An Artificial Intelligence Training Workshop for Diagnostic Radiology                     Residents

Hu, Ricky; Rizwan, Arsalan P.; Hu, Zoe; Li, Anthony; Chung, Andrew D.; Kwan, Benjamin Y. M.

doi:10.1148/ryai.220170

Cited by 4 publications

(5 citation statements)

References 31 publications

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“…Also in previous surveys, radiologists expressed high interest in AI, but regularly complained about missing access to it and lacking formal training 20,24,29 . Arguably, our study suggests the teaching effect of exposure to the new technology in clinical routine via a “hands-on” approach, while additional structured courses and curricula are desirable, and have already been developed and successfully evaluated 31,32 …”

Section: Discussionmentioning

confidence: 54%

“…20,24,29 Arguably, our study suggests the teaching effect of exposure to the new technology in clinical routine via a "hands-on" approach, while additional structured courses and curricula are desirable, and have already been developed and successfully evaluated. 31,32 Overall, we saw a unanimous wish among participants to "continue using AI" and a strong endorsement for the use of "more clinical AI," which shows the strong perceived benefits of supportive AI solutions in clinical routine. However, there were some points of critique, which have to be taken into account.…”

Section: Discussionmentioning

confidence: 94%

“…Numerous surveys have outlined a growing interest of radiologists and other physicians in AI, but also highlighted often little exposure to the new technology (both clinically and scientifically), mainly due to the lack of clinical implementation and missing formal training 15–17,24–30 . Several structured courses and curricula have been proposed and evaluated successfully, 31,32 and the leading radiological societies also started to offer their own resources and specialized certificates 33 …”

mentioning

confidence: 99%

“…23 Numerous surveys have outlined a growing interest of radiologists and other physicians in AI, but also highlighted often little exposure to the new technology (both clinically and scientifically), mainly due to the lack of clinical implementation and missing formal training. [15][16][17][24][25][26][27][28][29][30] Several structured courses and curricula have been proposed and evaluated successfully, 31,32 and the leading radiological societies also started to offer their own resources and specialized certificates. 33 The purpose of this study was to analyze the effect of implementing an established AI solution into clinical routine on physicians' perception and knowledge, by longitudinally surveying radiologists and traumatologists before and after, and matching them on an individual level by self-generated identification codes.…”

mentioning

confidence: 99%

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Implementing Artificial Intelligence for Emergency Radiology Impacts Physicians' Knowledge and Perception

Hoppe,

Rueckel,

Dikhtyar

et al. 2023

Invest Radiol

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Purpose The aim of this study was to evaluate the impact of implementing an artificial intelligence (AI) solution for emergency radiology into clinical routine on physicians' perception and knowledge. Materials and Methods A prospective interventional survey was performed pre-implementation and 3 months post-implementation of an AI algorithm for fracture detection on radiographs in late 2022. Radiologists and traumatologists were asked about their knowledge and perception of AI on a 7-point Likert scale (−3, “strongly disagree”; +3, “strongly agree”). Self-generated identification codes allowed matching the same individuals pre-intervention and post-intervention, and using Wilcoxon signed rank test for paired data. Results A total of 47/71 matched participants completed both surveys (66% follow-up rate) and were eligible for analysis (34 radiologists [72%], 13 traumatologists [28%], 15 women [32%]; mean age, 34.8 ± 7.8 years). Postintervention, there was an increase that AI “reduced missed findings” (1.28 [pre] vs 1.94 [post], P = 0.003) and made readers “safer” (1.21 vs 1.64, P = 0.048), but not “faster” (0.98 vs 1.21, P = 0.261). There was a rising disagreement that AI could “replace the radiological report” (−2.04 vs −2.34, P = 0.038), as well as an increase in self-reported knowledge about “clinical AI,” its “chances,” and its “risks” (0.40 vs 1.00, 1.21 vs 1.70, and 0.96 vs 1.34; all P's ≤ 0.028). Radiologists used AI results more frequently than traumatologists (P < 0.001) and rated benefits higher (all P's ≤ 0.038), whereas senior physicians were less likely to use AI or endorse its benefits (negative correlation with age, −0.35 to 0.30; all P's ≤ 0.046). Conclusions Implementing AI for emergency radiology into clinical routine has an educative aspect and underlines the concept of AI as a “second reader,” to support and not replace physicians.

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Section: Discussionmentioning

confidence: 54%

Section: Discussionmentioning

confidence: 94%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Implementing Artificial Intelligence for Emergency Radiology Impacts Physicians' Knowledge and Perception

Hoppe,

Rueckel,

Dikhtyar

et al. 2023

Invest Radiol

View full text Add to dashboard Cite

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“…Enhancing the quality of teacher training students can provide an abundant qualified reserve army for the construction of high-quality teams [28] . As the future frontline teachers of basic education, teacher trainees should have the concept of lifelong learning, be willing to accept the new technology of artificial intelligence, and actively use it in their daily life and learning to improve the efficiency of their learning and teaching.…”

Section: Student Level: Building a Sense Of Active Learning And Conti...mentioning

confidence: 99%

Research on the Current Situation of Artificial Intelligence Literacy of Teacher Trainees and Strategies to Improve It

2024

aetp

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The era of artificial intelligence has put forward new requirements for the necessary literacy of teachers, and teacher trainees are the backbone of future teaching positions, so strengthening the cultivation of their AI literacy is an intrinsic need to realize the development of high quality in education. This study mainly adopts the questionnaire survey method and interview method to investigate 430 teacher trainees from H Teachers College, to understand the current status of the development of teacher trainees' artificial intelligence literacy, to clarify the existing problems and to propose corresponding enhancement strategies. The results of the study show that the level of teacher students' artificial intelligence literacy needs to be improved, specifically, the teacher students' artificial intelligence knowledge reserve is insufficient, the artificial intelligence ability is weak, and there is room for strengthening the artificial intelligence awareness. Based on this, the article puts forward the enhancement strategy of teacher trainees' artificial intelligence literacy, aiming to provide a certain reference basis for strengthening the cultivation of teacher trainees' artificial intelligence literacy.

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A scoping review of artificial intelligence in medical education: BEME Guide No. 84

Gordon,

Daniel,

Ajiboye

et al. 2024

Medical Teacher

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An Artificial Intelligence Training Workshop for Diagnostic Radiology Residents

Cited by 4 publications

References 31 publications

Implementing Artificial Intelligence for Emergency Radiology Impacts Physicians' Knowledge and Perception

Implementing Artificial Intelligence for Emergency Radiology Impacts Physicians' Knowledge and Perception

Research on the Current Situation of Artificial Intelligence Literacy of Teacher Trainees and Strategies to Improve It

A scoping review of artificial intelligence in medical education: BEME Guide No. 84

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