Main factors influencing recovery in MERS Co-V patients using machine learning
Identifieur interne : 000E48 ( Pmc/Curation ); précédent : 000E47; suivant : 000E49Main factors influencing recovery in MERS Co-V patients using machine learning
Auteurs : Maya John [Inde] ; Hadil Shaiba [Arabie saoudite]Source :
- Journal of Infection and Public Health [ 1876-0341 ] ; 2019.
Abstract
Middle East Respiratory Syndrome (MERS) is a major infectious disease which has affected the Middle Eastern countries, especially the Kingdom of Saudi Arabia (KSA) since 2012. The high mortality rate associated with this disease has been a major cause of concern. This paper aims at identifying the major factors influencing MERS recovery in KSA.
The data used for analysis was collected from the Ministry of Health website, KSA. The important factors impelling the recovery are found using machine learning. Machine learning models such as support vector machine, conditional inference tree, naïve Bayes and J48 are modelled to identify the important factors. Univariate and multivariate logistic regression analysis is also carried out to identify the significant factors statistically.
The main factors influencing MERS recovery rate are identified as age, pre-existing diseases, severity of disease and whether the patient is a healthcare worker or not. In spite of MERS being a zoonotic disease, contact with camels is not a major factor influencing recovery.
The methods used were able to determine the prime factors influencing MERS recovery. It can be comprehended that awareness about symptoms and seeking medical intervention at the onset of development of symptoms will make a long way in reducing the mortality rate.
Url:
DOI: 10.1016/j.jiph.2019.03.020
PubMed: 30979679
PubMed Central: 7102802
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Main factors influencing recovery in MERS Co-V patients using machine learning</title><author><name sortKey="John, Maya" sort="John, Maya" uniqKey="John M" first="Maya" last="John">Maya John</name><affiliation wicri:level="1"><nlm:aff id="aff0005">Department of Computer Science and Engineering, Sree Buddha College of Engineering, Pathanamthitta, Kerala, India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>Department of Computer Science and Engineering, Sree Buddha College of Engineering, Pathanamthitta, Kerala</wicri:regionArea></affiliation></author><author><name sortKey="Shaiba, Hadil" sort="Shaiba, Hadil" uniqKey="Shaiba H" first="Hadil" last="Shaiba">Hadil Shaiba</name><affiliation wicri:level="1"><nlm:aff id="aff0010">Department of Computer Science, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia</nlm:aff><country xml:lang="fr">Arabie saoudite</country><wicri:regionArea>Department of Computer Science, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">30979679</idno><idno type="pmc">7102802</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7102802</idno><idno type="RBID">PMC:7102802</idno><idno type="doi">10.1016/j.jiph.2019.03.020</idno><date when="2019">2019</date><idno type="wicri:Area/Pmc/Corpus">000E48</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000E48</idno><idno type="wicri:Area/Pmc/Curation">000E48</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000E48</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Main factors influencing recovery in MERS Co-V patients using machine learning</title><author><name sortKey="John, Maya" sort="John, Maya" uniqKey="John M" first="Maya" last="John">Maya John</name><affiliation wicri:level="1"><nlm:aff id="aff0005">Department of Computer Science and Engineering, Sree Buddha College of Engineering, Pathanamthitta, Kerala, India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>Department of Computer Science and Engineering, Sree Buddha College of Engineering, Pathanamthitta, Kerala</wicri:regionArea></affiliation></author><author><name sortKey="Shaiba, Hadil" sort="Shaiba, Hadil" uniqKey="Shaiba H" first="Hadil" last="Shaiba">Hadil Shaiba</name><affiliation wicri:level="1"><nlm:aff id="aff0010">Department of Computer Science, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia</nlm:aff><country xml:lang="fr">Arabie saoudite</country><wicri:regionArea>Department of Computer Science, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh</wicri:regionArea></affiliation></author></analytic><series><title level="j">Journal of Infection and Public Health</title><idno type="ISSN">1876-0341</idno><idno type="eISSN">1876-035X</idno><imprint><date when="2019">2019</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>Middle East Respiratory Syndrome (MERS) is a major infectious disease which has affected the Middle Eastern countries, especially the Kingdom of Saudi Arabia (KSA) since 2012. The high mortality rate associated with this disease has been a major cause of concern. This paper aims at identifying the major factors influencing MERS recovery in KSA.</p></sec><sec><title>Methods</title><p>The data used for analysis was collected from the Ministry of Health website, KSA. The important factors impelling the recovery are found using machine learning. Machine learning models such as support vector machine, conditional inference tree, naïve Bayes and J48 are modelled to identify the important factors. Univariate and multivariate logistic regression analysis is also carried out to identify the significant factors statistically.</p></sec><sec><title>Result</title><p>The main factors influencing MERS recovery rate are identified as age, pre-existing diseases, severity of disease and whether the patient is a healthcare worker or not. In spite of MERS being a zoonotic disease, contact with camels is not a major factor influencing recovery.</p></sec><sec><title>Conclusion</title><p>The methods used were able to determine the prime factors influencing MERS recovery. It can be comprehended that awareness about symptoms and seeking medical intervention at the onset of development of symptoms will make a long way in reducing the mortality rate.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Morens, D M" uniqKey="Morens D">D.M. Morens</name></author><author><name sortKey="Folkers, G K" uniqKey="Folkers G">G.K. Folkers</name></author><author><name sortKey="Fauci, A S" uniqKey="Fauci A">A.S. Fauci</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Zaki, A M" uniqKey="Zaki A">A.M. Zaki</name></author><author><name sortKey="Van Boheemen, S" uniqKey="Van Boheemen S">S. Van Boheemen</name></author><author><name sortKey="Bestebroer, T M" uniqKey="Bestebroer T">T.M. Bestebroer</name></author><author><name sortKey="Osterhaus, A D M E" uniqKey="Osterhaus A">A.D.M.E. Osterhaus</name></author><author><name sortKey="Fouchier, R A M" uniqKey="Fouchier R">R.A.M. Fouchier</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Arabi, Y M" uniqKey="Arabi Y">Y.M. Arabi</name></author><author><name sortKey="Bouchama, A" uniqKey="Bouchama A">A. Bouchama</name></author><author><name sortKey="Luke, T" uniqKey="Luke T">T. Luke</name></author><author><name sortKey="Baillie, J K" uniqKey="Baillie J">J.K. Baillie</name></author><author><name sortKey="Al Omari, A" uniqKey="Al Omari A">A. Al Omari</name></author><author><name sortKey="Hajeer, A H" uniqKey="Hajeer A">A.H. Hajeer</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Cotten, M" uniqKey="Cotten M">M. Cotten</name></author><author><name sortKey="Watson, S J" uniqKey="Watson S">S.J. Watson</name></author><author><name sortKey="Kellam, P" uniqKey="Kellam P">P. Kellam</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Gossner, C" uniqKey="Gossner C">C. Gossner</name></author><author><name sortKey="Danielson, N" uniqKey="Danielson N">N. Danielson</name></author><author><name sortKey="Gervelmeyer, A" uniqKey="Gervelmeyer A">A. Gervelmeyer</name></author><author><name sortKey="Berthe, F" uniqKey="Berthe F">F. Berthe</name></author><author><name sortKey="Faye, B" uniqKey="Faye B">B. Faye</name></author><author><name sortKey="Kaasik Aaslav, K" uniqKey="Kaasik Aaslav K">K. Kaasik Aaslav</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Azhar, E I" uniqKey="Azhar E">E.I. Azhar</name></author><author><name sortKey="El Kafrawy, S A" uniqKey="El Kafrawy S">S.A. El-Kafrawy</name></author><author><name sortKey="Farraj, S A" uniqKey="Farraj S">S.A. Farraj</name></author><author><name sortKey="Hassan, A M" uniqKey="Hassan A">A.M. Hassan</name></author><author><name sortKey="Al Saeed, M S" uniqKey="Al Saeed M">M.S. Al-Saeed</name></author><author><name sortKey="Hashem, A M" uniqKey="Hashem A">A.M. Hashem</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kasem, S" uniqKey="Kasem S">S. Kasem</name></author><author><name sortKey="Qasim, I" uniqKey="Qasim I">I. Qasim</name></author><author><name sortKey="Al Hufofi, A" uniqKey="Al Hufofi A">A. Al-Hufofi</name></author><author><name sortKey="Hashim, O" uniqKey="Hashim O">O. Hashim</name></author><author><name sortKey="Alkarar, A" uniqKey="Alkarar A">A. Alkarar</name></author><author><name sortKey="Abu Obeida, A" uniqKey="Abu Obeida A">A. Abu-Obeida</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Assiri, A" uniqKey="Assiri A">A. Assiri</name></author><author><name sortKey="Mcgeer, A" uniqKey="Mcgeer A">A. McGeer</name></author><author><name sortKey="Perl, T M" uniqKey="Perl T">T.M. Perl</name></author><author><name sortKey="Price, C S" uniqKey="Price C">C.S. Price</name></author><author><name sortKey="Al Rabeeah, A A" uniqKey="Al Rabeeah A">A.A. Al Rabeeah</name></author><author><name sortKey="Cummings, D A T" uniqKey="Cummings D">D.A.T. Cummings</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Memish, Z A" uniqKey="Memish Z">Z.A. Memish</name></author><author><name sortKey="Zumla, A I" uniqKey="Zumla A">A.I. Zumla</name></author><author><name sortKey="Al Hakeem, R F" uniqKey="Al Hakeem R">R.F. Al-Hakeem</name></author><author><name sortKey="Al Rabeeah, A A" uniqKey="Al Rabeeah A">A.A. Al-Rabeeah</name></author><author><name sortKey="Stephens, G M" uniqKey="Stephens G">G.M. Stephens</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Omrani, A S" uniqKey="Omrani A">A.S. Omrani</name></author><author><name sortKey="Matin, M A" uniqKey="Matin M">M.A. Matin</name></author><author><name sortKey="Haddad, Q" uniqKey="Haddad Q">Q. Haddad</name></author><author><name sortKey="Al Nakhli, D" uniqKey="Al Nakhli D">D. Al-Nakhli</name></author><author><name sortKey="Memish, Z A" uniqKey="Memish Z">Z.A. Memish</name></author><author><name sortKey="Albarrak, A M" uniqKey="Albarrak A">A.M. Albarrak</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Memish, Z A" uniqKey="Memish Z">Z.A. Memish</name></author><author><name sortKey="Cotten, M" uniqKey="Cotten M">M. Cotten</name></author><author><name sortKey="Watson, S J" uniqKey="Watson S">S.J. Watson</name></author><author><name sortKey="Kellam, P" uniqKey="Kellam P">P. Kellam</name></author><author><name sortKey="Zumla, A" uniqKey="Zumla A">A. Zumla</name></author><author><name sortKey="Alhakeem, R F" uniqKey="Alhakeem R">R.F. Alhakeem</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Hui, D S" uniqKey="Hui D">D.S. Hui</name></author><author><name sortKey="Azhar, E I" uniqKey="Azhar E">E.I. Azhar</name></author><author><name sortKey="Kim, Y J" uniqKey="Kim Y">Y.-J. Kim</name></author><author><name sortKey="Memish, Z A" uniqKey="Memish Z">Z.A. Memish</name></author><author><name sortKey="Oh, M" uniqKey="Oh M">M. Oh</name></author><author><name sortKey="Zumla, A" uniqKey="Zumla A">A. Zumla</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Breban, R" uniqKey="Breban R">R. Breban</name></author><author><name sortKey="Riou, J" uniqKey="Riou J">J. Riou</name></author><author><name sortKey="Fontanet, A" uniqKey="Fontanet A">A. Fontanet</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Al Mohrej, O A" uniqKey="Al Mohrej O">O.A. Al-Mohrej</name></author><author><name sortKey="Al Shirian, S D" uniqKey="Al Shirian S">S.D. Al-Shirian</name></author><author><name sortKey="Al Otaibi, S K" uniqKey="Al Otaibi S">S.K. Al-Otaibi</name></author><author><name sortKey="Tamim, H M" uniqKey="Tamim H">H.M. Tamim</name></author><author><name sortKey="Masuadi, E M" uniqKey="Masuadi E">E.M. Masuadi</name></author><author><name sortKey="Fakhoury, H M" uniqKey="Fakhoury H">H.M. Fakhoury</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Bawazir, A" uniqKey="Bawazir A">A. Bawazir</name></author><author><name sortKey="Al Mazroo, E" uniqKey="Al Mazroo E">E. Al-Mazroo</name></author><author><name sortKey="Jradi, H" uniqKey="Jradi H">H. Jradi</name></author><author><name sortKey="Ahmed, A" uniqKey="Ahmed A">A. Ahmed</name></author><author><name sortKey="Badri, M" uniqKey="Badri M">M. Badri</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Alsahaf, A J" uniqKey="Alsahaf A">A.J. Alsahaf</name></author><author><name sortKey="Cheng, A C" uniqKey="Cheng A">A.C. Cheng</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Yang, Y M" uniqKey="Yang Y">Y.-M. Yang</name></author><author><name sortKey="Hsu, C Y" uniqKey="Hsu C">C.-Y. Hsu</name></author><author><name sortKey="Lai, C C" uniqKey="Lai C">C.-C. Lai</name></author><author><name sortKey="Yen, M F" uniqKey="Yen M">M.-F. Yen</name></author><author><name sortKey="Wikramaratna, P S" uniqKey="Wikramaratna P">P.S. Wikramaratna</name></author><author><name sortKey="Chen, H H" uniqKey="Chen H">H.-H. Chen</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Rivers, C M" uniqKey="Rivers C">C.M. Rivers</name></author><author><name sortKey="Majumder, M S" uniqKey="Majumder M">M.S. Majumder</name></author><author><name sortKey="Lofgren, E T" uniqKey="Lofgren E">E.T. Lofgren</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Ahmed, A E" uniqKey="Ahmed A">A.E. Ahmed</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Al Turaiki, I" uniqKey="Al Turaiki I">I. Al-Turaiki</name></author><author><name sortKey="Alshahrani, M" uniqKey="Alshahrani M">M. Alshahrani</name></author><author><name sortKey="Almutairi, T" uniqKey="Almutairi T">T. Almutairi</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Abdullah, M" uniqKey="Abdullah M">M. Abdullah</name></author><author><name sortKey="Altheyab, M S" uniqKey="Altheyab M">M.S. Altheyab</name></author><author><name sortKey="Lattas, A M" uniqKey="Lattas A">A.M. Lattas</name></author><author><name sortKey="Algashmari, W F" uniqKey="Algashmari W">W.F. Algashmari</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Li, E Y" uniqKey="Li E">E.Y. Li</name></author><author><name sortKey="Tung, C Y" uniqKey="Tung C">C.Y. Tung</name></author><author><name sortKey="Chang, S H" uniqKey="Chang S">S.H. Chang</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Wiemken, T L" uniqKey="Wiemken T">T.L. Wiemken</name></author><author><name sortKey="Furmanek, S P" uniqKey="Furmanek S">S.P. Furmanek</name></author><author><name sortKey="Mattingly, W A" uniqKey="Mattingly W">W.A. Mattingly</name></author><author><name sortKey="Guinn, B E" uniqKey="Guinn B">B.E. Guinn</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Quinlan, R" uniqKey="Quinlan R">R. Quinlan</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Majumder, M S" uniqKey="Majumder M">M.S. Majumder</name></author><author><name sortKey="Kluberg, S A" uniqKey="Kluberg S">S.A. Kluberg</name></author><author><name sortKey="Mekaru, S R" uniqKey="Mekaru S">S.R. Mekaru</name></author><author><name sortKey="Brownstein, J S" uniqKey="Brownstein J">J.S. Brownstein</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Ahmed, A E" uniqKey="Ahmed A">A.E. Ahmed</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Chen, X" uniqKey="Chen X">X. Chen</name></author><author><name sortKey="Chughtai, A A" uniqKey="Chughtai A">A.A. Chughtai</name></author><author><name sortKey="Dyda, A" uniqKey="Dyda A">A. Dyda</name></author><author><name sortKey="Macintyre, C R" uniqKey="Macintyre C">C.R. Macintyre</name></author></analytic></biblStruct></listBibl></div1></back></TEI><pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">J Infect Public Health</journal-id><journal-id journal-id-type="iso-abbrev">J Infect Public Health</journal-id><journal-title-group><journal-title>Journal of Infection and Public Health</journal-title></journal-title-group><issn pub-type="ppub">1876-0341</issn><issn pub-type="epub">1876-035X</issn><publisher><publisher-name>Elsevier</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">30979679</article-id><article-id pub-id-type="pmc">7102802</article-id><article-id pub-id-type="publisher-id">S1876-0341(19)30129-7</article-id><article-id pub-id-type="doi">10.1016/j.jiph.2019.03.020</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Main factors influencing recovery in MERS Co-V patients using machine learning</article-title></title-group><contrib-group><contrib contrib-type="author" id="aut0005"><name><surname>John</surname><given-names>Maya</given-names></name><email>maya.j.mail@gmail.com</email><xref rid="aff0005" ref-type="aff">1</xref><xref rid="cor0005" ref-type="corresp">⁎</xref></contrib><contrib contrib-type="author" id="aut0010"><name><surname>Shaiba</surname><given-names>Hadil</given-names></name><email>hadil.shaiba@gmail.com</email><xref rid="aff0010" ref-type="aff">2</xref></contrib></contrib-group><aff id="aff0005"><label>1</label>Department of Computer Science and Engineering, Sree Buddha College of Engineering, Pathanamthitta, Kerala, India</aff><aff id="aff0010"><label>2</label>Department of Computer Science, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia</aff><author-notes><corresp id="cor0005"><label>⁎</label>Corresponding author. <email>maya.j.mail@gmail.com</email></corresp></author-notes><pub-date pub-type="pmc-release"><day>10</day><month>4</month><year>2019</year></pub-date><pmc-comment> PMC Release delay is 0 months and 0 days and was based on .</pmc-comment>
<pub-date pub-type="ppub" iso-8601-date="2019-10-01"><season>September-October</season><year>2019</year></pub-date><pub-date pub-type="epub"><day>10</day><month>4</month><year>2019</year></pub-date><volume>12</volume><issue>5</issue><fpage>700</fpage><lpage>704</lpage><history><date date-type="received"><day>13</day><month>11</month><year>2018</year></date><date date-type="rev-recd"><day>8</day><month>3</month><year>2019</year></date><date date-type="accepted"><day>24</day><month>3</month><year>2019</year></date></history><permissions><copyright-statement>.</copyright-statement><copyright-year>2019</copyright-year><copyright-holder></copyright-holder><license><license-p>Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.</license-p></license></permissions><abstract id="abs0005"><sec><title>Background</title><p>Middle East Respiratory Syndrome (MERS) is a major infectious disease which has affected the Middle Eastern countries, especially the Kingdom of Saudi Arabia (KSA) since 2012. The high mortality rate associated with this disease has been a major cause of concern. This paper aims at identifying the major factors influencing MERS recovery in KSA.</p></sec><sec><title>Methods</title><p>The data used for analysis was collected from the Ministry of Health website, KSA. The important factors impelling the recovery are found using machine learning. Machine learning models such as support vector machine, conditional inference tree, naïve Bayes and J48 are modelled to identify the important factors. Univariate and multivariate logistic regression analysis is also carried out to identify the significant factors statistically.</p></sec><sec><title>Result</title><p>The main factors influencing MERS recovery rate are identified as age, pre-existing diseases, severity of disease and whether the patient is a healthcare worker or not. In spite of MERS being a zoonotic disease, contact with camels is not a major factor influencing recovery.</p></sec><sec><title>Conclusion</title><p>The methods used were able to determine the prime factors influencing MERS recovery. It can be comprehended that awareness about symptoms and seeking medical intervention at the onset of development of symptoms will make a long way in reducing the mortality rate.</p></sec></abstract><kwd-group id="kwd0005"><title>Keywords</title><kwd>MERS</kwd><kwd>Infectious disease</kwd><kwd>Survival rate</kwd><kwd>Machine learning</kwd><kwd>Saudi Arabia</kwd></kwd-group></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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