Artificial intelligence in radiology

Khafaji, Mawya A.; Safhi, Mohammed A.; Albadawi, Roia H.; Al-Amoudi, Salma O.; Shehata, Salah S; Toonsi, Fadi

doi:10.15537/smj.2022.43.1.20210337

Cited by 22 publications

(49 citation statements)

References 29 publications

(60 reference statements)

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“…In agreement with our results, these previous studies indicated low levels of AI knowledge among medical doctors and students [37][38][39][40], while dental students had moderate levels [41]. Nevertheless, as already mentioned, AI knowledge and literacy do not equal or predict AI readiness [28].…”

Section: Resultssupporting

confidence: 92%

“…Our study investigated AI readiness among medical and dental professionals, filling a gap in previous studies investigating readiness in the health field; prior studies instead concentrated on knowledge and attitudes [37][38][39][40][41][42].…”

Section: Resultsmentioning

confidence: 99%

“…However, the tool and readiness have not been thoroughly investigated among medical and dental professionals. A number of reviews and commentaries have discussed AI medical uses [34][35][36], and a few original papers have investigated knowledge and attitudes about AI among medical doctors or students [26,[37][38][39]. It is worth noting that many of these studies were specifically interested in AI use for radiology [26], particularly in Saudi Arabia [37][38][39].…”

Section: Introductionmentioning

confidence: 99%

“…A number of reviews and commentaries have discussed AI medical uses [34][35][36], and a few original papers have investigated knowledge and attitudes about AI among medical doctors or students [26,[37][38][39]. It is worth noting that many of these studies were specifically interested in AI use for radiology [26], particularly in Saudi Arabia [37][38][39]. In one multi-continent study, medical doctors and students had low levels of familiarity with AI, and only 2.9-9.8% had attended courses about AI [40].…”

Section: Introductionmentioning

confidence: 99%

“…Results of Saudi Arabian studies among medical doctors and students showed low levels of knowledge about AI despite the desire to learn. There were also concerns among respondents about the possibility of AI affecting their future employment [37][38][39]. In the dental field, few studies have investigated AI among dentists and dental students.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Medical and Dental Professionals Readiness for Artificial Intelligence for Saudi Arabia Vision 2030

Aboalshamat¹,

Alhuzali²,

Alalyani³

et al. 2022

Int J Pharm Res Allied Sci

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Healthcare Artificial Intelligence (AI) readiness is defined as adequate knowledge, attitudes, and skills such that health professionals are prepared for AI use in prevention, diagnosis, treatment, and rehabilitation. The aim of this study is to assess readiness levels for AI among medical and dental professionals in Saudi Arabia. A crosssectional study of 334 medical and dental students and practitioners in Saudi Arabia. Data were collected with a self-administered online questionnaire using the Medical Artificial Intelligence Readiness Scale (MAIRS). Data were analyzed using descriptive statistics and t-tests using SPSS software. The level of significance was set at p ≤ 0.05. Participants' MAIRS responses ranged from a mean (m) of 2.26 and a standard deviation (SD) of 1.17 to m = 2.76 and SD = 1.7 out of 5, indicating low levels of AI readiness. Dental professionals had significantly (p < 0.05) better readiness on 21 (of 22) MAIRS items. Only one item was significantly (p<0.05) associated with gender or qualifications. Participants had low readiness levels for AI, although dental professionals had significantly better scores. It is recommended that AI material and hands-on training be provided during undergraduate and postgraduate education for Saudi Arabian medical and dental professionals.

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Section: Resultssupporting

confidence: 92%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Medical and Dental Professionals Readiness for Artificial Intelligence for Saudi Arabia Vision 2030

Aboalshamat¹,

Alhuzali²,

Alalyani³

et al. 2022

Int J Pharm Res Allied Sci

View full text Add to dashboard Cite

show abstract

Attitudes, knowledge, and skills towards artificial intelligence among healthcare students: A systematic review

Baigi

Sarbaz

Ghaddaripouri

et al. 2023

Health Science Reports

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Background and Aims: This systematic review examined healthcare students' attitudes, knowledge, and skill in Artificial Intelligence (AI).Methods: On August 3, 2022, studies were retrieved from the PubMed, Embase, Scopus, and Web of Science databases. Preferred Reporting Items for Systematic Reviews and Meta-Analyses recommendations were followed. We included crosssectional studies that examined healthcare students' knowledge, attitudes, skills, and perceptions of AI in this review. Using the eligibility requirements as a guide, titles and abstracts were screened. Complete texts were then retrieved and independently reviewed per the eligibility requirements. To collect data, a standardized form was used.Results: Of the 38 included studies, 29 (76%) of healthcare students had a positive and promising attitude towards AI in the clinical profession and its use in he future; however, in nine of the studies (24%), students considered AI a threat to healthcare fields and had a negative attitude towards it. Furthermore, 26 studies evaluated the knowledge of healthcare students about AI. Among these, 18 studies evaluated the level of student knowledge as low (50%). On the other hand, in six of the studies, students' high knowledge of AI was reported, and two of the studies reported average student general knowledge (almost 50%). Of the six studies, four (67%) of the students had very low skills, so they stated that they had never worked with AI. Conclusion:Evidence from this review shows that healthcare students had a positive and promising attitude towards AI in medicine; however, most students had low knowledge and limited skills in working with AI. Face-to-face instruction, training manuals, and detailed instructions are therefore crucial for implementing and comprehending how AI technology works and raising students' knowledge of the advantages of AI.

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Efficiency, accuracy, and health professional's perspectives regarding artificial intelligence in radiology practice: A scoping review

He,

Liu,

et al. 2024

iRADIOLOGY

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In this scoping review, we evaluated the performance of artificial intelligence (AI) in clinical radiology practice and examined health professionals' perspectives regarding AI use in radiology. This review followed the Joanna Briggs Institute (JBI) methodological guidelines. We searched multiple databases and the gray literature from March 15, 2016 to December 31, 2023. Of 49 articles reviewed, 13 assessed the performance of AI in radiology clinical practice, and 36 examined the attitudes of health professionals toward the use of AI in radiology. In four separate studies, AI significantly improved the diagnostic sensitivity or detection rate. Furthermore, six articles emphasized a significant reduction in case reading times with AI use. Although three studies suggested an increase in specificity with the assistance of AI, these findings did not reach statistical significance. Health professionals expressed the belief that AI would have a significant impact on radiology but would not replace radiologists in the near future. Limited knowledge of AI was observed among health professionals, who supported increased education and explicit regulations and guidelines related to AI. Overall, AI can enhance diagnostic efficiency and accuracy in clinical radiology practice. However, knowledge gaps and the concerns of health professionals should be addressed by prioritizing education and reinforcing ethical and legal regulations to facilitate the advancement of AI use in radiology. This scoping review provides evidence toward a comprehensive understanding of AI's potential in clinical radiology practice, promoting its use and stimulating further discussion on related challenges and implications.

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Artificial intelligence in radiology

Cited by 22 publications

References 29 publications

Medical and Dental Professionals Readiness for Artificial Intelligence for Saudi Arabia Vision 2030

Medical and Dental Professionals Readiness for Artificial Intelligence for Saudi Arabia Vision 2030

Attitudes, knowledge, and skills towards artificial intelligence among healthcare students: A systematic review

Efficiency, accuracy, and health professional's perspectives regarding artificial intelligence in radiology practice: A scoping review

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