Research Article
Review of Covid-19 Diagnosis Techniques Combined with Machine Learning and AI Analysis
@INPROCEEDINGS{10.1007/978-3-030-94182-6_41, author={Xiao-Wei Gu and Shu-Wen Chen and Xuan Tong and Hui-Shen Yan and Lu Chen and Si-Ye Wu}, title={Review of Covid-19 Diagnosis Techniques Combined with Machine Learning and AI Analysis}, proceedings={IoT and Big Data Technologies for Health Care. Second EAI International Conference, IoTCare 2021, Virtual Event, October 18-19, 2021, Proceedings, Part II}, proceedings_a={IOTCARE PART 2}, year={2022}, month={6}, keywords={COVID-19 Medical image Chest CT CXR Deep learning}, doi={10.1007/978-3-030-94182-6_41} }- Xiao-Wei Gu
Shu-Wen Chen
Xuan Tong
Hui-Shen Yan
Lu Chen
Si-Ye Wu
Year: 2022
Review of Covid-19 Diagnosis Techniques Combined with Machine Learning and AI Analysis
IOTCARE PART 2
Springer
DOI: 10.1007/978-3-030-94182-6_41
Abstract
The pandemic of coronavirus disease 2019 (COVID-19) is rapidly spreading all over the world. In order to reduce the workload of doctors, chest X-ray (CXR) and chest computed tomography (CT) scans are playing a major role in the detection and following-up of COVID-19 symptoms. Artificial intelligence (AI) technology based on machine learning and deep learning has significantly upgraded recently medical image screening tools, therefore, medical specialists can make clinical decisions more efficiently on COVID-19 infection cases, providing the best protection to patients as soon as possible. This paper tries to cover the latest progress of automated medical imaging diagnosis techniques involved with COVID-19, including image acquisition, segmentation, diagnosis, and follow-up. This paper focuses on the combination of X-ray, CT scan with AI, especially the deep-learning technique, all of which can be widely used in the frontline hospitals to fight against COVID-19.
