<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>2739-0063</journal-id>
<journal-title><![CDATA[Revista InveCom]]></journal-title>
<abbrev-journal-title><![CDATA[Revista InveCom]]></abbrev-journal-title>
<issn>2739-0063</issn>
<publisher>
<publisher-name><![CDATA[Asociación Investigadores Venezolanos de la Comunicación]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2739-00632026000303017</article-id>
<article-id pub-id-type="doi">10.5281/zenodo.17254435</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Deep learning in occupational safety and health and its contribution to workplace risk management: A systematic review]]></article-title>
<article-title xml:lang="es"><![CDATA[El aprendizaje profundo en seguridad y salud laboral y su contribución a la gestión de riesgos en el lugar de trabajo: una revisión sistemática]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Segovia Hermoza]]></surname>
<given-names><![CDATA[Milner]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Huamani Morales]]></surname>
<given-names><![CDATA[Katherin Lizat]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Segovia Segovia]]></surname>
<given-names><![CDATA[Milner]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Nacional de Ingeniería  ]]></institution>
<addr-line><![CDATA[Lima ]]></addr-line>
<country>Peru</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Nacional Mayor de San Marcos  ]]></institution>
<addr-line><![CDATA[Lima ]]></addr-line>
<country>Peru</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad Nacional San Antonio Abad del Cusco  ]]></institution>
<addr-line><![CDATA[Cusco ]]></addr-line>
<country>Peru</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>09</month>
<year>2026</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>09</month>
<year>2026</year>
</pub-date>
<volume>6</volume>
<numero>3</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://ve.scielo.org/scielo.php?script=sci_arttext&amp;pid=S2739-00632026000303017&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://ve.scielo.org/scielo.php?script=sci_abstract&amp;pid=S2739-00632026000303017&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://ve.scielo.org/scielo.php?script=sci_pdf&amp;pid=S2739-00632026000303017&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Occupational health and safety (OHS) is essential in all industrial sectors due to the significant impact of accidents and occupational illnesses. Traditionally, risk management has relied on periodic assessments and reactive control measures; however, artificial intelligence and deep learning have enabled the development of more proactive and efficient approaches. These technologies facilitate the analysis of large volumes of data to identify hidden patterns, predict risks, and improve workplace safety. In this context, this study analyzes the current use of deep learning in OHS, focusing on its implementation, perceived effectiveness, and the challenges it presents. Furthermore, it examines its application in sectors such as construction, logistics, and mining, where it contributes to risk prevention and the detection of unsafe behaviors. To this end, a systematic review was conducted following the PRISMA protocol, including 14 open-access articles selected from an initial pool of 274 publications retrieved from Scopus, PubMed, Web of Science, and DOAJ. The analysis concludes that deep learning has great potential to reduce unsafe behaviors by identifying and detecting key variables, such as information management, that influence the occurrence of incidents and hazardous conditions. Therefore, this technology emerges as a valuable tool to support OHS professionals in prevention, control, and decision-making in various work environments.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen La salud y seguridad en el trabajo (SST) es fundamental en todos los sectores industriales debido al impacto significativo de los accidentes y las enfermedades laborales. Tradicionalmente, la gestión de riesgos se ha basado en evaluaciones periódicas y medidas de control reactivas; sin embargo, la inteligencia artificial y el aprendizaje profundo han permitido desarrollar enfoques más preventivos y eficientes. Estas tecnologías facilitan el análisis de grandes volúmenes de datos para identificar patrones ocultos, predecir riesgos y mejorar la seguridad laboral. En este marco, el presente estudio analiza el uso actual del aprendizaje profundo en SST, centrándose en su implementación, la percepción de su eficacia y los desafíos que plantea. Además, se examina su aplicación en sectores como la construcción, la logística y la minería, donde contribuye a la prevención de riesgos y a la detección de comportamientos inseguros. Para ello, se llevó a cabo una revisión sistemática siguiendo el protocolo PRISMA, que incluyó 14 artículos de acceso abierto seleccionados de un total inicial de 274 publicaciones recuperadas de Scopus, PubMed, Web of Science y DOAJ. A partir del análisis realizado, se concluye que el aprendizaje profundo posee un gran potencial para disminuir conductas inseguras mediante la identificación y detección de variables clave, como la gestión de la información, que influyen en la ocurrencia de incidentes y condiciones peligrosas. Por ende, esta tecnología se presenta como una herramienta valiosa para apoyar al personal de SST en la prevención, control y toma de decisiones en diversos contextos laborales.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[deep learning]]></kwd>
<kwd lng="en"><![CDATA[occupational risks]]></kwd>
<kwd lng="en"><![CDATA[workplace safety]]></kwd>
<kwd lng="es"><![CDATA[aprendizaje profundo]]></kwd>
<kwd lng="es"><![CDATA[riesgos laborales]]></kwd>
<kwd lng="es"><![CDATA[seguridad en el trabajo]]></kwd>
</kwd-group>
</article-meta>
</front><back>
<ref-list>
<ref id="B1">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Ajayi]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Oyedele]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
<name>
<surname><![CDATA[Owolabi]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Akinade]]></surname>
<given-names><![CDATA[O.]]></given-names>
</name>
<name>
<surname><![CDATA[Bilal]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Davila Delgado]]></surname>
<given-names><![CDATA[J. M.]]></given-names>
</name>
<name>
<surname><![CDATA[Akanbi]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Deep learning models for health and safety risk prediction in power infrastructure projects.]]></article-title>
<source><![CDATA[Risk Analysis]]></source>
<year>2020</year>
<volume>40</volume>
<numero>10</numero>
<issue>10</issue>
<page-range>2019-39</page-range></nlm-citation>
</ref>
<ref id="B2">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Antwi-Afari]]></surname>
<given-names><![CDATA[M. F.]]></given-names>
</name>
<name>
<surname><![CDATA[Qarout]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Herzallah]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
<name>
<surname><![CDATA[Anwer]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Umer]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Manu]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Deep learning-based networks for automated recognition and classification of awkward working postures in construction using wearable insole sensor data]]></article-title>
<source><![CDATA[Automation in Construction]]></source>
<year>2022</year>
<volume>136</volume>
<page-range>104181</page-range></nlm-citation>
</ref>
<ref id="B3">
<nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Casuat]]></surname>
<given-names><![CDATA[C. D.]]></given-names>
</name>
<name>
<surname><![CDATA[Merencilla]]></surname>
<given-names><![CDATA[N. E.]]></given-names>
</name>
<name>
<surname><![CDATA[Reyes]]></surname>
<given-names><![CDATA[R. C.]]></given-names>
</name>
<name>
<surname><![CDATA[Sevilla]]></surname>
<given-names><![CDATA[R. V.]]></given-names>
</name>
<name>
<surname><![CDATA[Pascion]]></surname>
<given-names><![CDATA[C. G.]]></given-names>
</name>
</person-group>
<source><![CDATA[Deep-Hart: An inference deep learning approach of hard hat detection for work safety and surveillance.]]></source>
<year>2020</year>
<conf-name><![CDATA[ Conference on Engineering Technologies and Applied Sciences (ICETAS 2020)]]></conf-name>
<conf-loc> </conf-loc>
</nlm-citation>
</ref>
<ref id="B4">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Denning]]></surname>
<given-names><![CDATA[P. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Denning]]></surname>
<given-names><![CDATA[D. E.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The profession of IT: Dilemmas of artificial intelligence]]></article-title>
<source><![CDATA[Communications of the ACM]]></source>
<year>2020</year>
<volume>63</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>22-4</page-range></nlm-citation>
</ref>
<ref id="B5">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Dong]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Abbas]]></surname>
<given-names><![CDATA[K.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A survey on deep learning and its applications.]]></article-title>
<source><![CDATA[Computer Science Review]]></source>
<year>2021</year>
<volume>40</volume>
<numero>100379</numero>
<issue>100379</issue>
</nlm-citation>
</ref>
<ref id="B6">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Du]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Feng]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Feng]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Malekian]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[Z.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A new machine-learning prediction model for slope deformation of an open-pit mine: An evaluation of field data]]></article-title>
<source><![CDATA[Energies]]></source>
<year>2019</year>
<volume>12</volume>
<numero>7</numero>
<issue>7</issue>
<page-range>1288</page-range></nlm-citation>
</ref>
<ref id="B7">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Fan]]></surname>
<given-names><![CDATA[Z.]]></given-names>
</name>
<name>
<surname><![CDATA[Xu]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Health risks of occupational exposure to toxic chemicals in coal mine workplaces based on risk assessment mathematical model based on deep learning]]></article-title>
<source><![CDATA[Environmental Technology and Innovation]]></source>
<year>2021</year>
<volume>22</volume>
<page-range>101500</page-range></nlm-citation>
</ref>
<ref id="B8">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Fang]]></surname>
<given-names><![CDATA[Q.]]></given-names>
</name>
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Luo]]></surname>
<given-names><![CDATA[X.]]></given-names>
</name>
<name>
<surname><![CDATA[Ding]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
<name>
<surname><![CDATA[Rose]]></surname>
<given-names><![CDATA[T. M.]]></given-names>
</name>
<name>
<surname><![CDATA[An]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
<name>
<surname><![CDATA[Yu]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A deep learning-based method for detecting non-certified work on construction sites]]></article-title>
<source><![CDATA[Advanced Engineering Informatics]]></source>
<year>2018</year>
<volume>35</volume>
<page-range>56-68</page-range></nlm-citation>
</ref>
<ref id="B9">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Hunt]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
<name>
<surname><![CDATA[Sarkar]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Warhurst]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Measuring the impact of AI on jobs at the organization level: Lessons from a survey of UK business leaders.]]></article-title>
<source><![CDATA[Research Policy]]></source>
<year>2022</year>
<volume>51</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>104425</page-range></nlm-citation>
</ref>
<ref id="B10">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Jain]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Miyapuram]]></surname>
<given-names><![CDATA[S. T.]]></given-names>
</name>
<name>
<surname><![CDATA[Reddy]]></surname>
<given-names><![CDATA[S. R]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[IoT based fire accident detection system with deep learning intelligence]]></article-title>
<source><![CDATA[International Journal of Engineering and Advanced Technology]]></source>
<year>2021</year>
<volume>11</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>138-42</page-range></nlm-citation>
</ref>
<ref id="B11">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Jeong]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
<name>
<surname><![CDATA[Park]]></surname>
<given-names><![CDATA[C. G.]]></given-names>
</name>
<name>
<surname><![CDATA[Kang]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
<name>
<surname><![CDATA[Choi]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Hwang]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Measuring ethics level of technological topics using phylogenetic tree]]></article-title>
<source><![CDATA[Technology Analysis &amp; Strategic Management]]></source>
<year>2023</year>
<page-range>1-14</page-range></nlm-citation>
</ref>
<ref id="B12">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Liu]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Luo]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Liu]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Deep learning-based data analytics for safety in construction]]></article-title>
<source><![CDATA[Automation in Construction]]></source>
<year>2022</year>
<volume>140</volume>
<page-range>104302</page-range></nlm-citation>
</ref>
<ref id="B13">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Luo]]></surname>
<given-names><![CDATA[X.]]></given-names>
</name>
<name>
<surname><![CDATA[Lin]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
<name>
<surname><![CDATA[Zhu]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Yu]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[Z.]]></given-names>
</name>
<name>
<surname><![CDATA[Meng]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
<name>
<surname><![CDATA[Peng]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Mine landslide susceptibility assessment using IVM, ANN and SVM models considering the contribution of affecting factors.]]></article-title>
<source><![CDATA[PLoS ONE]]></source>
<year>2019</year>
<volume>14</volume>
<numero>4</numero>
<issue>4</issue>
</nlm-citation>
</ref>
<ref id="B14">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Uchida]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Noshita]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Tsutsui]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
<name>
<surname><![CDATA[Koyama]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Application of a deep learning for occupational health and safety recognition: a pilot study in a logistics industry]]></article-title>
<source><![CDATA[Sangyo Eiseigaku Zasshi]]></source>
<year>2018</year>
<volume>60</volume>
<numero>6</numero>
<issue>6</issue>
<page-range>191-5</page-range></nlm-citation>
</ref>
<ref id="B15">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Nath]]></surname>
<given-names><![CDATA[N. D.]]></given-names>
</name>
<name>
<surname><![CDATA[Behzadan]]></surname>
<given-names><![CDATA[A. H.]]></given-names>
</name>
<name>
<surname><![CDATA[Paal]]></surname>
<given-names><![CDATA[S. G.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Deep learning for site safety: Real-time detection of personal protective equipment]]></article-title>
<source><![CDATA[Automation in Construction]]></source>
<year>2020</year>
<volume>112</volume>
<page-range>103085</page-range></nlm-citation>
</ref>
<ref id="B16">
<nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Rybak]]></surname>
<given-names><![CDATA[N.]]></given-names>
</name>
<name>
<surname><![CDATA[Hassall]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
</person-group>
<source><![CDATA[Deep learning unsupervised text-based detection of anomalies in U.S. Chemical Safety and Hazard Investigation Board reports]]></source>
<year>2021</year>
<conf-name><![CDATA[ Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME 2021)]]></conf-name>
<conf-loc> </conf-loc>
</nlm-citation>
</ref>
<ref id="B17">
<nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Sarwar Murshed]]></surname>
<given-names><![CDATA[M. G.]]></given-names>
</name>
<name>
<surname><![CDATA[Carroll]]></surname>
<given-names><![CDATA[J. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Khan]]></surname>
<given-names><![CDATA[N.]]></given-names>
</name>
<name>
<surname><![CDATA[Hussain]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
</person-group>
<source><![CDATA[Resource-aware on-device deep learning for supermarket hazard detection]]></source>
<year>2020</year>
<conf-name><![CDATA[ Conference on Machine Learning and Applications (ICMLA)]]></conf-name>
<conf-loc> </conf-loc>
</nlm-citation>
</ref>
<ref id="B18">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Yi]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Case analysis of applications for deep learning technology in the mining industry]]></article-title>
<source><![CDATA[Journal of the Korean Society of Mineral and Energy Resources Engineers]]></source>
<year>2019</year>
<volume>56</volume>
<numero>5</numero>
<issue>5</issue>
<page-range>435-46</page-range></nlm-citation>
</ref>
<ref id="B19">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Zi]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
<name>
<surname><![CDATA[Hou]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Deng]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
<name>
<surname><![CDATA[Jiang]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A C-BiLSTM approach to classify construction accident reports]]></article-title>
<source><![CDATA[Applied Sciences]]></source>
<year>2020</year>
<volume>10</volume>
<numero>17</numero>
<issue>17</issue>
<page-range>5754</page-range></nlm-citation>
</ref>
<ref id="B20">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zhong]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
<name>
<surname><![CDATA[Pan]]></surname>
<given-names><![CDATA[X.]]></given-names>
</name>
<name>
<surname><![CDATA[Love]]></surname>
<given-names><![CDATA[P. E. D.]]></given-names>
</name>
<name>
<surname><![CDATA[Sun]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Tao]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Hazard analysis: A deep learning and text mining framework for accident prevention]]></article-title>
<source><![CDATA[Advanced Engineering Informatics]]></source>
<year>2020</year>
<volume>46,</volume>
<page-range>101152</page-range></nlm-citation>
</ref>
</ref-list>
</back>
</article>
