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Document Title Author Full Name Author Short Name Index Corresponding Address ResearcherID ResearcherID Author Name ORCID ORCID Author Name Related Email
International expert consensus statement about methods and indications for keyhole microneurosurgery from International Society on Minimally Invasive Neurosurgery Kang, Dezhi Kang, DZ 10 Fujian Med Univ, Affiliated Hosp 1, Dept Neurosurg, Fuzhou, Fujian, Peoples R China szlq006@163.com;kyoko@fujita-hu.ac.jp;
International expert consensus statement about methods and indications for keyhole microneurosurgery from International Society on Minimally Invasive Neurosurgery Kikuta, Kenichiro Kikuta, K 11 Univ Fukui, Dept Neurosurg, Fukui, Japan szlq006@163.com;kyoko@fujita-hu.ac.jp;
International expert consensus statement about methods and indications for keyhole microneurosurgery from International Society on Minimally Invasive Neurosurgery Zhao, Yuanli Zhao, YL 12 Capital Med Univ, Beijing Tiantan Hosp, Dept Neurosurg, Beijing, Peoples R China szlq006@163.com;kyoko@fujita-hu.ac.jp;
International expert consensus statement about methods and indications for keyhole microneurosurgery from International Society on Minimally Invasive Neurosurgery Zhang, Hengzhu Zhang, HZ 13 Yangzhou Univ, Clin Med Coll, Dept Neurosurg, Yangzhou, Jiangsu, Peoples R China szlq006@163.com;kyoko@fujita-hu.ac.jp;
International expert consensus statement about methods and indications for keyhole microneurosurgery from International Society on Minimally Invasive Neurosurgery Irie, Shinsuke Irie, S 14 Kushiro Kojinkai Mem Hosp, Dept Neurosurg, Kushiro, Japan szlq006@163.com;kyoko@fujita-hu.ac.jp;
International expert consensus statement about methods and indications for keyhole microneurosurgery from International Society on Minimally Invasive Neurosurgery Li, Yuping Li, YP 15 Yangzhou Univ, Clin Med Coll, Dept Neurosurg, Yangzhou, Jiangsu, Peoples R China C-4122-2014 Li, Yuping 0000-0002-4527-2582 Li, Yuping szlq006@163.com;kyoko@fujita-hu.ac.jp;
International expert consensus statement about methods and indications for keyhole microneurosurgery from International Society on Minimally Invasive Neurosurgery Liew, Boon Seng Liew, BS 16 Hosp Sungai Buloh, Dept Neurosurg, Sungai Buloh, Malaysia F-4685-2014 Liew, Boon Seng 0000-0001-7322-5487 Boon Seng, Liew szlq006@163.com;kyoko@fujita-hu.ac.jp;
International expert consensus statement about methods and indications for keyhole microneurosurgery from International Society on Minimally Invasive Neurosurgery Kato, Yoko Kato, Y 17 교신저자 Fujita Hlth Univ, Dept Neurosurg, Toyoake, Aichi, Japan szlq006@163.com;kyoko@fujita-hu.ac.jp;
Internet of Vehicles: Key Technologies, Network Model, Solutions and Challenges With Future Aspects Qureshi, Kashif Naseer Qureshi, KN 1 Bahria Univ, Dept Comp Sci, Islamabad 44000, Pakistan AAJ-1052-2020 Qureshi, Kashif 0000-0003-3045-8402 Qureshi, Kashif ggjeon@gmail.com;
Internet of Vehicles: Key Technologies, Network Model, Solutions and Challenges With Future Aspects Din, Sadia Din, S 2 Kyungpook Natl Univ, Sch Comp Sci & Engn, Daegu 41566, South Korea ADU-4679-2022 Din, Sadia 0000-0003-0921-4462 Din, Sadia ggjeon@gmail.com;
Internet of Vehicles: Key Technologies, Network Model, Solutions and Challenges With Future Aspects Jeon, Gwanggil Jeon, G 3 교신저자 Xidian Univ, Sch Elect Engn, Xian 710071, Peoples R China ggjeon@gmail.com;
Internet of Vehicles: Key Technologies, Network Model, Solutions and Challenges With Future Aspects Jeon, Gwanggil Jeon, G 3 교신저자 Incheon Natl Univ, Dept Embedded Syst Engn, Incheon 22012, South Korea ggjeon@gmail.com;
Internet of Vehicles: Key Technologies, Network Model, Solutions and Challenges With Future Aspects Piccialli, Francesco Piccialli, F 4 Incheon Natl Univ, Dept Embedded Syst Engn, Incheon 22012, South Korea ABC-2457-2020 Piccialli, Francesco ggjeon@gmail.com;
Interpretable machine learning for early neurological deterioration prediction in atrial fibrillation-related stroke Kim, Seong-Hwan Kim, SH 1 Korea Univ, Ansan Hosp, Coll Med, Dept Neurol, Gojan 1 Dong, Ansan 15355, Gyeonggi Do, South Korea mcastenosis@gmail.com;jinmanjung@gmail.com;dr.jinmanjung@gmail.com;
Interpretable machine learning for early neurological deterioration prediction in atrial fibrillation-related stroke Jeon, Eun-Tae Jeon, ET 2 Korea Univ, Ansan Hosp, Coll Med, Dept Neurol, Gojan 1 Dong, Ansan 15355, Gyeonggi Do, South Korea AEI-9225-2022 Jeon, Eun-Tae mcastenosis@gmail.com;jinmanjung@gmail.com;dr.jinmanjung@gmail.com;
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