Bangsheng Jiang
Jinan University
4 Papers
15 Citations
Bangsheng Jiang is an academic researcher from Jinan University. The author has contributed to research in topics: Medicine & Rural area. The author has an hindex of 3, co-authored 4 publications.
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Papers
Artificial Intelligence Versus Clinicians in Disease Diagnosis: Systematic Review.
Jiayi Shen,Jiayi Shen,Casper J. P. Zhang,Bangsheng Jiang,Jiebin Chen,Jian Song,Zherui Liu,Zonglin He,Sum Yi Wong,Po-Han Fang,Wai-Kit Ming +10 more
TL;DR: Current AI development has a diagnostic performance that is comparable with medical experts, especially in image recognition-related fields, and can be extended to other types of medical imaging such as magnetic resonance imaging and other medical practices unrelated to images.
An Innovative Artificial Intelligence–Based App for the Diagnosis of Gestational Diabetes Mellitus (GDM-AI): Development Study
Jiayi Shen,Jiayi Shen,Jiebin Chen,Zequan Zheng,Jiabin Zheng,Zherui Liu,Jian Song,Sum Yi Wong,Wang Xiaoling,Huang Mengqi,Po-Han Fang,Bangsheng Jiang,Winghei Tsang,Zonglin He,Taoran Liu,Babatunde Akinwunmi,Babatunde Akinwunmi,Chi Chiu Wang,Casper J. P. Zhang,Jian Huang,Wai-Kit Ming +20 more
TL;DR: This study proved that SVM can achieve accurate diagnosis with less operation cost and higher efficacy in GDM diagnosis, and shows the app has a promising future in improving the quality of maternal health for pregnant women, precision medicine, and long-distance medical care.
An Innovative Artificial Intelligence Application in Diseases Diagnosis: An Opportunity to Improve Maternal Health Care in Underdeveloped Rural Areas (Preprint)
Patent
Food nutrition constituent detecting method and system based on binocular camera
Zherui Liu,Ming Weijie,Yang Xiqi,He Yi,Huang Xinyi,Jiebin Chen,Peng Junhao,Shen Jiayi,Sui Minggang,Wu Hongzhang,Zhang Chunye,Li Jingzhen,Fang Bohan,Sun Yimeng,Bangsheng Jiang,Huang Mengqi,Ren Weida,Wang Xiaoling,Gong Song,He Zonglin,Wu Jialin,Feng Yaxuan,Jian Song,Lyu Yin,Chen Jieying,Xue Dongmei,Lin Ruqing,Lin Xiaoli +27 more
- 16 Nov 2018
TL;DR: In this article, a food nutrition constituent detecting method and system based on a binocular camera is presented, in which a first training set is constructed and a first artificial intelligence model capable of recognizing a food name and a food position in a picture is trained; a camera is used to shoot pictures, the first Artificial Intelligence model identifies the food name in each picture, the food names and the food positions in each two pictures shot each time by the camera form a training sample and a second training set was formed, and the second Artificial Intelligence Model capable of identifying the quality of food in
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