Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study
Background: In the past vicennium, several artificial intelligence (AI) and machine learning (ML) models have been developed to assist in medical diagnosis, decision making, and design of treatment protocols. The number of active pathologists in Poland is low, prolonging tumor patients’ diagnosis an...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Journal of Personalized Medicine |
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| Online Access: | https://www.mdpi.com/2075-4426/13/6/962 |
| _version_ | 1797593940877115392 |
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| author | Alhassan Ali Ahmed Agnieszka Brychcy Mohamed Abouzid Martin Witt Elżbieta Kaczmarek |
| author_facet | Alhassan Ali Ahmed Agnieszka Brychcy Mohamed Abouzid Martin Witt Elżbieta Kaczmarek |
| author_sort | Alhassan Ali Ahmed |
| collection | DOAJ |
| description | Background: In the past vicennium, several artificial intelligence (AI) and machine learning (ML) models have been developed to assist in medical diagnosis, decision making, and design of treatment protocols. The number of active pathologists in Poland is low, prolonging tumor patients’ diagnosis and treatment journey. Hence, applying AI and ML may aid in this process. Therefore, our study aims to investigate the knowledge of using AI and ML methods in the clinical field in pathologists in Poland. To our knowledge, no similar study has been conducted. Methods: We conducted a cross-sectional study targeting pathologists in Poland from June to July 2022. The questionnaire included self-reported information on AI or ML knowledge, experience, specialization, personal thoughts, and level of agreement with different aspects of AI and ML in medical diagnosis. Data were analyzed using IBM<sup>®</sup> SPSS<sup>®</sup> Statistics v.26, PQStat Software v.1.8.2.238, and RStudio Build 351. Results: Overall, 68 pathologists in Poland participated in our study. Their average age and years of experience were 38.92 ± 8.88 and 12.78 ± 9.48 years, respectively. Approximately 42% used AI or ML methods, which showed a significant difference in the knowledge gap between those who never used it (OR = 17.9, 95% CI = 3.57–89.79, <i>p</i> < 0.001). Additionally, users of AI had higher odds of reporting satisfaction with the speed of AI in the medical diagnosis process (OR = 4.66, 95% CI = 1.05–20.78, <i>p</i> = 0.043). Finally, significant differences (<i>p</i> = 0.003) were observed in determining the liability for legal issues used by AI and ML methods. Conclusion: Most pathologists in this study did not use AI or ML models, highlighting the importance of increasing awareness and educational programs regarding applying AI and ML in medical diagnosis. |
| first_indexed | 2024-03-11T02:16:40Z |
| format | Article |
| id | doaj.art-b69e092309484e9f9087f2d3930b30c0 |
| institution | Directory Open Access Journal |
| issn | 2075-4426 |
| language | English |
| last_indexed | 2024-03-11T02:16:40Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Personalized Medicine |
| spelling | doaj.art-b69e092309484e9f9087f2d3930b30c02023-11-18T11:11:10ZengMDPI AGJournal of Personalized Medicine2075-44262023-06-0113696210.3390/jpm13060962Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional StudyAlhassan Ali Ahmed0Agnieszka Brychcy1Mohamed Abouzid2Martin Witt3Elżbieta Kaczmarek4Department of Bioinformatics and Computational Biology, Poznan University of Medical Sciences, 61-806 Poznan, PolandDepartment of Clinical Patomorphology, Heliodor Swiecicki Clinical Hospital of the Poznan University of Medical Sciences, 61-806 Poznan, PolandDoctoral School, Poznan University of Medical Sciences, 61-806 Poznan, PolandDepartment of Anatomy, Rostock University Medical Centre, 18057 Rostock, GermanyDepartment of Bioinformatics and Computational Biology, Poznan University of Medical Sciences, 61-806 Poznan, PolandBackground: In the past vicennium, several artificial intelligence (AI) and machine learning (ML) models have been developed to assist in medical diagnosis, decision making, and design of treatment protocols. The number of active pathologists in Poland is low, prolonging tumor patients’ diagnosis and treatment journey. Hence, applying AI and ML may aid in this process. Therefore, our study aims to investigate the knowledge of using AI and ML methods in the clinical field in pathologists in Poland. To our knowledge, no similar study has been conducted. Methods: We conducted a cross-sectional study targeting pathologists in Poland from June to July 2022. The questionnaire included self-reported information on AI or ML knowledge, experience, specialization, personal thoughts, and level of agreement with different aspects of AI and ML in medical diagnosis. Data were analyzed using IBM<sup>®</sup> SPSS<sup>®</sup> Statistics v.26, PQStat Software v.1.8.2.238, and RStudio Build 351. Results: Overall, 68 pathologists in Poland participated in our study. Their average age and years of experience were 38.92 ± 8.88 and 12.78 ± 9.48 years, respectively. Approximately 42% used AI or ML methods, which showed a significant difference in the knowledge gap between those who never used it (OR = 17.9, 95% CI = 3.57–89.79, <i>p</i> < 0.001). Additionally, users of AI had higher odds of reporting satisfaction with the speed of AI in the medical diagnosis process (OR = 4.66, 95% CI = 1.05–20.78, <i>p</i> = 0.043). Finally, significant differences (<i>p</i> = 0.003) were observed in determining the liability for legal issues used by AI and ML methods. Conclusion: Most pathologists in this study did not use AI or ML models, highlighting the importance of increasing awareness and educational programs regarding applying AI and ML in medical diagnosis.https://www.mdpi.com/2075-4426/13/6/962artificial intelligencemachine learninghistopathologymedical diagnosiscancertumor pathology |
| spellingShingle | Alhassan Ali Ahmed Agnieszka Brychcy Mohamed Abouzid Martin Witt Elżbieta Kaczmarek Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study Journal of Personalized Medicine artificial intelligence machine learning histopathology medical diagnosis cancer tumor pathology |
| title | Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study |
| title_full | Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study |
| title_fullStr | Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study |
| title_full_unstemmed | Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study |
| title_short | Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study |
| title_sort | perception of pathologists in poland of artificial intelligence and machine learning in medical diagnosis a cross sectional study |
| topic | artificial intelligence machine learning histopathology medical diagnosis cancer tumor pathology |
| url | https://www.mdpi.com/2075-4426/13/6/962 |
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