default author photo

Jun Tu

Tianjin Medical University - Department of Neurology

China

SCHOLARLY PAPERS

2

DOWNLOADS

103

TOTAL CITATIONS

0

Scholarly Papers (2)

Actions:
Email selected abstracts
1.

Macroeconomic Development and Dramatic Increase in Stroke Burden in Rural China: A 25-Year Population-Based Study

Number of pages: 27 Posted: 07 Feb 2020
Peng Zhao, Qiuxing Lin, Yuhan Hao, Jie Liu, Ying Gao, Jun Tu, Jinghua Wang, Yaogang Wang and Xianjia Ning
Tianjin Medical University - Department of Neurology, Tianjin Medical University - Department of Neurology, Tianjin Medical University - Department of Neurology, Tianjin Medical University - Department of Neurology, Tianjin Medical University - General Hospital, Tianjin Medical University - Department of Neurology, Tianjin Medical University - Department of Neurology, Tianjin Medical University - School of Public Health and Tianjin Medical University - Department of Neurology
Downloads 66 (907,769)

Abstract:

Loading...

Stroke; Macroeconomic development; Epidemiology; Incidence

2.

Ten-Year Assessment of China's Health Care Reform on Improving Stroke Prognoses Among Low-Income Populations: A Long-Term (1992-2018), Population-Based, Prospective Study

Number of pages: 31 Posted: 29 Feb 2020
Jie Liu, Qiuxing Lin, Xinxin Zhang, Dongwang Qi, Conglin Wang, Ying Gao, Jun Tu, Yaogang Wang, Jinghua Wang and Xianjia Ning
Tianjin Medical University - Department of Neurology, Tianjin Medical University - Department of Neurology, Tianjin Medical University - Department of Endocrinology and Metabolism, Tianjin Medical University - Department of Endocrinology and Metabolism, Tianjin Medical University - General Hospital, Tianjin Medical University - General Hospital, Tianjin Medical University - Department of Neurology, Tianjin Medical University - School of Public Health, Tianjin Medical University - Department of Neurology and Tianjin Medical University - Department of Neurology
Downloads 37 (1,222,651)

Abstract:

Loading...

Health care reform; Stroke prognoses; Low-income populations; Population-based study; China