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Yingcheng Liu on Muck Rack

Yingcheng Liu

As seen in: Nature, Frontiers in Public Health, Science Magazine
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Articles

Risk factors and predictive modeling of postpartum depression among postpartum women: empirical evidence from Chongqing, China

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By Jiaming Jiang, Guichuan Lai, Wenlong Li, Yingcheng Liu, Tian Liu, Xinjing Liu, Qian Wang, Biao Xie, Xiaoni Zhong, Haijiao Zeng
| Frontiers in Public Health Verified
1 Introduction Postpartum depression (PPD) is a prevalent mental health disorder affecting women worldwide, with significant implications for both maternal wellbeing and child development (1). Women experiencing PPD often exhibit symptoms such as persistent sadness, fatigue, feelings of worthlessness, reduced interest in their infants, loss of appetite, and sleep disturbances.
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Monitoring gait at home with radio waves in Parkinson’s disease: A marker of severity, progression, and medication response

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By Xavier Charmetant, Jackson Liang, Armen A. Gharibans, Yingcheng Liu
| Science Magazine Verified
Gait speed as a marker of PD motor fluctuation and medication response Within 3 to 5 years of levodopa treatment, about 50% of individuals with PD begin to develop motor fluctuations (34), characterized by a decline in the duration of benefit of each dose with emergent motor fluctuations, a phenomenon known as “wearing-off” or “ON-OFF” effect (3).
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Artificial intelligence-enabled detection and assessment of Parkinson’s disease using nocturnal breathing signals - Nature Medicine

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By Yuzhe Yang, Yuan Yuan, Hao Wang, Yingcheng Liu
| Nature Verified
Abstract There are currently no effective biomarkers for diagnosing Parkinson’s disease (PD) or tracking its progression. Here, we developed an artificial intelligence (AI) model to detect PD and track its progression from nocturnal breathing signals. The model was evaluated on a large dataset comprising 7,671 individuals, using data from several hospitals in the United States, as well as multiple public datasets.
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