A LIME-Based Explainable Machine Learning Model for Predicting the Severity Level of COVID-19 Diagnosed Patients

The fast and seemingly uncontrollable spread of the novel coronavirus disease (COVID-19) poses great challenges to an already overloaded health system worldwide. It thus exemplifies an urgent need for fast and effective triage. Such triage can help in the implementation of the necessary measures to...

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Autores principales:	Freddy Gabbay, Shirly Bar-Lev, Ofer Montano, Noam Hadad
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	COVID-19 machine learning deep learning explainable AI Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/85adda00d46d46428fae7e1c91ec9428
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id	oai:doaj.org-article:85adda00d46d46428fae7e1c91ec9428
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spelling	oai:doaj.org-article:85adda00d46d46428fae7e1c91ec94282021-11-11T15:24:08ZA LIME-Based Explainable Machine Learning Model for Predicting the Severity Level of COVID-19 Diagnosed Patients10.3390/app1121104172076-3417https://doaj.org/article/85adda00d46d46428fae7e1c91ec94282021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/10417https://doaj.org/toc/2076-3417The fast and seemingly uncontrollable spread of the novel coronavirus disease (COVID-19) poses great challenges to an already overloaded health system worldwide. It thus exemplifies an urgent need for fast and effective triage. Such triage can help in the implementation of the necessary measures to prevent patient deterioration and conserve strained hospital resources. We examine two types of machine learning models, a multilayer perceptron artificial neural networks and decision trees, to predict the severity level of illness for patients diagnosed with COVID-19, based on their medical history and laboratory test results. In addition, we combine the machine learning models with a LIME-based explainable model to provide explainability of the model prediction. Our experimental results indicate that the model can achieve up to 80% prediction accuracy for the dataset we used. Finally, we integrate the explainable machine learning models into a mobile application to enable the usage of the proposed models by medical staff worldwide.Freddy GabbayShirly Bar-LevOfer MontanoNoam HadadMDPI AGarticleCOVID-19machine learningdeep learningexplainable AITechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10417, p 10417 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	COVID-19 machine learning deep learning explainable AI Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	COVID-19 machine learning deep learning explainable AI Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Freddy Gabbay Shirly Bar-Lev Ofer Montano Noam Hadad A LIME-Based Explainable Machine Learning Model for Predicting the Severity Level of COVID-19 Diagnosed Patients
description	The fast and seemingly uncontrollable spread of the novel coronavirus disease (COVID-19) poses great challenges to an already overloaded health system worldwide. It thus exemplifies an urgent need for fast and effective triage. Such triage can help in the implementation of the necessary measures to prevent patient deterioration and conserve strained hospital resources. We examine two types of machine learning models, a multilayer perceptron artificial neural networks and decision trees, to predict the severity level of illness for patients diagnosed with COVID-19, based on their medical history and laboratory test results. In addition, we combine the machine learning models with a LIME-based explainable model to provide explainability of the model prediction. Our experimental results indicate that the model can achieve up to 80% prediction accuracy for the dataset we used. Finally, we integrate the explainable machine learning models into a mobile application to enable the usage of the proposed models by medical staff worldwide.
format	article
author	Freddy Gabbay Shirly Bar-Lev Ofer Montano Noam Hadad
author_facet	Freddy Gabbay Shirly Bar-Lev Ofer Montano Noam Hadad
author_sort	Freddy Gabbay
title	A LIME-Based Explainable Machine Learning Model for Predicting the Severity Level of COVID-19 Diagnosed Patients
title_short	A LIME-Based Explainable Machine Learning Model for Predicting the Severity Level of COVID-19 Diagnosed Patients
title_full	A LIME-Based Explainable Machine Learning Model for Predicting the Severity Level of COVID-19 Diagnosed Patients
title_fullStr	A LIME-Based Explainable Machine Learning Model for Predicting the Severity Level of COVID-19 Diagnosed Patients
title_full_unstemmed	A LIME-Based Explainable Machine Learning Model for Predicting the Severity Level of COVID-19 Diagnosed Patients
title_sort	lime-based explainable machine learning model for predicting the severity level of covid-19 diagnosed patients
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/85adda00d46d46428fae7e1c91ec9428
work_keys_str_mv	AT freddygabbay alimebasedexplainablemachinelearningmodelforpredictingtheseveritylevelofcovid19diagnosedpatients AT shirlybarlev alimebasedexplainablemachinelearningmodelforpredictingtheseveritylevelofcovid19diagnosedpatients AT ofermontano alimebasedexplainablemachinelearningmodelforpredictingtheseveritylevelofcovid19diagnosedpatients AT noamhadad alimebasedexplainablemachinelearningmodelforpredictingtheseveritylevelofcovid19diagnosedpatients AT freddygabbay limebasedexplainablemachinelearningmodelforpredictingtheseveritylevelofcovid19diagnosedpatients AT shirlybarlev limebasedexplainablemachinelearningmodelforpredictingtheseveritylevelofcovid19diagnosedpatients AT ofermontano limebasedexplainablemachinelearningmodelforpredictingtheseveritylevelofcovid19diagnosedpatients AT noamhadad limebasedexplainablemachinelearningmodelforpredictingtheseveritylevelofcovid19diagnosedpatients
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A LIME-Based Explainable Machine Learning Model for Predicting the Severity Level of COVID-19 Diagnosed Patients

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