On the Early Detection of COVID19 using Advanced Machine Learning Techniques: A Review

Siddiqui, Mohammed A.; Ali, Mohammed; Deriche, Mohamed

doi:10.1109/ssd52085.2021.9429345

“…The paper's machine learning section examines works by researchers who have utilized machine learning techniques to detect covid 19. SVM appeared to be the most widely used technique, as it was utilized in [75,77,78,96,99,101,119]. Many articles [78,95,98,99,101,119] used KNN because it produced good results.…”

Section: Discussionmentioning

confidence: 99%

“…SVM appeared to be the most widely used technique, as it was utilized in [75,77,78,96,99,101,119]. Many articles [78,95,98,99,101,119] used KNN because it produced good results. In addition, we applied our own algorithm to predict COVID-19 in Lung CT scan pictures.…”

Section: Discussionmentioning

confidence: 99%

“…They achieved accuracy of 86.73 percent and sensitivity of 87.27 percent for COVID-19 patients, 68.42 percent for CAP patients, and 100 percent for normal patients using flip-and-shift augmentation, Ran-dAugment, AdaBoost, EfficientNet, K-means, and Ima-geNet. A review study on machine learning approaches was offered by Siddiqui et al in 2021 [101]. SVM, KNN, Logistic regression, and LSTM were the machine learning algorithms employed.…”

Section: Methods For Machine Learning Techniquementioning

confidence: 99%

See 1 more Smart Citation

Soft computing and image processing techniques for COVID-19 prediction in lung CT scan images

Appari¹,

Kanojia²

2022

HIS

View full text Add to dashboard Cite

COVID-19 is a contagious respiratory illness that can be passed from person to person. Because it affects the lungs, damages blood arteries, and causes cardiac problems, COVID-19 must be diagnosed quickly. The reverse transcriptase polymerase chain reaction (RT-PCR) is a method for detecting COVID-19, but it is time consuming and labor expensive, as well as putting the person collecting the sample in danger. As a result, clinicians prefer to use CT scan and Xray images. COVID-19 classification can be done manually, however AI makes the process go faster. AI approaches include image processing, machine learning, and deep learning. An AI model is required to diagnose COVID-19, and a dataset is necessary to train that model. A dataset consists of the information from which the model is trained. This paper consists of the review of different image processing, machine learning and deep learning papers proposed by different researchers. As well as models based on deep learning and pretrained model using gradient boosting algorithm The goal of this paper is to provide information for future researchers to work with.

show abstract

“…To accelerate the detection and classification of CAP and COVID-19 in clinical settings, artificial intelligence (AI) algorithms (Wang et al, 2022;Siddiqui et al, 2021;Mondal et al, 2021;Hussain et al, 2022) have recently been introduced and have shown great promise, which can reduce the burden of expert radiologists/clinicians to detect and assess the severity of pneumonia. Several studies recently reviewed these AI techniques used in COVID-19 detection and analysis in ultrasound (Zhao and Lediju Bell, 2022;Wang et al, 2022;Alzubaidi et al, 2021;Siddiqui et al, 2021;Mondal et al, 2021;Liu, 2021;Gudigar et al, 2021;Ulhaq et al, 2020). Most of these review works have been performed between late 2019 and early 2022 and mainly focused on discussing AI techniques used in different ultrasound-based COVID-19 studies.…”

Section: Ai For Ultrasound-based Covid-2019 Managementmentioning

confidence: 99%

Ultrasound-Based AI for COVID-19 Detection: A Comprehensive Review of Public and Private Lung Ultrasound Datasets and Studies

Morshed¹,

Shihab²,

Jahin³

et al. 2023

Preprint

0

View full text Add to dashboard Cite

The COVID-19 pandemic has affected millions of people globally, with respiratory organs being strongly affected in individuals with comorbidities. Medical imaging-based diagnosis and prognosis have become increasingly popular in clinical settings to detect COVID-19 lung infections. Among various medical imaging modalities, ultrasound stands out as low-cost, mobile, and radiation-safe imaging technology. In this comprehensive review, we focus on ultrasound-based AI studies for COVID-19 detection that use public or private lung ultrasound datasets. We surveyed articles that used publicly available lung ultrasound datasets for COVID-19 and reviewed publicly available datasets and organize ultrasound-based AI studies per dataset. We analyzed and tabulated studies in several dimensions, such as data preprocessing, AI models, cross-validation, and evaluation criteria. In total, we reviewed 42 articles, where 28 articles used public datasets, and the rest used private data. Our findings suggest that ultrasound-based AI studies for the detection of COVID-19 have great potential for clinical use, especially for children and pregnant women. Our review also provides a useful summary for future researchers and clinicians who may be interested in the field.

show abstract

“…To accelerate the detection and classification of CAP and COVID-19 in clinical settings, artificial intelligence (AI) algorithms [4,[25][26][27] have recently been introduced and have shown great promise, which may lessen the burden of expert radiologists/clinicians to detect and assess the severity of pneumonia. Several studies recently reviewed these AI techniques used in COVID-19 detection and analysis in ultrasound [4,25,26,[28][29][30][31][32]. Most of these review works have been performed between late 2019 and early 2022 and mainly focused on discussing AI techniques used in different ultrasound-based COVID-19 studies.…”

Section: Ai For Ultrasound-based Covid-2019 Managementmentioning

confidence: 99%

Ultrasound-Based AI for COVID-19 Detection: A Comprehensive Review of Public and Private Lung Ultrasound Datasets and Studies

Morshed¹,

Shihab²,

Jahin³

et al. 2023

Preprint

1

0

View full text Add to dashboard Cite

The COVID-19 pandemic has affected millions of people globally, with respiratory organs being strongly affected in individuals with comorbidities. Medical imaging-based diagnosis and prognosis have become increasingly popular in clinical settings to detect COVID-19 lung infections. Among various medical imaging modalities, ultrasound stands out as low-cost, mobile, and radiation-safe imaging technology. In this comprehensive review, we focus on ultrasound-based AI studies for COVID-19 detection that use public or private lung ultrasound datasets. We surveyed articles that used publicly available lung ultrasound datasets for COVID-19 and reviewed publicly available datasets and organize ultrasound-based AI studies per dataset. We analyzed and tabulated studies in several dimensions, such as data preprocessing, AI models, cross-validation, and evaluation criteria. In total, we reviewed 42 articles, where 28 articles used public datasets, and the rest used private data. Our findings suggest that ultrasound-based AI studies for the detection of COVID-19 have great potential for clinical use, especially for children and pregnant women. Our review also provides a useful summary for future researchers and clinicians who may be interested in the field.

show abstract

On the Early Detection of COVID19 using Advanced Machine Learning Techniques: A Review

Cited by 10 publications

References 19 publications

Soft computing and image processing techniques for COVID-19 prediction in lung CT scan images

Soft computing and image processing techniques for COVID-19 prediction in lung CT scan images

Ultrasound-Based AI for COVID-19 Detection: A Comprehensive Review of Public and Private Lung Ultrasound Datasets and Studies

Ultrasound-Based AI for COVID-19 Detection: A Comprehensive Review of Public and Private Lung Ultrasound Datasets and Studies

Contact Info

Product

Resources

About