|
Original Artikel |
Datum |
Titel |
Autoren Alle 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, et al. (+6) 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, et al. (+3) 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, et al. (+4) 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, et al. (+8) 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, et al. (+4) 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, et al. (+12) 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, et al. (+5) 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, et al. (+2) 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, et al. (+4) 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, et al. (+5) 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, et al. (+6) 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, et al. (+4) 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, et al. (+8) 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, et al. (+3) 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, et al. (+2) Guangzuo Luo, Xunhua Xu |