M
Mingqian Huang
Researcher at Icahn School of Medicine at Mount Sinai
Publications - 14
Citations - 5564
Mingqian Huang is an academic researcher from Icahn School of Medicine at Mount Sinai. The author has contributed to research in topics: Medicine & Internal medicine. The author has an hindex of 6, co-authored 7 publications receiving 4004 citations.
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Journal ArticleDOI
CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV).
Michael H. Chung,Adam Bernheim,Xueyan Mei,Ning Zhang,Mingqian Huang,Xianjun Zeng,Jiufa Cui,Wenjian Xu,Yang Yang,Zahi A. Fayad,Adam Jacobi,Kunwei Li,Shaolin Li,Hong Shan +13 more
TL;DR: In this retrospective case series, chest CT scans of 21 symptomatic patients from China infected with the 2019 novel coronavirus were reviewed, with emphasis on identifying and characterizing the most common findings.
Journal ArticleDOI
Chest CT Findings in Coronavirus Disease-19 (COVID-19): Relationship to Duration of Infection.
Adam Bernheim,Xueyan Mei,Mingqian Huang,Yang Yang,Zahi A. Fayad,Ning Zhang,Kaiyue Diao,Bin Lin,Xiqi Zhu,Kunwei Li,Shaolin Li,Hong Shan,Adam Jacobi,Michael H. Chung +13 more
TL;DR: With a longer time after the onset of symptoms, CT findings were more frequent, including consolidation, bilateral and peripheral disease, greater total lung involvement, linear opacities, “crazy-paving” pattern and the “reverse halo” sign.
Journal ArticleDOI
Artificial intelligence-enabled rapid diagnosis of patients with COVID-19.
Xueyan Mei,Hao-Chih Lee,Kaiyue Diao,Mingqian Huang,Bin Lin,Chenyu Liu,Zongyu Xie,Yixuan Ma,Philip M. Robson,Michael H. Chung,Adam Bernheim,Venkatesh Mani,Claudia Calcagno,Kunwei Li,Shaolin Li,Hong Shan,Jian Lv,Tongtong Zhao,Junli Xia,Qihua Long,Sharon Steinberger,Adam Jacobi,Timothy W. Deyer,Marta Luksza,Fang Liu,Brent P. Little,Zahi A. Fayad,Yang Yang +27 more
TL;DR: Artificial intelligence algorithms integrating chest CT findings with clinical symptoms, exposure history and laboratory testing to rapidly diagnose patients who are positive for COVID-19 with similar accuracy as compared to a senior radiologist.
Journal ArticleDOI
CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19).
Kunwei Li,Yijie Fang,Wenjuan Li,Cunxue Pan,Peixin Qin,Yinghua Zhong,Xueguo Liu,Mingqian Huang,Yuting Liao,Shaolin Li +9 more
TL;DR: The proportion of clinical mild-type patients with COVID-19 was relatively high; CT was not suitable for independent screening tool; the CT visual quantitative analysis has high consistency and can reflect the clinical classification of CO VID-19.
Posted ContentDOI
Artificial intelligence-enabled rapid diagnosis of COVID-19 patients.
Xueyan Mei,Hao-Chih Lee,Kaiyue Diao,Mingqian Huang,Bin Lin,Chenyu Liu,Zongyu Xie,Yixuan Ma,Philip M. Robson,Michael H. Chung,Adam Bernheim,Venkatesh Mani,Claudia Calcagno,Kunwei Li,Shaolin Li,Hong Shan,Jian Lv,Tongtong Zhao,Junli Xia,Qihua Long,Sharon Steinberger,Adam Jacobi,Timothy W. Deyer,Marta Luksza,Fang Liu,Brent P. Little,Zahi A. Fayad,Yang Yang +27 more
TL;DR: Artificial intelligence algorithms are used to integrate chest CT findings with clinical symptoms, exposure history, and laboratory testing to rapidly diagnose COVID-19 positive patients and improved the detection of RT-PCR positive CO VID-19 patients who presented with normal CT scans.