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Huating Li

As seen in: Nature, Frontiers, Cell Metabolism, Cell Reports Medicine
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Articles by Huating Li

Patient factors in medical artificial intelligence: a systematic review

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By Shixin Lai, Zhouyu Guan, Yulian Zhang, Junxian Hong, Dian Zeng, Justin B. Echouffo-Tcheugui, Yiming Qin, Jie Shen, Huating Li, Zehua Jiang, Haichao Chen, Yilan Wu, Zihao Zou, Gezheng Zhao, Yue Qiu Verified, Nan Liu, Xiaodong Sun, Han Lv, Nestoras Mathioudakis, Ethan Goh, Lorainne Tudor Car, Pearse A. Keane, David C. Klonoff, Saleha Masood
| Nature Verified
Abstract Medical artificial intelligence (AI) is increasingly developed, piloted and used in clinical practice, yet the translation of technical capability into real-world benefit is impacted by patient factors that shape how patients understand, engage with and respond to AI outputs and processes. However, there has been limited systematic evaluation of how patient factors are integrated and reported across medical AI research.
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Extended reality in clinical neurology: From interdisciplinary innovations to clinical practice

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By Jiale Yang, Zhouyu Guan, Dian Zeng, Yiming Qin, Shiyu Wang, Qian Wu, Qinyi Wang, Haoxuan Li, Junyu Wu, Haiwei Huang, Yongtian Wang, Enhua Wu, Nadia Magnenat Thalmann, Weiping Jia, Huating Li, Felipe Fregni, Chufan Zhao
| Cell Reports Medicine Verified
Keywords extended reality virtual reality augmented reality mixed reality clinical neurology neurosurgery rehabilitation clinical assessment Introduction Extended reality (XR) is an umbrella term for immersive technologies that exist along the Milgram’s reality-virtuality continuum, encompassing virtual reality (VR), augmented reality (AR), and mixed reality (MR).1,2,3,4 VR immerses users in a completely synthetic environment, blocking out the physical world.
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Time and person sensitive foundation model for disease prediction and risk stratification

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By Zheyuan Wang, Yukun Zhou, Yilan Wu, Ke Zou, Zhouyu Guan, Yibing Chen, Gabriel Dawei Yang, Ping Zhang, Changchang Yin, An Ran, Danqi Fang, Benjamin Sommer Thinggaard, Jakob Grauslund, Haoxuan Li, Jia Shu, Tingyao Li, Nan Jiang, Huating Li, Xiangning Wang, Qiang Wu, Charumathi Sabanayagam, Siegfried Wagner, Carol Cheung, Ching-Yu Cheng, Pearse A. Keane, Yih-Chung Tham, Samantha Yew, Xujia Liu, Yixiao Jin, Tingli Chen
| Nature Verified
Abstract Foundation models (FMs) enable generalizable medical AI, but existing retinal FMs perform best on cross-sectional classification and detection and are less effective for predicting disease incidence and progression. We present RETFound Plus, a CFP-based FM trained with temporal modeling on 1,304,292 fundus photographs from 304,345 participants across multiple visits to learn progression-aware representations.
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PRIMARY-AI: outcomes-based standards to safeguard primary care in the AI era - Nature Medicine

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By Dian Zeng, Lorainne Tudor Car, Kamlesh Khunti, Yuanli Liu, Till Bärnighausen, Niels H. Chavannes, Pearse A. Keane, Holger Kunz, Lan Xue, Yih Chung Tham, Lorenzo Righetto Verified, Donald J. Boudreau, Qionghai Dai, Weiping Jia, Yang Liu Verified, Dinggang Shen, Jia Liu, Weixing Shen, John S. Ji, Zhong Lin Wang, Zhiyi Wang, Haibo Wang, Shenglan Tang, Chenyang Pei, Zehua Jiang, Zihao Zou, Yiming Qin, Huating Li, Yasha Wang, Dinesh Visva Gunasekeran, Sabrina Wong, Dong Xu, Ryan J. Urbanowicz, Liliana Laranjo, Ana Neves, Nan Liu, Neil M. Bressler, Rifat Atun, David C. Klonoff, Nigam H. Shah, Josip Car, Rupa Sarker, Phuoc Van Le
| Nature Verified
Artificial intelligence (AI) is being deployed at scale in primary care — from diagnostic support and risk stratification to triage and clinical documentation — without any agreed-upon outcomes-based framework for determining whether it strengthens or undermines continuity, coordination, comprehensiveness and people-centered care1. This is dangerous for the billions of people whose first contact with health systems is primary care.
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Interindividual variability in gut microbiome mediates the efficacy of resistant starch on MASLD

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By Xiaoxue Long, Hui Wang, Yuwei Lu, Xiaojing J. Gao, Yuanyuan Xiao, Mingliang Zhang, Jingyi Guo, Jingyi Yang, Qian Li, Guiyun Zhou, Ruibao Yang, Feng Chen, Qingqing Wu, Liming Sun, Chengshuang Chu, Xuexue Zhu, Zhengjun Wu, Quanlu Ren, Chunping You, Zhenmin Liu, Dan Liu, Di Cheng, Anran Chen, Qian Wu, Li Wei, Lei Zhang, Jun Li, Gianni Panagiotou, Weiping Jia, Rong Zeng, Yueqiong Ni, Luonan Chen, Huating Li, Piao Kang, Qichen Fang
| Cell Metabolism Verified
Keywords metabolic dysfunction-associated steatotic liver disease gut microbiota resistant starch treatment effect heterogeneity prebiotics precision medicine multi-omics Bifidobacterium pseudocatenulatum Introduction Metabolic dysfunction-associated steatotic liver disease (MASLD), previously recognized as non-alcoholic fatty liver disease (NAFLD), is gaining increasing attention as a global health crisis.1 It encompasses a spectrum ranging from simple steatosis to metabolic...
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An eyecare foundation model for clinical assistance: a randomized controlled trial - Nature Medicine

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By Tingyao Li, Zhouyu Guan, Yali Jia, Ping Zhang, Dian Zeng, Benjamin Sommer Thinggaard, Yukun Zhou, Huating Li, An Ran, Ying Zheng, Dingqiao Wang, Hongwei Ji, Youxin Chen, Xiangning Wang, Hua-Tao Xie, Weizhi Ma, Huazhu Fu, Wenxiao Wang, Andrzej Grzybowski, You Wu, Lee-Ling Lim, Carol Cheung, Pearse A. Keane, Ya Xing Wang, Yih-Chung Tham, Ching-Yu Cheng
| Nature Verified
Abstract In the context of an increasing need for clinical assessments of foundation models, we developed EyeFM, a multimodal vision–language eyecare copilot, and conducted a multifaceted evaluation, including retrospective validations, multicountry efficacy validation as a clinical copilot and a double-masked randomized controlled trial (RCT). EyeFM was pretrained on 14.5 million ocular images from five imaging modalities paired with clinical texts from global, multiethnic datasets.
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A deep learning system for detecting silent brain infarction and predicting stroke risk - Nature Biomedical Engineering

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By Yilan Wu, An Ran, Benjamin Sommer Thinggaard, Yiming Qin, Yuehua Li, Ruth Hogg, David Wright, Ya Xing Wang, Charumathi Sabanayagam, Ping Zhang, Xiaokang Yang, Lee-Ling Lim, Carol Cheung, Yih Chung Tham, Ching-Yu Cheng, Qionghai Dai, Weiping Jia, Huating Li, Tingyao Li
| Nature Verified
Abstract Current brain imaging to detect silent brain infarctions (SBIs) is not feasible for the general population. Here, to overcome this challenge, we developed a retinal image-based deep learning system, DeepRETStroke, to detect SBI and refine stroke risk. We use 895,640 retinal photographs to pretrain the DeepRETStroke system, which encodes a domain-specific foundation model for representing eye–brain connections.
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Associations between multiple metabolic biomarkers with steatotic liver disease subcategories: A 5-year Chinese cohort study

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By Hongli Chen, Siyu M. Chen, Dan Liu, Yebei Liang, Huating Li, Yuqian Bao, Zhijun Zhu, Keqing Dong, Liang Feng, Di Cheng, Li Wei, Weiping Jia, Fusong Jiang
| Cell Reports Medicine Verified
Keywords NAFLD MASLD MetALD ALD retinol-binding protein 4 fibroblast growth factor 21 adiponectin osteocalcin cohort study Introduction Non-alcoholic fatty liver disease (NAFLD) encompasses a spectrum of liver conditions ranging from hepatic steatosis to steatohepatitis, fibrosis, and cirrhosis, affecting approximately one-quarter of adults worldwide.1 Recently, the NAFLD nomenclature consensus group underscored the need for unified global nomenclature to improve disease management strategies...
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Integrated image-based deep learning and language models for primary diabetes care - Nature Medicine

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By Zhouyu Guan, Lee-Ling Lim, Li Chen, Xiaodong Sun, Xiangning Wang, Ruhan Liu, Ya Xing Wang, Truong Nguyen, Trường Nguyễn, Wenyong Huang, Carolyn Shan-Yeu Tien, Yiming Qin, Ling Dai, Weizhi Ma, Xiaokang Yang, Alicia Jenkins, Yong Mong Bee, Rafael Simó, Pearse A. Keane, Ching-Yu Cheng, Weiping Jia, Yih-Chung Tham, Huating Li
| Nature Verified
Abstract Primary diabetes care and diabetic retinopathy (DR) screening persist as major public health challenges due to a shortage of trained primary care physicians (PCPs), particularly in low-resource settings.
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Resistant starch intake facilitates weight loss in humans by reshaping the gut microbiota - Nature Metabolism

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By Huating Li, Jun Li, Yueqiong Ni, Petia Kovatcheva-Datchary, Ping Li, Jianping Ye, Yuqian Bao, Guowang Xu, Xinyu Liu, Gianni Panagiotou, Aimin Xu
| Nature Verified
Abstract Emerging evidence suggests that modulation of gut microbiota by dietary fibre may offer solutions for metabolic disorders. In a randomized placebo-controlled crossover design trial (ChiCTR-TTRCC-13003333) in 37 participants with overweight or obesity, we test whether resistant starch (RS) as a dietary supplement influences obesity-related outcomes.
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A deep learning system for predicting time to progression of diabetic retinopathy - Nature Medicine

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By Ruhan Liu, Xiangning Wang, Zhouyu Guan, Anran Ran, Haoxuan Che, Hao Chen, Xiaodong Sun, Ya Xing Wang, Dinggang Shen, Yih-Chung Tham, Ching-Yu Cheng, Huating Li
| Nature Verified
Abstract Diabetic retinopathy (DR) is the leading cause of preventable blindness worldwide. The risk of DR progression is highly variable among different individuals, making it difficult to predict risk and personalize screening intervals. We developed and validated a deep learning system (DeepDR Plus) to predict time to DR progression within 5 years solely from fundus images. First, we used 717,308 fundus images from 179,327 participants with diabetes to pretrain the system.
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New evidence for the effect of type 2 diabetes and glycemic traits on testosterone levels: a two-sample Mendelian randomization study

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By Carmine Gazzaruso, Mayank Choubey, Huating Li, Swayamsidha Mangaraj
| Frontiers
Introduction With the improvement of nutritional status, type 2 diabetes mellitus has gradually become one of the major threats to human health (1). The number of adults with diabetes increased from 108 million to 422 million between 1980 and 2014 (2), with type 2 diabetes accounting for more than 90% of these cases (3). Diabetes has become one of the top three diseases in the world, and the global prevalence is increasing (4).
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Prevalence of ideal cardiovascular health and its relationship with relative handgrip strength in rural northeast China

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By Clas-Håkan Nygård, Yuexing Liu, Huating Li
| Frontiers
1. Introduction In 2019, there were an estimated 523 million cases of cardiovascular disease (CVD) and 18.6 million CVD-related deaths globally; thus, CVD remains an important cause of health problems worldwide (1). It has been the major cause of death in China, and the proportion of deaths caused by CVDs continues to increase, particularly in rural populations (2). Studies on CVD risk in rural China demonstrate an alarmingly high prevalence of hypertension, dyslipidemia, and metabolic syndrome.
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