A survey of machine learning techniques for detecting and diagnosing COVID-19 from imaging

作     者：Aishwarza Panday Muhammad Ashad Kabir Nihad Karim Chowdhury Aishwarza Panday;Muhammad Ashad Kabir;Nihad Karim Chowdhury

作者机构：Department of Computer Science&EngineeringStamford UniversityDhaka 1217Bangladesh School of Computing and MathematicsCharles Sturt UniversityNSW 2795Australia Department of Computer Science&EngineeringUniversity of ChittagongChittagong 4349Bangladesh 

出 版 物：《Quantitative Biology》 (定量生物学（英文版）)

年 卷 期：2022年第10卷第2期

页      面：188-207页

核心收录：

学科分类：12[管理学] 08[工学] 0710[理学-生物学] 0831[工学-生物医学工程（可授工学、理学、医学学位）] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 1002[医学-临床医学] 081104[工学-模式识别与智能系统] 100201[医学-内科学(含：心血管病、血液病、呼吸系病、消化系病、内分泌与代谢病、肾病、风湿病、传染病)] 0835[工学-软件工程] 0701[理学-数学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 10[医学] 

主　　题：COVID-19 machine learning deep learning detection classification diagnosing X-ray CT scan 

摘      要：Background: Due to the limited availability and high cost of the reverse transcription-polymerase chain reaction (RT- PCR) test, many studies have proposed machine learning techniques for detecting COVID-19 from medical imaging. The purpose of this study is to systematically review, assess and synthesize research articles that have used different machine learning techniques to detect and diagnose COVID-19 from chest X-ray and CT scan ***: A structured literature search was conducted in the relevant bibliographic databases to ensure that the survey solely centered on reproducible and high-quality research. We selected papers based on our inclusion ***: In this survey, we reviewed 98 articles that fulfilled our inclusion criteria. We have surveyed a complete pipeline of chest imaging analysis techniques related to COVID-19, including data collection, pre-processing, feature extraction, classification, and visualization. We have considered CT scans and X-rays as both are widely used to describe the latest developments in medical imaging to detect ***: This survey provides researchers with valuable insights into different machine learning techniques and their performance in the detection and diagnosis of COVID-19 from chest imaging. At the end, the challenges and limitations in detecting COVID-19 using machine learning techniques and the future direction of research are discussed.