Zuhal Y Hamd, Amal I Alorainy, Monira I Aldhahi, Awadia Gareeballah, Naifah F Alsubaie, Shahad A Alshanaiber, Nehal S Almudayhesh, Raneem A Alyousef, Reem A AlNiwaider, Lamia A Bin Moammar, Mohamed M Abuzaid
{"title":"评估人工智能对沙特阿拉伯放射学临床实践的影响。","authors":"Zuhal Y Hamd, Amal I Alorainy, Monira I Aldhahi, Awadia Gareeballah, Naifah F Alsubaie, Shahad A Alshanaiber, Nehal S Almudayhesh, Raneem A Alyousef, Reem A AlNiwaider, Lamia A Bin Moammar, Mohamed M Abuzaid","doi":"10.2147/JMDH.S465508","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Artificial Intelligence (AI) is becoming integral to the health sector, particularly radiology, because it enhances diagnostic accuracy and optimizes patient care. This study aims to assess the awareness and acceptance of AI among radiology professionals in Saudi Arabia, identifying the educational and training needs to bridge knowledge gaps and enhance AI-related competencies.</p><p><strong>Methods: </strong>This cross-sectional observational study surveyed radiology professionals across various hospitals in Saudi Arabia. Participants were recruited through multiple channels, including direct invitations, emails, social media, and professional societies. The survey comprised four sections: demographic details, perceptions of AI, knowledge about AI, and willingness to adopt AI in clinical practice.</p><p><strong>Results: </strong>Out of 374 radiology professionals surveyed, 45.2% acknowledged AI's significant impact on their field. Approximately 44% showed enthusiasm for AI adoption. However, 58.6% reported limited AI knowledge and inadequate training, with 43.6% identifying skill development and the complexity of AI educational programs as major barriers to implementation.</p><p><strong>Conclusion: </strong>While radiology professionals in Saudi Arabia are generally positive about integrating AI into clinical practice, significant gaps in knowledge and training need to be addressed. Tailored educational programs are essential to fully leverage AI's potential in improving medical imaging practices and patient care outcomes.</p>","PeriodicalId":16357,"journal":{"name":"Journal of Multidisciplinary Healthcare","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11476743/pdf/","citationCount":"0","resultStr":"{\"title\":\"Evaluation of the Impact of Artificial Intelligence on Clinical Practice of Radiology in Saudi Arabia.\",\"authors\":\"Zuhal Y Hamd, Amal I Alorainy, Monira I Aldhahi, Awadia Gareeballah, Naifah F Alsubaie, Shahad A Alshanaiber, Nehal S Almudayhesh, Raneem A Alyousef, Reem A AlNiwaider, Lamia A Bin Moammar, Mohamed M Abuzaid\",\"doi\":\"10.2147/JMDH.S465508\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Artificial Intelligence (AI) is becoming integral to the health sector, particularly radiology, because it enhances diagnostic accuracy and optimizes patient care. This study aims to assess the awareness and acceptance of AI among radiology professionals in Saudi Arabia, identifying the educational and training needs to bridge knowledge gaps and enhance AI-related competencies.</p><p><strong>Methods: </strong>This cross-sectional observational study surveyed radiology professionals across various hospitals in Saudi Arabia. Participants were recruited through multiple channels, including direct invitations, emails, social media, and professional societies. The survey comprised four sections: demographic details, perceptions of AI, knowledge about AI, and willingness to adopt AI in clinical practice.</p><p><strong>Results: </strong>Out of 374 radiology professionals surveyed, 45.2% acknowledged AI's significant impact on their field. Approximately 44% showed enthusiasm for AI adoption. However, 58.6% reported limited AI knowledge and inadequate training, with 43.6% identifying skill development and the complexity of AI educational programs as major barriers to implementation.</p><p><strong>Conclusion: </strong>While radiology professionals in Saudi Arabia are generally positive about integrating AI into clinical practice, significant gaps in knowledge and training need to be addressed. Tailored educational programs are essential to fully leverage AI's potential in improving medical imaging practices and patient care outcomes.</p>\",\"PeriodicalId\":16357,\"journal\":{\"name\":\"Journal of Multidisciplinary Healthcare\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-10-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11476743/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Multidisciplinary Healthcare\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2147/JMDH.S465508\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Multidisciplinary Healthcare","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/JMDH.S465508","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
Evaluation of the Impact of Artificial Intelligence on Clinical Practice of Radiology in Saudi Arabia.
Background: Artificial Intelligence (AI) is becoming integral to the health sector, particularly radiology, because it enhances diagnostic accuracy and optimizes patient care. This study aims to assess the awareness and acceptance of AI among radiology professionals in Saudi Arabia, identifying the educational and training needs to bridge knowledge gaps and enhance AI-related competencies.
Methods: This cross-sectional observational study surveyed radiology professionals across various hospitals in Saudi Arabia. Participants were recruited through multiple channels, including direct invitations, emails, social media, and professional societies. The survey comprised four sections: demographic details, perceptions of AI, knowledge about AI, and willingness to adopt AI in clinical practice.
Results: Out of 374 radiology professionals surveyed, 45.2% acknowledged AI's significant impact on their field. Approximately 44% showed enthusiasm for AI adoption. However, 58.6% reported limited AI knowledge and inadequate training, with 43.6% identifying skill development and the complexity of AI educational programs as major barriers to implementation.
Conclusion: While radiology professionals in Saudi Arabia are generally positive about integrating AI into clinical practice, significant gaps in knowledge and training need to be addressed. Tailored educational programs are essential to fully leverage AI's potential in improving medical imaging practices and patient care outcomes.
期刊介绍:
The Journal of Multidisciplinary Healthcare (JMDH) aims to represent and publish research in healthcare areas delivered by practitioners of different disciplines. This includes studies and reviews conducted by multidisciplinary teams as well as research which evaluates or reports the results or conduct of such teams or healthcare processes in general. The journal covers a very wide range of areas and we welcome submissions from practitioners at all levels and from all over the world. Good healthcare is not bounded by person, place or time and the journal aims to reflect this. The JMDH is published as an open-access journal to allow this wide range of practical, patient relevant research to be immediately available to practitioners who can access and use it immediately upon publication.