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Patrick Robinson
Researcher at University of North Carolina at Charlotte
Publications - 13
Citations - 112
Patrick Robinson is an academic researcher from University of North Carolina at Charlotte. The author has contributed to research in topics: Medicine & Public health. The author has an hindex of 4, co-authored 9 publications receiving 41 citations.
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Journal ArticleDOI
Accurately Differentiating Between Patients With COVID-19, Patients With Other Viral Infections, and Healthy Individuals: Multimodal Late Fusion Learning Approach.
Ming Xu,Liu Ouyang,Lei Han,Kai Sun,Tingting Yu,Qian Li,Hua Tian,Lida Safarnejad,Hengdong Zhang,Yue Gao,Forrest Sheng Bao,Yuanfang Chen,Patrick Robinson,Yaorong Ge,Baoli Zhu,Jie Liu,Shi Chen +16 more
TL;DR: Wang et al. as discussed by the authors proposed a hybrid deep learning-machine learning framework to detect patients with COVID-19 using low-dimensional clinical and lab testing data, as well as high-dimensional computed tomography imaging data.
Journal ArticleDOI
An operational machine learning approach to predict mosquito abundance based on socioeconomic and landscape patterns
Shi Chen,Ari Whiteman,Ang Li,Tyler Rapp,Eric Delmelle,Gang Chen,Cheryl L. Brown,Patrick Robinson,Maren J. Coffman,Daniel Janies,Michael Dulin +10 more
TL;DR: In this article, three supervised learning models, k-nearest neighbor (kNN), artificial neural network (ANN), and support vector machine (SVM), were constructed, tuned, and evaluated using both continuous input factors and binary inputs.
Journal ArticleDOI
A Multimodality Machine Learning Approach to Differentiate Severe and Nonsevere COVID-19: Model Development and Validation.
Yuanfang Chen,Liu Ouyang,Forrest Sheng Bao,Qian Li,Lei Han,Lei Han,Hengdong Zhang,Hengdong Zhang,Baoli Zhu,Baoli Zhu,Baoli Zhu,Yaorong Ge,Patrick Robinson,Ming Xu,Ming Xu,Ming Xu,Jie Liu,Shi Chen +17 more
TL;DR: In this paper, a machine learning approach was used to understand COVID-19 more comprehensively, accurately differentiate severe and nonsevere clinical types based on multiple medical features, and provide reliable predictions of the clinical type of the disease.
Posted ContentDOI
Accurately Differentiating COVID-19, Other Viral Infection, and Healthy Individuals Using Multimodal Features via Late Fusion Learning
Xu Ming,Xu Ming,Liu Ouyang,Yan Gao,Yuanfang Chen,Yuanfang Chen,Tingting Yu,Qian Li,Kai Sun,Forrest Sheng Bao,Lida Safarnejad,Jing Wen,Chao Jiang,Tianyang Chen,Han Lei,Zhang Hengdong,Yue Gao,Yu Zhengmin,Liu Xiaowen,Tianyu Yan,Hebi Li,Patrick Robinson,Baoli Zhu,Jie Liu,Yang Liu,Zengli Zhang,Yaorong Ge,Shi Chen +27 more
TL;DR: This study recruited 214 confirmed COVID-19 patients, developed a deep learning model to extract a 10-feature high-level representation of the CT scans, and developed three machine learning models based on the 43 features combined from all three modalities to differentiate four classes at once.
Journal ArticleDOI
Trends in Public and Global Health Education among Nationally Recognized Undergraduate Liberal Arts Colleges in the United States.
TL;DR: The prevalence of public health and global health curricular offerings appear to be increasing in terms of undergraduate curricula and in the context of liberal arts education in the United States, with more students seeking formal curricular or IS PH degree pathways.