| |
Original Artikel |
Datum |
Titel |
Autoren Max. 6 Autoren |
| 1 |
[GO] |
2024―Okt―21 |
Trends in CT examination utilization in the emergency department during and after the COVID-19 pandemic |
Felix Kempter, Tobias Heye, Jan Vosshenrich, Benjamin Ceresa, Dominik Jäschke |
| 2 |
[GO] |
2024―Aug―09 |
Adaptive Mish activation and ranger optimizer-based SEA-ResNet50 model with explainable AI for multiclass classification of COVID-19 chest X-ray images |
S. R. Sannasi Chakravarthy, N. Bharanidharan, C. Vinothini, Venkatesan Vinoth Kumar, T. R. Mahesh, Suresh Guluwadi |
| 3 |
[GO] |
2024―Mai―27 |
Fog-based deep learning framework for real-time pandemic screening in smart cities from multi-site tomographies |
Ibrahim Alrashdi |
| 4 |
[GO] |
2024―Feb―27 |
Automated machine learning for the identification of asymptomatic COVID-19 carriers based on chest CT images |
Minyue Yin, Chao Xu, Jinzhou Zhu, Yuhan Xue, Yijia Zhou, Yu He, Jiaxi Lin, Lu Liu, Jingwen Gao, Xiaolin Liu, Dan Shen, Cuiping Fu |
| 5 |
[GO] |
2024―Jan―02 |
Detection of COVID-19 using edge devices by a light-weight convolutional neural network from chest X-ray images |
Sohamkumar Chauhan, Damoder Reddy Edla, Vijayasree Boddu, M Jayanthi Rao, Ramalingaswamy Cheruku, Soumya Ranjan Nayak, Sheshikala Martha, Kamppa Lavanya, Tsedenya Debebe Nigat |
| 6 |
[GO] |
2023―Nov―30 |
Radiographic patterns and severity scoring of COVID-19 pneumonia in children: a retrospective study |
Jumlong Saelim, Supika Kritsaneepaiboon, Vorawan Charoonratana, Puttichart Khantee |
| 7 |
[GO] |
2023―Nov―10 |
A radiomics based approach using adrenal gland and periadrenal fat CT images to allocate COVID-19 health care resources fairly |
Mudan Zhang, Xuntao Yin, Wuchao Li, Yan Zha, Xianchun Zeng, Xiaoyong Zhang, Jingjing Cui, Zhong Xue, Rongpin Wang, Chen Liu |
| 8 |
[GO] |
2023―Okt―02 |
TVFx - CoVID-19 X-Ray images classification approach using neural networks based feature thresholding technique |
Syed Thouheed Ahmed, Syed Muzamil Basha, Muthukumaran Venkatesan, Sandeep Kumar Mathivanan, Saurav Mallik, Najah Alsubaie, Mohammed S. Alqahtani |
| 9 |
[GO] |
2023―Jun―15 |
COV-MobNets: a mobile networks ensemble model for diagnosis of COVID-19 based on chest X-ray images |
Mohammad Amir Eshraghi, Ahmad Ayatollahi, Shahriar Baradaran Shokouhi |
| 10 |
[GO] |
2023―Feb―06 |
Role of chest CT scan in patients with preexisting cancer and COVID-19 pneumonia |
Faezeh Khorasanizadeh, Soori Kaviani, Shadi Salamroudi, Monireh Sadat Seyyedsalehi, Masoumeh Gity, Kazem Zendehdel |
| 11 |
[GO] |
2022―Nov―29 |
Analysis of CT signs, radiomic features and clinical characteristics for delta variant COVID-19 patients with different vaccination status |
Huanhuan Wei, Zehua Shao, Jianqing Tai, Fangfang Fu, Chuanjian Lv, Zhiping Guo, Yaping Wu, Lijuan Chen, Yan Bai, Qingxia Wu, Xuan Yu, Xinling Mu, Fengmin Shao, Meiyun Wang |
| 12 |
[GO] |
2022―Aug―12 |
Correlation of CT-derived pectoralis muscle status and COVID-19 induced lung injury in elderly patients |
Pei Ying-hao, Zhang Hai-dong, Fang Yuan, Liu Yong-kang, Liang Sen, Xu Wei-long, Yang Yu-shan, Zhu Jun-feng, Zhou Hai-qi, Jiang Hua |
| 13 |
[GO] |
2022―Jul―30 |
Detecting COVID-19 patients via MLES-Net deep learning models from X-Ray images |
Wei Wang, Yongbin Jiang, Xin Wang, Peng Zhang, Ji Li |
| 14 |
[GO] |
2022―Jul―20 |
Investigation of the relationship of CO-RADS and CT patterns with laboratory parameters in COVID-19 patients and a new perspective on the total CT scoring system |
Nevin Aydin, Pinar Yildiz, Döndü Üsküdar Cansu, Elif Gündogdu, Rüya Mutluay, Göknur Yorulmaz, Melisa Sahin Tekin, Evin Kocaturk, İ. Özkan Alatas, Elif Doyuk Kartal, Nurettin Erben, Gül Durmaz, Nilgun Kasifoglu, Tercan Us, Garip Sahin, Cengiz Bal, Senay Yilmaz, Cengiz Korkmaz |
| 15 |
[GO] |
2022―Jun―07 |
Evaluation of the models generated from clinical features and deep learning-based segmentations: Can thoracic CT on admission help us to predict hospitalized COVID-19 patients who will require intensive care? |
Mutlu Gülbay, Aliye Baştuğ, Erdem Özkan, Büşra Yüce Öztürk, Bökebatur Ahmet Raşit Mendi, Hürrem Bodur |
| 16 |
[GO] |
2022―Mrz―29 |
Performances of clinical characteristics and radiological findings in identifying COVID-19 from suspected cases |
Xuanxuan Li, Yajing Zhao, Yiping Lu, Yingyan Zheng, Nan Mei, Qiuyue Han, Zhuoying Ruan, Anling Xiao, Xiaohui Qiu, Dongdong Wang, Bo Yin |
| 17 |
[GO] |
2022―Feb―17 |
The application research of AI image recognition and processing technology in the early diagnosis of the COVID-19 |
Wenyu Chen, Ming Yao, Zhenyu Zhu, Yanbao Sun, Xiuping Han |
| 18 |
[GO] |
2022―Feb―06 |
Quantitative CT comparison between COVID-19 and mycoplasma pneumonia suspected as COVID-19: a longitudinal study |
Junzhong Liu, Yuzhen Wang, Guanghui He, Xinhua Wang, Minfeng Sun |
| 19 |
[GO] |
2021―Dez―13 |
Comparison of lung image quality between CT Ark and Brilliance 64 CT during COVID-19 |
Gonghua Dai, Jiying Duan, Liang Zheng, Miao He, Yanshan Dai, Mingming Zhang, Shuguang Chu |
| 20 |
[GO] |
2021―Nov―22 |
UMLF-COVID: an unsupervised meta-learning model specifically designed to identify X-ray images of COVID-19 patients |
Rui Miao, Xin Dong, Sheng-Li Xie, Yong Liang, Sio-Long Lo |
| 21 |
[GO] |
2021―Okt―21 |
GACDN: generative adversarial feature completion and diagnosis network for COVID-19 |
Qi Zhu, Haizhou Ye, Liang Sun, Zhongnian Li, Ran Wang, Feng Shi, Dinggang Shen, Daoqiang Zhang |
| 22 |
[GO] |
2021―Okt―04 |
RSNA and BSTI grading systems of COVID-19 pneumonia: comparison of the diagnostic performance and interobserver agreement |
Seyhmus Kavak, Recai Duymus |
| 23 |
[GO] |
2021―Feb―20 |
CT-based radiomics combined with signs: a valuable tool to help radiologist discriminate COVID-19 and influenza pneumonia |
Yilong Huang, Zhenguang Zhang, Siyun Liu, Xiang Li, Yunhui Yang, Jiyao Ma, Zhipeng Li, Jialong Zhou, Yuanming Jiang, Bo He |
| 24 |
[GO] |
2021―Feb―09 |
COVID-19 lung CT image segmentation using deep learning methods: U-Net versus SegNet |
Adnan Saood, Iyad Hatem |
| 25 |
[GO] |
2020―Okt―20 |
A model based on CT radiomic features for predicting RT-PCR becoming negative in coronavirus disease 2019 (COVID-19) patients |
Quan Cai, Si-Yao Du, Si Gao, Guo-Liang Huang, Zheng Zhang, Shu Li, Xin Wang, Pei-Ling Li, Peng Lv, Gang Hou, Li-Na Zhang |
| 26 |
[GO] |
2020―Okt―02 |
Nomogram to identify severe coronavirus disease 2019 (COVID-19) based on initial clinical and CT characteristics: a multi-center study |
Yixing Yu, Ximing Wang, Min Li, Lan Gu, Zongyu Xie, Wenhao Gu, Feng Xu, Yaxing Bao, Rongrong Liu, Su Hu, Mengjie Hu, Chunhong Hu |
| 27 |
[GO] |
2020―Aug―05 |
Dynamic changes of Chest CT follow-up in Coronavirus Disease-19 (COVID-19) pneumonia: relationship to clinical typing |
Nian Liu, Guanghong He, Xiongxiong Yang, Jianxin Chen, Jie Wu, Min Ma, Wenying Lu, Qiang Li, Tao Cheng, Xiaohua Huang |
| 28 |
[GO] |
2020―Jul―23 |
Analysis of 4 imaging features in patients with COVID-19 |
Jun Jin, De-hong Gao, Xin Mo, Si-ping Tan, Zhen-xia Kou, Yi-bo Chen, Jin-bo Cao, Wen-jing Chen, Ya-ming Zhang, Bing-qing Li, Kuan-long Huang, Bing-ren Xu, Xiao-li Tang, Yu-li Wang |
| 29 |
[GO] |
2020―Jun―23 |
CT findings of patients infected with SARS-CoV-2 |
Xiaoyang Wang, Chenbin Liu, Liang Hong, Cuiyun Yuan, Jiguang Ding, Qing Jia, Gangqiang Sun, Wenxian Peng, Qingfeng Sun |
| 30 |
[GO] |
2020―Jun―15 |
Imaging features of the initial chest thin-section CT scans from 110 patients after admission with suspected or confirmed diagnosis of COVID-19 |
Cheng-Juan Long, Ping Fang, Tie-Jun Song, Jing-Chao Zhang, Qing Yang |
| 31 |
[GO] |
2020―Mai―24 |
Application of CareDose 4D combined with Karl 3D technology in the low dose computed tomography for the follow-up of COVID-19 |
Jiawei Li, Xiao Wang, Xiaolu Huang, Fangxing Chen, Xuesong Zhang, Ying Liu, Guangzuo Luo, Xunhua Xu |
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