{"id":2827,"date":"2024-05-30T08:19:39","date_gmt":"2024-05-30T05:19:39","guid":{"rendered":"https:\/\/fti.dp.ua\/conf\/?p=2827"},"modified":"2024-05-30T08:19:40","modified_gmt":"2024-05-30T05:19:40","slug":"05307-0819","status":"publish","type":"post","link":"https:\/\/fti.dp.ua\/conf\/2024\/05307-0819\/","title":{"rendered":"Research and integration of SVM algorithm in information and measurement technologies for choosing the profession of doctor"},"content":{"rendered":"\n

Research and integration of SVM algorithm in information and measurement technologies for choosing the profession of doctor<\/h1>\n\n\n\n
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Oleksii Izmalkov<\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/h5>\n\n\n\n

ORCID: https:\/\/orcid.org\/0009-0005-3732-7474<\/a><\/em><\/p>\n\n\n\n

Oles Honchar Dnipro National University<\/em><\/p>\n<\/div><\/div>\n\n\n\n

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This study defines the application of advanced information and measurement technologies in psychophysical analysis to improve the career selection process for medical professions. Traditional career guidance methods often rely on subjective assessments, which can lead to incorrect career choices, decreased job satisfaction, and increased burnout levels. This study aims to address these issues by integrating objective and comprehensive assessment tools, such as biometric sensors, virtual reality simulations, psychometric assessments, and machine learning algorithms, with a particular focus on Support Vector Machines (SVM). SVM is used in this study to analyze complex multidimensional data and identify patterns that correlate psychophysical traits with a suitable medical career. These technologies allow for precise measurement of cognitive abilities, psychomotor skills, and personality traits, leading to more accurate career recommendations. The study includes a detailed literature review, selection and evaluation of relevant technologies, and the development of a psychophysical analysis model using SVM. Data collection from individuals seeking career guidance in the medical field provides a reliable dataset for training and evaluation of the model. The model’s effectiveness is assessed using metrics such as accuracy, precision, recall, and F1 score with cross-validation to ensure its reliability. The implementation and testing of the SVM-based model in real-world conditions confirm its practical applicability. Interpretation methods, such as SHAP (SHapley Additive exPlanations), are used to explain the model’s predictions, ensuring transparency and user trust. Feedback from users and career advisors helps to refine the model, enhance its accuracy, and improve usability. This study contributes to the field by demonstrating how information and measurement technologies, particularly SVM, can revolutionize career guidance in medical professions. The findings indicate that these technologies can significantly improve the alignment between an individual’s psychophysical traits and their chosen profession.<\/p>\n\n\n\n

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CIMS 2024 Vernal<\/a><\/div>\n\n
Information Technology and Cybersecurity<\/a><\/div><\/div>\n\n\n\n
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Research and integration of SVM algorithm in information and measurement technologies for choosing the profession of doctor Oleksii Izmalkov ORCID: https:\/\/orcid.org\/0009-0005-3732-7474 Oles Honchar Dnipro National University This study defines the application of advanced information and measurement technologies in psychophysical analysis to improve the career selection process for medical professions. Traditional career guidance methods often rely on subjective assessments, which can lead to incorrect career choices, decreased job satisfaction, and increased burnout levels. This study aims to address these issues by … <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[35],"tags":[29],"class_list":["post-2827","post","type-post","status-publish","format-standard","hentry","category-info-tech-2","tag-cims-2024-vernal"],"_links":{"self":[{"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/posts\/2827","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/comments?post=2827"}],"version-history":[{"count":1,"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/posts\/2827\/revisions"}],"predecessor-version":[{"id":2828,"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/posts\/2827\/revisions\/2828"}],"wp:attachment":[{"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/media?parent=2827"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/categories?post=2827"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/tags?post=2827"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}