A Nonclinical Spectroscopic Approach for Diagnosing Covid-19: A Concise Perspective

Mir, Jan Mohammad; Khan, Mohd Washid; Shalla, Aabid H.; Maurya, R. C.

doi:10.1007/s10812-021-01238-9

Cited by 4 publications

(3 citation statements)

References 51 publications

(30 reference statements)

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“…However, machine learning algorithms can effectively learn and distinguish between the various associations observed in the parameters of regular blood tests. As a result, some initial efforts have begun to develop artificial intelligence methods for the diagnosis of COVID-19 and mortality from regular blood samples [19,[21][22][23]. In addition, there are also some research methods utilizing novel approaches to predict disease diagnosis [24][25][26].…”

Section: Introductionmentioning

confidence: 99%

An interpretable machine learning framework for diagnosis and prognosis of COVID-19

Fan,

Liu,

Sun

2023

PLoS ONE

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Coronaviruses have affected the lives of people around the world. Increasingly, studies have indicated that the virus is mutating and becoming more contagious. Hence, the pressing priority is to swiftly and accurately predict patient outcomes. In addition, physicians and patients increasingly need interpretability when building machine models in healthcare. We propose an interpretable machine framework(KISM) that can diagnose and prognose patients based on blood test datasets. First, we use k-nearest neighbors, isolated forests, and SMOTE to pre-process the original blood test datasets. Seven machine learning tools Support Vector Machine, Extra Tree, Random Forest, Gradient Boosting Decision Tree, eXtreme Gradient Boosting, Logistic Regression, and ensemble learning were then used to diagnose and predict COVID-19. In addition, we used SHAP and scikit-learn post-hoc interpretability to report feature importance, allowing healthcare professionals and artificial intelligence models to interact to suggest biomarkers that some doctors may have missed. The 10-fold cross-validation of two public datasets shows that the performance of KISM is better than that of the current state-of-the-art methods. In the diagnostic COVID-19 task, an AUC value of 0.9869 and an accuracy of 0.9787 were obtained, and ultimately Leukocytes, platelets, and Proteina C reativa mg/dL were found to be the most indicative biomarkers for the diagnosis of COVID-19. An AUC value of 0.9949 and an accuracy of 0.9677 were obtained in the prognostic COVID-19 task and Age, LYMPH, and WBC were found to be the most indicative biomarkers for identifying the severity of the patient.

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Section: Introductionmentioning

confidence: 99%

An interpretable machine learning framework for diagnosis and prognosis of COVID-19

Fan,

Liu,

Sun

2023

PLoS ONE

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“…Wood et al [51] investigated these biomarker in saliva for COVID-19 detection. Mir et al [52] indicated that ATR-FTIR analysis was cost-effective since it took less time and required no reagent. Significant vibrational modes of biological materials generally fell within the 1800-900 cm -1 band, which was referred to as the "bio fingerprint" zone.…”

Section: Covid-19 Virus Detection Using Infrared Spectroscopymentioning

confidence: 99%

Spectroscopic methods for COVID-19 detection and early diagnosis

Bedair

Okasha

Mansour

2022

Virol J

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The coronavirus pandemic is a worldwide hazard that poses a threat to millions of individuals throughout the world. This pandemic is caused by the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), which was initially identified in Wuhan, China's Hubei provincial capital, and has since spread throughout the world. According to the World Health Organization's Weekly Epidemiological Update, there were more than 250 million documented cases of coronavirus infections globally, with five million fatalities. Early detection of coronavirus does not only reduce the spread of the virus, but it also increases the chance of curing the infection. Spectroscopic techniques have been widely used in the early detection and diagnosis of COVID-19 using Raman, Infrared, mass spectrometry and fluorescence spectroscopy. In this review, the reported spectroscopic methods for COVID-19 detection were discussed with emphasis on the practical aspects, limitations and applications.

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“…This technique has found a wide range of use for detecting the novel coronavirus infection. Like drug repurposing for COVID-19, instrumental repurposing in the form of Envelope protein Hemagglutin Spike protein RT-PCR which was earlier used for diagnosing Ebola and Zika viral infections supported to a maximum in diagnosing COVID-19 infection [23].…”

Section: Covid-19 Diagnosismentioning

confidence: 99%

A Systematic Biomedical Perspective on COVID-19 Pandemic: From Detection to Vaccination

Mir¹,

Wani²,

John³

et al. 2021

Advanced Chemicobiology Research

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The year 2020 witnessed a challenging period for worldwide scientists to find a suitable treatment for the deadly novel coronavirus infectious disease-2019 (nCOVID or COVID-19). The entire scientific community has been eager to develop effective vaccines and medicine against COVID-19. Despite the fact of administration of vaccination in several countries across the globe, the drug repurposing of several antiviral compounds yielded satisfactory results in recovering the affected people. As it is a known fact that vaccination alone is not the end of this pandemic, but the final treatment in terms of drugs/medicines specific to this disease is yet underway. It looks worthy to present a literature survey based on the collective information related to the drug candidates that have been repurposed, the respective theoretical evaluation, and some of the effective therapies usable in treating COVID-19. This review also describes diagnosis and vaccination availed so far. Therefore, a sequential literature extract is hereby presented starting from the detection, going through virulence, drug repositioning, virtual screening, and the final destination in the form of vaccine development. A few commercially available vaccines have also been introduced. Based on the survey, it is clear that the entire world must remain alert for any future pandemic keeping in view the successful and unsuccessful efforts practiced in the COVID-19 pandemic.

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A Nonclinical Spectroscopic Approach for Diagnosing Covid-19: A Concise Perspective

Cited by 4 publications

References 51 publications

An interpretable machine learning framework for diagnosis and prognosis of COVID-19

An interpretable machine learning framework for diagnosis and prognosis of COVID-19

Spectroscopic methods for COVID-19 detection and early diagnosis

A Systematic Biomedical Perspective on COVID-19 Pandemic: From Detection to Vaccination

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