| Prevalence, awareness, treatment, and control of hypertension in China: data from 1· 7 million adults in a population-based screening study (China PEACE Million Persons Project) J Lu, Y Lu, X Wang, X Li, GC Linderman, C Wu, X Cheng, L Mu, H Zhang, ... The Lancet 390 (10112), 2549-2558, 2017 | 1064 | 2017 |
| Prevalence of dyslipidemia and availability of lipid-lowering medications among primary health care settings in China Y Lu, H Zhang, J Lu, Q Ding, X Li, X Wang, D Sun, L Tan, L Mu, J Liu, ... JAMA network open 4 (9), e2127573-e2127573, 2021 | 90 | 2021 |
| A novel machine learning unsupervised algorithm for sleep/wake identification using actigraphy X Li, Y Zhang, F Jiang, H Zhao Chronobiology international 37 (7), 1002-1015, 2020 | 45 | 2020 |
| Trends in the prevalence of overweight and obesity among Chinese school-age children and adolescents from 2010 to 2015 J Zhang, X Li, N Hawley, Z Zheng, Z Zou, L Tan, Q Chen, H Shi, H Zhao, ... Childhood Obesity 14 (3), 182-188, 2018 | 37 | 2018 |
| Exome sequencing implicates impaired GABA signaling and neuronal ion transport in trigeminal neuralgia W Dong, SC Jin, A Allocco, X Zeng, AH Sheth, S Panchagnula, ... IScience 23 (10), 2020 | 27 | 2020 |
| Daily time-use patterns and obesity and mental health among primary school students in Shanghai: a population-based cross-sectional study Y Zhang, D Zhang, X Li, P Ip, F Ho, Y Jiang, W Sun, Q Zhu, W Zhu, ... Scientific Reports 7 (1), 16200, 2017 | 22 | 2017 |
| Automated feature extraction from population wearable device data identified novel loci associated with sleep and circadian rhythms X Li, H Zhao PLoS genetics 16 (10), e1009089, 2020 | 16 | 2020 |
| Analysis of the seasonal trend of congenital heart defects Y Dong, Y Zhang, S Tong, Z Jiang, Z Xu, X Li, W Wang The Journal of pediatrics 207, 29-33. e1, 2019 | 9 | 2019 |
| Circadian rhythm analysis using wearable device data: novel penalized machine learning approach X Li, M Kane, Y Zhang, W Sun, Y Song, S Dong, Q Lin, Q Zhu, F Jiang, ... Journal of Medical Internet Research 23 (10), e18403, 2021 | 8 | 2021 |
| Severe hypertension in China: results from the China PEACE million persons project J Li Journal of Hypertension 39 (3), 461, 2021 | 6 | 2021 |
| Wireless AI-powered IoT sensors for laboratory mice behavior recognition M Chen, Y Liu, JC Tam, H Chan, X Li, C Chan, WJ Li IEEE Internet of Things Journal 9 (3), 1899-1912, 2021 | 5 | 2021 |
| Comparison of actigraphy‐measured and parent‐reported sleep in association with weight status among preschool children AM Abdollahi, X Li, I Merikanto, MH Leppänen, H Vepsäläinen, R Lehto, ... Journal of Sleep Research 33 (1), e13960, 2024 | 3 | 2024 |
| CARE as a wearable derived feature linking circadian amplitude to human cognitive functions S Cui, Q Lin, Y Gui, Y Zhang, H Lu, H Zhao, X Wang, X Li, F Jiang NPJ Digital Medicine 6 (1), 123, 2023 | 3 | 2023 |
| Depression and anxiety among caregivers of psychiatric patients during the late stage of the COVID-19 pandemic: A perspective from network analysis HL Sun, YJ Zhao, S Sha, XH Li, TL Si, YF Liu, Z Su, T Cheung, A Chang, ... Journal of Affective Disorders 344, 33-40, 2024 | 2 | 2024 |
| Development and validation of the chinese geriatric depression risk calculator (CGD-risk): a screening tool to identify elderly chinese with depression C Sakal, J Li, YT Xiang, X Li Journal of Affective Disorders 319, 428-436, 2022 | 2 | 2022 |
| Shared genetic architecture of blood eosinophil counts and asthma in UK Biobank B Li, Y Wang, Z Wang, X Li, S Kay, GL Chupp, H Zhao, JL Gomez ERJ Open Research 9 (4), 2023 | 1 | 2023 |
| Association Between Sleep Efficiency Variability and Cognition Among Older Adults: Cross-Sectional Accelerometer Study C Sakal, T Li, J Li, C Yang, X Li JMIR aging 7, e54353, 2024 | | 2024 |
| Identifying Predictive Risk Factors for Future Cognitive Impairment Among Chinese Older Adults: Longitudinal Prediction Study C Sakal, T Li, J Li, X Li JMIR aging 7, e53240, 2024 | | 2024 |
| Associations between wearable device-measured sleep variability and cognition among older adults C Sakal, T Li, J Li, X Li arXiv preprint arXiv:2309.08809, 2023 | | 2023 |
| Using wearable device-based machine learning models to autonomously identify older adults with poor cognition C Sakal, T Li, J Li, X Li arXiv preprint arXiv:2309.07133, 2023 | | 2023 |
