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<article article-type="research-article" dtd-version="1.3" 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" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">vguit</journal-id><journal-title-group><journal-title xml:lang="ru">Вестник Воронежского государственного университета инженерных технологий</journal-title><trans-title-group xml:lang="en"><trans-title>Proceedings of the Voronezh State University of Engineering Technologies</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2226-910X</issn><issn pub-type="epub">2310-1202</issn><publisher><publisher-name>VSUET</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.20914/2310-1202-2023-4-109-114</article-id><article-id custom-type="elpub" pub-id-type="custom">vguit-3424</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>Пищевая  биотехнология</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>Food biotechnology</subject></subj-group></article-categories><title-group><article-title>Математическое и алгоритмическое моделирование комплексного медико-социального интегрального показателя для работников АПК</article-title><trans-title-group xml:lang="en"><trans-title>Mathematical and algorithmic modeling of a complex medical and social integral indicator for agricultural workers</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Гладских</surname><given-names>Н. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Gladskikh</surname><given-names>N. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>к.т.н., доцент, ул. Ленина,73а, г. Воронеж, 394043, Россия</p></bio><bio xml:lang="en"><p>Cand. Sci. (Engin.), associate professor, st. Studencheskaya, 10, Voronezh, 394000, Russia</p></bio><email xlink:type="simple">ngladskikh@rambler.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Устимов</surname><given-names>М. Г.</given-names></name><name name-style="western" xml:lang="en"><surname>Ustimov</surname><given-names>M. G.</given-names></name></name-alternatives><bio xml:lang="ru"><p>аспирант, ,ул. Ленина,73а, г. Воронеж, 394043, Россия</p></bio><bio xml:lang="en"><p>graduate student, , st. Studencheskaya, 10, Voronezh, 394000, Russia</p></bio><email xlink:type="simple">ngladskikh@rambler.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Левицкий</surname><given-names>Е. Н.</given-names></name><name name-style="western" xml:lang="en"><surname>Levitsky</surname><given-names>E. N.</given-names></name></name-alternatives><bio xml:lang="ru"><p>аспирант, ул. Ленина,73а, г. Воронеж, 394043, Россия</p></bio><bio xml:lang="en"><p>graduate student, , st. Studencheskaya, 10, Voronezh, 394000, Russia</p></bio><email xlink:type="simple">nglad-skikh@rambler.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Воронежский институт высоких технологий</institution></aff><aff xml:lang="en"><institution>Voronezh State Medical University</institution></aff></aff-alternatives><pub-date pub-type="collection"><year>2023</year></pub-date><pub-date pub-type="epub"><day>26</day><month>02</month><year>2024</year></pub-date><volume>85</volume><issue>4</issue><fpage>109</fpage><lpage>114</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Гладских Н.А., Устимов М.Г., Левицкий Е.Н., 2024</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="ru">Гладских Н.А., Устимов М.Г., Левицкий Е.Н.</copyright-holder><copyright-holder xml:lang="en">Gladskikh N.A., Ustimov M.G., Levitsky E.N.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.vestnik-vsuet.ru/vguit/article/view/3424">https://www.vestnik-vsuet.ru/vguit/article/view/3424</self-uri><abstract><p>Качественная и количественная оценка состояния здоровья в том числе работников АПК является важной и актуальной задачей. При разработке методики расчета вероятности утраты работником трудоспособности в зависимости от состояния условий труда на рабочем месте было показано, что в контексте решения задач по оценке влияния условий труда на здоровье работника, в том числе, в процедурах оценки профессионального риска, вероятность утраты трудоспособности представляет собой не что иное, как количественную оценку вероятности развития профессионального заболевания или производственной травмы в конкретных условиях труда, что, на первый взгляд, можно было бы охарактеризовать показателями частоты профессиональной заболеваемости и травматизма с учетом условий труда. На базе участковых отделений городских поликлиник было проведено обследование состояния здоровья работников АПК. Для сбора информации о пациентах использовалась «Анкета о здоровье», которая по решению Всемирной Организации Здравоохранения введена во всех медицинских учреждениях анкета о здоровье пациента. Было собрано и проанализировано 156 анкет. На первом этапе обработки информации исследована структура медико-социальных характеристик работников АПК. На втором этапе применялся метод априорного ранжирования, использующий экспертную информацию для ранговой оценки каждого значения признака. В ходе исследования были рассчитаны балльные оценки, необходимые для последующего расчета комплексного интегрального медико-социального показателя здоровья. Результаты исследования свидетельствуют о наличии отрицательной тенденции в динамике состояния здоровья работников АПК, что в первую очередь связано с нерациональным питанием, недостатком двигательной активности, самолечением, редкими обращениями к медицинским специалистам. В связи с этим важными задачами являются, прежде всего, разработка и внедрение профилактических, лечебно-реабилитационных технологий и приоритетных программ в работу предприятий АПК, в частности, рациональная организация питания в предприятиях АПК, оптимизация двигательного режима.</p></abstract><trans-abstract xml:lang="en"><p>Qualitative and quantitative assessment of the health status of workers in the agro-industrial complex is an important and urgent task. When developing a methodology for calculating the probability of an employee losing ability to work depending on the state of working conditions in the workplace, it was shown that in the context of solving problems of assessing the impact of working conditions on the health of a worker, including in procedures for assessing occupational risk, the probability of loss of ability to work is not nothing more than a quantitative assessment of the probability of developing an occupational disease or work-related injury in specific working conditions, which, at first glance, could be characterized by indicators of the frequency of occupational diseases and injuries taking into account working conditions. A survey of the health status of agricultural workers was conducted at local departments of city clinics. To collect information about patients, we used the “Health Questionnaire”, which, by decision of the World Health Organization, introduced a questionnaire about the patient’s health in all medical institutions. 156 questionnaires were collected and analyzed. At the first stage of information processing, the structure of medical and social characteristics of agricultural workers was studied. At the second stage, the a priori ranking method was used, which uses expert information to rank each attribute value. During the study, the scores necessary for the subsequent calculation of a complex integral medical and social health indicator were calculated. The results of the study indicate the presence of a negative trend in the dynamics of the health status of agricultural workers, which is primarily associated with poor nutrition, lack of physical activity, self-medication, and rare visits to medical specialists. In this regard, important tasks are, first of all, the development and implementation of preventive, treatment and rehabilitation technologies and priority programs in the work of agro-industrial enterprises, in particular, the rational organization of nutrition in agro-industrial enterprises, optimization of the motor regime.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>интегральный показатель</kwd><kwd>реабилитационный потенциал</kwd><kwd>априорное ранжирование</kwd><kwd>экспертное оценивание</kwd><kwd>балльные оценки</kwd><kwd>коэффициент конкордации</kwd></kwd-group><kwd-group xml:lang="en"><kwd>integral indicator</kwd><kwd>rehabilitation potential</kwd><kwd>a priori ranking</kwd><kwd>expert assessment</kwd><kwd>point estimates</kwd><kwd>coefficient of concordance</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Falissard L., Morgand C., Roussel S., Imbaud C. et al. A deep artificial neural network− based model for prediction of underlying cause of death from death certificates: algorithm development and validation // JMIR Medical informatics. 2020. V. 8. №. 4. P. e17125. doi: 10.2196/17125</mixed-citation><mixed-citation xml:lang="en">Falissard L., Morgand C., Roussel S., Imbaud C. et al. A deep artificial neural network− based model for prediction of underlying cause of death from death certificates: algorithm development and validation. JMIR Medical informatics. 2020. vol. 8. no. 4. pp. e17125. doi: 10.2196/17125</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Shirwaikar R.D., Acharya D., Makkithaya K., Surulivelrajan M. et al. Optimizing neural networks for medical data sets: A case study on neonatal apnea prediction // Artificial intelligence in medicine. 2019. V. 98. P. 59-76.</mixed-citation><mixed-citation xml:lang="en">Shirwaikar R.D., Acharya D., Makkithaya K., Surulivelrajan M. et al. Optimizing neural networks for medical data sets: A case study on neonatal apnea prediction. Artificial intelligence in medicine. 2019. vol. 98. pp. 59-76.</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">May A.M., DeSimone C.V., Kashou A.H., Hodge D.O. et al. The WCT formula: a novel algorithm designed to automatically differentiate wide-complex tachycardias // Journal of Electrocardiology. 2019. V. 54. P. 61-68.</mixed-citation><mixed-citation xml:lang="en">May A.M., DeSimone C.V., Kashou A.H., Hodge D.O. et al. The WCT formula: a novel algorithm designed to automatically differentiate wide-complex tachycardias. Journal of Electrocardiology. 2019. vol. 54. pp. 61-68.</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Khudov H., Ruban I., Makoveichuk O., Pevtsov H. et al. Development of methods for determining the contours of objects for a complex structured color image based on the ant colony optimization algorithm // Physics and Engineering. 2020. V. 1. P. 34-47. doi: 10.21303/2461-4262.2020.001108</mixed-citation><mixed-citation xml:lang="en">Khudov H., Ruban I., Makoveichuk O., Pevtsov H. et al. Development of methods for determining the contours of objects for a complex structured color image based on the ant colony optimization algorithm. Physics and Engineering. 2020. vol. 1. pp. 34-47. doi: 10.21303/2461-4262.2020.001108</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Vlachopoulos L., Székely G., Gerber C., Fürnstahl P. A scale-space curvature matching algorithm for the reconstruction of complex proximal humeral fractures // Medical image analysis. 2018. V. 43. P. 142-156.</mixed-citation><mixed-citation xml:lang="en">Vlachopoulos L., Székely G., Gerber C., Fürnstahl P. A scale-space curvature matching algorithm for the reconstruction of complex proximal humeral fractures. Medical image analysis. 2018. vol. 43. pp. 142-156.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Kavitha K.S., Ramakrishnan K.V., Singh M.K. Modeling and design of evolutionary neural network for heart disease detection // International Journal of Computer Science Issues (IJCSI). 2010. V. 7. №. 5. P. 272.</mixed-citation><mixed-citation xml:lang="en">Kavitha K.S., Ramakrishnan K.V., Singh M.K. Modeling and design of evolutionary neural network for heart disease detection. International Journal of Computer Science Issues (IJCSI). 2010. vol. 7. no. 5. pp. 272.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Jeyaraj P.R., Nadar E.R.S. Deep Boltzmann machine algorithm for accurate medical image analysis for classification of cancerous region // Cognitive Computation and Systems. 2019. V. 1. №. 3. P. 85-90. doi: 10.1049/ccs.2019.0004</mixed-citation><mixed-citation xml:lang="en">Jeyaraj P.R., Nadar E.R.S. Deep Boltzmann machine algorithm for accurate medical image analysis for classification of cancerous region. Cognitive Computation and Systems. 2019. vol. 1. no. 3. pp. 85-90. doi: 10.1049/ccs.2019.0004</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Yuan Y., Yan S., Fang Q. Light transport modeling in highly complex tissues using the implicit mesh-based Monte Carlo algorithm // Biomedical Optics Express. 2021. V. 12. №. 1. P. 147-161. doi: 10.1364/BOE.411898</mixed-citation><mixed-citation xml:lang="en">Yuan Y., Yan S., Fang Q. Light transport modeling in highly complex tissues using the implicit mesh-based Monte Carlo algorithm. Biomedical Optics Express. 2021. vol. 12. no. 1. pp. 147-161. doi: 10.1364/BOE.411898</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Kushwaha P.K., Kumaresan M. Machine learning algorithm in healthcare system: A Review // 2021 international conference on technological advancements and innovations (ICTAI). IEEE, 2021. P. 478-481.</mixed-citation><mixed-citation xml:lang="en">Kushwaha P.K., Kumaresan M. Machine learning algorithm in healthcare system: A Review. 2021 international conference on technological advancements and innovations (ICTAI). IEEE, 2021. pp. 478-481.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Li X., Li D., Deng Y., Xing J. Intelligent mining algorithm for complex medical data based on deep learning // Journal of Ambient Intelligence and Humanized Computing. 2021. V. 12. P. 1667-1678.</mixed-citation><mixed-citation xml:lang="en">Li X., Li D., Deng Y., Xing J. Intelligent mining algorithm for complex medical data based on deep learning. Journal of Ambient Intelligence and Humanized Computing. 2021. vol. 12. pp. 1667-1678.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Al-Kasasbeh R.T., Korenevskiy N., Alshamasin M.S., Al-Habahbeh O. et al. Fuzzy Mathematical Models for Predicting and Diagnosing Occupational Diseases of Workers in the Agro-industrial Complex in Contact with Pesticides // 2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC). IEEE, 2022. P. 290-294.</mixed-citation><mixed-citation xml:lang="en">Al-Kasasbeh R.T., Korenevskiy N., Alshamasin M.S., Al-Habahbeh O. et al. Fuzzy Mathematical Models for Predicting and Diagnosing Occupational Diseases of Workers in the Agro-industrial Complex in Contact with Pesticides. 2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC). IEEE, 2022. pp. 290-294.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Karaeva A.P., Magaril E.R., Kiselev A.V., Cioca L.I. Screening of factors for assessing the environmental and economic efficiency of investment projects in the energy sector // International Journal of Environmental Research and Public Health. 2022. V. 19. №. 18. P. 11716.</mixed-citation><mixed-citation xml:lang="en">Karaeva A.P., Magaril E.R., Kiselev A.V., Cioca L.I. Screening of factors for assessing the environmental and economic efficiency of investment projects in the energy sector. International Journal of Environmental Research and Public Health. 2022. vol. 19. no. 18. pp. 11716.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Mutanov G., Ziyadin S., Shaikh A.A. Graphic model for evaluating the competitiveness and eco-efficiency of eco-innovative projects // Enterpreneurship and Sustainability Issues. 2019. V. 6. №. 4. doi: 10.9770/jesi.2019.6.4(41)</mixed-citation><mixed-citation xml:lang="en">Mutanov G., Ziyadin S., Shaikh A.A. Graphic model for evaluating the competitiveness and eco-efficiency of eco-innovative projects. Enterpreneurship and Sustainability Issues. 2019. vol. 6. no. 4. doi: 10.9770/jesi.2019.6.4(41)</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Tamošaitienė J., Khosravi M., Cristofaro M., Chan D.W. et al. Identification and prioritization of critical risk factors of commercial and recreational complex building projects: A Delphi study using the TOPSIS method // Applied Sciences. 2021. V. 11. №. 17. P. 7906.</mixed-citation><mixed-citation xml:lang="en">Tamošaitienė J., Khosravi M., Cristofaro M., Chan D.W. et al. Identification and prioritization of critical risk factors of commercial and recreational complex building projects: A Delphi study using the TOPSIS method. Applied Sciences. 2021. vol. 11. no. 17. pp. 7906.</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Ivlev I., Vacek J., Kneppo P. Multi-criteria decision analysis for supporting the selection of medical devices under uncertainty // European Journal of Operational Research. 2015. V. 247. №. 1. P. 216-228.</mixed-citation><mixed-citation xml:lang="en">Ivlev I., Vacek J., Kneppo P. Multi-criteria decision analysis for supporting the selection of medical devices under uncertainty. European Journal of Operational Research. 2015. vol. 247. no. 1. pp. 216-228.</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Ocampo-Melgar A., Bautista S., deSteiguer J.E., Orr B.J. Potential of an outranking multi-criteria approach to support the participatory assessment of land management actions // Journal of environmental management. 2017. V. 195. P. 70-77.</mixed-citation><mixed-citation xml:lang="en">Ocampo-Melgar A., Bautista S., deSteiguer J.E., Orr B.J. Potential of an outranking multi-criteria approach to support the participatory assessment of land management actions. Journal of environmental management. 2017. vol. 195. pp. 70-77.</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Attardi R., Cerreta M., Sannicandro V., Torre C.M. et al. Non-compensatory composite indicators for the evaluation of urban planning policy: The Land-Use Policy Efficiency Index (LUPEI) // European Journal of Operational Research. 2018. V. 264. №. 2. P. 491-507.</mixed-citation><mixed-citation xml:lang="en">Attardi R., Cerreta M., Sannicandro V., Torre C.M. et al. Non-compensatory composite indicators for the evaluation of urban planning policy: The Land-Use Policy Efficiency Index (LUPEI). European Journal of Operational Research. 2018. vol. 264. no. 2. pp. 491-507.</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Waibel S., Wu W.L., Smith M., Johnson L. et al. Selection of Pediatric Mental Health Quality Measures for Health System Improvement in British Columbia Based on a Modified Delphi Approach // Frontiers in pediatrics. 2022. V. 10. P. 866391.</mixed-citation><mixed-citation xml:lang="en">Waibel S., Wu W.L., Smith M., Johnson L. et al. Selection of Pediatric Mental Health Quality Measures for Health System Improvement in British Columbia Based on a Modified Delphi Approach. Frontiers in pediatrics. 2022. vol. 10. pp. 866391.</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Hassan S., Kumbhare D. Validity and diagnosis in physical and rehabilitation medicine: critical view and future perspectives // American Journal of Physical Medicine &amp; Rehabilitation. 2022. V. 101. №. 3. P. 262-269. doi: 10.1097/PHM.0000000000001768</mixed-citation><mixed-citation xml:lang="en">Hassan S., Kumbhare D. Validity and diagnosis in physical and rehabilitation medicine: critical view and future perspectives. American Journal of Physical Medicine &amp; Rehabilitation. 2022. vol. 101. no. 3. pp. 262-269. doi: 10.1097/PHM.0000000000001768</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Karpouzas G.A., Ramadan S.N., Cost C.E., Draper T.L. et al. Discordant patient–physician assessments of disease activity and its persistence adversely impact quality of life and work productivity in US Hispanics with rheumatoid arthritis // RMD open. 2017. V. 3. №. 2. P. e000551. doi: 10.15863/TAS.2019.06.74.88</mixed-citation><mixed-citation xml:lang="en">Karpouzas G.A., Ramadan S.N., Cost C.E., Draper T.L. et al. Discordant patient–physician assessments of disease activity and its persistence adversely impact quality of life and work productivity in US Hispanics with rheumatoid arthritis. RMD open. 2017. vol. 3. no. 2. pp. e000551. doi: 10.15863/TAS.2019.06.74.88</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
