derive an effective method, based on an extended version of the pseudo‐amino acid composition, for predicting protein folding rates without any explicit structural information, and the results indicate that sequence order information is an important determinant ofprotein folding rates.
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Identification of lesion images from gastrointestinal endoscope based on feature extraction of combinational methods with and without learning process
Dingyun Liu,Tao Gan,Nini Rao,Yao-Wen Xing,Jie Zheng,Sang Li,Chengsi Luo,Zhong-Jun Zhou,Wan Yongli +8 more
TL;DR: A new computer-aided method to detect lesion images and provide worthwhile guidance for improving the efficiency and accuracy of gastrointestinal disease diagnosis and is a good prospect for clinical application.
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Exploring time- and frequency- dependent functional connectivity and brain networks during deception with single-trial event-related potentials.
Junfeng Gao,Yong Yang,Wen-tao Huang,Pan Lin,Sheng Ge,Hong-mei Zheng,Ling-yun Gu,Hui Zhou,Chenhong Li,Nini Rao +9 more
TL;DR: The experimental results revealed that deceptive responses elicited greater connectivity strength than truthful responses, particularly in the θ band on specific electrode pairs primarily involving connections between the prefrontal/frontal and central regions and between the cortex and left parietal regions.