Zobrazeno 1 - 10 of 39 pro vyhledávání: '"Zhaoxian Zhou"'
1
Akademický článek
Structure–activity relationship-based chemical classification of highly imbalanced Tox21 datasets
Autor: Gabriel Idakwo, Sundar Thangapandian, Joseph Luttrell, Yan Li, Nan Wang, Zhaoxian Zhou, Huixiao Hong, Bei Yang, Chaoyang Zhang, Ping Gong
Publikováno v: Journal of Cheminformatics, Vol 12, Iss 1, Pp 1-19 (2020)
Abstract The specificity of toxicant-target biomolecule interactions lends to the very imbalanced nature of many toxicity datasets, causing poor performance in Structure–Activity Relationship (SAR)-based chemical classification. Undersampling and o
Externí odkaz: https://doaj.org/article/b896e5129bce4435858ec953edd5dd19
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2
Akademický článek
Deep learning architectures for multi-label classification of intelligent health risk prediction
Autor: Andrew Maxwell, Runzhi Li, Bei Yang, Heng Weng, Aihua Ou, Huixiao Hong, Zhaoxian Zhou, Ping Gong, Chaoyang Zhang
Publikováno v: BMC Bioinformatics, Vol 18, Iss S14, Pp 121-131 (2017)
Abstract Background Multi-label classification of data remains to be a challenging problem. Because of the complexity of the data, it is sometimes difficult to infer information about classes that are not mutually exclusive. For medical data, patient
Externí odkaz: https://doaj.org/article/cdbc44b8717942fb9bf70b246576e543
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3
Akademický článek
Deep Learning-Based Structure-Activity Relationship Modeling for Multi-Category Toxicity Classification: A Case Study of 10K Tox21 Chemicals With High-Throughput Cell-Based Androgen Receptor Bioassay Data
Autor: Gabriel Idakwo, Sundar Thangapandian, Joseph Luttrell, Zhaoxian Zhou, Chaoyang Zhang, Ping Gong
Publikováno v: Frontiers in Physiology, Vol 10 (2019)
Deep learning (DL) has attracted the attention of computational toxicologists as it offers a potentially greater power for in silico predictive toxicology than existing shallow learning algorithms. However, contradicting reports have been documented.
Externí odkaz: https://doaj.org/article/8297a26d1b35453fa6e1e4b17d253b7f
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7
Bi-level Nasal Positive Airway Pressure (BiPAP) versus Nasal Continuous Positive Airway Pressure (CPAP) for Preterm Infants with Birth Weight Less Than 1500 g and Respiratory Distress Syndrome Following INSURE Treatment: A Two-center Randomized Controlled Trial
Autor: Jing Wang, Gao-Yan Chen, Zhihui Rong, Zhaoxian Zhou, Rui Pan, Ping-Ying Zhang, Liwen Chang
Publikováno v: Current Medical Science
Summary The present study aimed to examine the effectiveness of bi-level positive airway pressure (BiPAP) versus continuous positive airway pressure (CPAP) in preterm infants with birth weight less than 1500 g and respiratory distress syndrome (RDS)
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d68ec56bcc9aea90ad4f41f88ec1890e
https://doi.org/10.1007/s11596-021-2372-8
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8
Analyses of Countermovement Jump Performance in Time and Frequency Domains
Autor: Zhanxin Sha, Boyi Dai, Zhaoxian Zhou
Publikováno v: Journal of Human Kinetics
This study aimed to analyze counter-movement jump (CMJ) performance in time and frequency domains. Fortyfour Division I American football players participated in the study. Kinetic variables were collected from both dominant and non-dominant legs usi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4600ea1fa9f765d900f3ad9534505468
https://doi.org/10.2478/hukin-2021-0028
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9
Deep learning-based structure-activity relationship modeling for multi-category toxicity classification : a case study of 10K Tox21 chemicals with high-throughput cell-based androgen receptor bioassay data
Autor: Gabriel Idakwo, Sundar Thangapandian, Joseph Luttrell, Zhaoxian Zhou, Chaoyang Zhang, Ping Gong
Deep learning (DL) has attracted the attention of computational toxicologists as it offers a potentially greater power for in silico predictive toxicology than existing shallow learning algorithms. However, contradicting reports have been documented.
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::13ea287e687fde07ae445721033dffaf
https://doi.org/10.21079/11681/41302
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10
Basketball-51: A Video Dataset for Activity Recognition in the Basketball Game
Autor: Chaoyang Zhang, Sarbagya Ratna Shakya, Zhaoxian Zhou
Publikováno v: Computer Science & Information Technology (CS & IT).
In recent years, there has been an increase in the association of technology in sports and live sports broadcasting networks. From score updates, broadcasting commercials, assisting referees for decision making, and minimizing errors, the adoption of
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d65fc8fef785206542f526db5fd01075
https://doi.org/10.5121/csit.2021.110712
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