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Original Artikel |
Datum |
Titel |
Autoren Alle Autoren |
| 1 |
[GO] |
2025―Sep―02 |
MDSTransUNet: Multi-scale Deep Supervised Transformer U-Net for COVID-19 Lung Tissue and Infection Segmentation |
Yidan Yan, Beibei Hou, Junding Sun |
| 2 |
[GO] |
2024―Jan―26 |
Automated Detection and Forecasting of COVID-19 using Deep Learning Techniques: A Review |
Afshin Shoeibi, Marjane Khodatars, Mahboobeh Jafari, Navid Ghassemi, Delaram Sadeghi, Parisa Moridian, et al. (+9) Ali Khadem, Roohallah Alizadehsani, Sadiq Hussain, Assef Zare, Zahra Alizadeh Sani, Fahime Khozeimeh, Saeid Nahavandi, U. Rajendra Acharya, Juan M. Gorriz |
| 3 |
[GO] |
2023―Mrz―08 |
Multi-weight Susceptible-Infected Model for Predicting COVID-19 in China |
Jun Zhang, Nanning Zheng, Mingyu Liu, Dingyi Yao, Yusong Wang, Jianji Wang, Jingmin Xin |
| 4 |
[GO] |
2023―Jan―12 |
Towards an ML-Based Semantic IoT for Pandemic Management: A Survey of Enabling Technologies for COVID-19 |
Rita Zgheib, Ghazar Chahbandarian, Firuz Kamalov, Haythem El Messiry, Ahmed Al-Gindy |
| 5 |
[GO] |
2022―Dez―09 |
Learning Label Diffusion Maps for Semi-Automatic Segmentation of Lung CT Images with COVID-19 |
Aldimir Bruzadin, Maurílio Boaventura, Marilaine Colnago, Rogério Galante Negri, Wallace Casaca |
| 6 |
[GO] |
2022―Sep―08 |
Deep Learning for Covid-19 Forecasting: state-of-the-art review. |
Firuz Kamalov, Khairan Rajab, Aswani Cherukuri, Ashraf Elnagar, Murodbek Safaraliev |
| 7 |
[GO] |
2022―Jun―23 |
A Semi-Supervised Learning Approach for COVID-19 Detection from Chest CT Scans |
Yong Zhang, Li Su, Zhenxing Liu, Wei Tan, Yinuo Jiang, Cheng Cheng |
| 8 |
[GO] |
2022―Feb―16 |
Multi-modal trained artificial intelligence solution to triage chest X-Ray for COVID-19 using pristine ground-truth, versus radiologists |
Tao Tan, Bipul Das, Ravi Soni, Mate Fejes, Hongxu Yang, Sohan Ranjan, et al. (+11) Daniel Attila Szabo, Vikram Melapudi, K.S. Shriram, Utkarsh Agrawal, Laszlo Rusko, Zita Herczeg, Barbara Darazs, Pal Tegzes, Lehel Ferenczi, Rakesh Mullick, Gopal Avinash |
| 9 |
[GO] |
2022―Feb―10 |
Comparison and Ensemble of 2D and 3D Approaches for COVID-19 Detection in CT Images |
Sara Atito Ali Ahmed, Mehmet Can Yavuz, Mehmet Umut Sen, Fatih Gulsen, Onur Tutar, Bora Korkmazer, et al. (+6) Cesur Samanci, Sabri Şirolu, Rauf Hamid, Ali Ergun Eryürekli, Toghrul Mammadov, Berrin Yanikoglu |
| 10 |
[GO] |
2022―Jan―21 |
A Fuzzy-enhanced Deep Learning Approach for Early Detection of Covid-19 Pneumonia from Portable Chest X-Ray Images |
Cosimo Ieracitano, Nadia Mammone, Mario Versaci, Giuseppe Varone, Abder-Rahman Ali, Antonio Armentano, et al. (+10) Grazia Calabrese, Anna Ferrarelli, Lorena Turano, Carmela Tebala, Zain Hussain, Zakariya Sheikh, Aziz Sheikh, Giuseppe Sceni, Amir Hussain, Francesco Carlo Morabito |
| 11 |
[GO] |
2021―Okt―22 |
Digital twins based on bidirectional LSTM and GAN for modelling the COVID-19 pandemic |
César Quilodrán-Casas, Vinicius L.S. Silva, Rossella Arcucci, Claire E. Heaney, YiKe Guo, Christopher C. Pain |
| 12 |
[GO] |
2021―Okt―20 |
Time series predicting of COVID-19 based on deep learning |
Madini O. Alassafi, Mutasem Jarrah, Reem Alotaibi |
| 13 |
[GO] |
2021―Jun―16 |
Fusion of Intelligent Learning for COVID-19: A State-of-the-Art Review and Analysis on Real Medical Data |
Weiping Ding, Janmenjoy Nayak, H. Swapnarekha, Ajith Abraham, Bighnaraj Naik, Danilo Pelusi |
| 14 |
[GO] |
2021―Jun―07 |
Deep Supervised Learning Using Self-Adaptive Auxiliary Loss for COVID-19 Diagnosis from Imbalanced CT Images |
Kai Hu, Yingjie Huang, Wei Huang, Hui Tan, Zhineng Chen, Zheng Zhong, et al. (+3) Xuanya Li, Yuan Zhang, Xieping Gao |
| 15 |
[GO] |
2021―Mrz―19 |
MANet: A Two-stage Deep Learning Method for Classification of COVID-19 from Chest X-ray Images |
Yujia Xu, Hak-Keung Lam, Guangyu Jia |
| 16 |
[GO] |
2020―Dez―30 |
ResGNet-C: A graph convolutional neural network for detection of COVID-19 |
Xiang Yu, Siyuan Lu, Lili Guo, Shui-Hua Wang, Yu-Dong Zhang |
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