LeCun Y, Bengio Y, Hinton G. Deep learning. Nature. 2015;521:436–44.

Article  CAS  PubMed  Google Scholar 

Johnson PM, Lin DJ, Zbontar J, Zitnick CL, Sriram A, Muckley M, et al. Deep learning reconstruction enables prospectively accelerated clinical knee MRI. Radiology. 2023;307:e220425.

Article  PubMed  Google Scholar 

Wasserthal J, Breit H-C, Meyer MT, Pradella M, Hinck D, Sauter AW, et al. TotalSegmentator: robust segmentation of 104 anatomic structures in CT images. Radiol Artif Intell. 2023;5:e230024.

Article  PubMed  PubMed Central  Google Scholar 

Chung R, Demers JP, Tiberio R, Savage CA, McNulty F, Stout M, et al. Implementation of an institution-wide rules-based automated CT protocoling system. AJR Am J Roentgenol. 2024;222:e2329806.

Article  PubMed  Google Scholar 

Zech JR, Santomartino SM, Yi PH. Artificial intelligence (AI) for fracture diagnosis: an overview of current products and considerations for clinical adoption, from the AJR special series on AI applications. AJR Am J Roentgenol. 2022;219:869–78.

Article  PubMed  Google Scholar 

Tejani AS, Elhalawani H, Moy L, Kohli M, Kahn CE Jr. Artificial intelligence and radiology education. Radiol Artif Intell. 2023;5:e220084.

Article  PubMed  Google Scholar 

Ngo B, Nguyen D, vanSonnenberg E. The cases for and against artificial intelligence in the medical school curriculum. Radiol Artif Intell. 2022;4:e220074.

Article  PubMed  PubMed Central  Google Scholar 

Richardson ML, Ojeda PI. A “bumper-car” curriculum for teaching deep learning to radiology residents. Acad Radiol. 2022;29:763–70.

Article  PubMed  Google Scholar 

Allen B, Agarwal S, Coombs L, Wald C, Dreyer K. 2020 ACR Data Science Institute Artificial Intelligence Survey. J Am Coll Radiol. 2021;18:1153–9.

Article  PubMed  Google Scholar 

Ahmed MI, Spooner B, Isherwood J, Lane M, Orrock E, Dennison A. A systematic review of the barriers to the implementation of artificial intelligence in healthcare. Cureus. 2023;15:e46454.

PubMed  PubMed Central  Google Scholar 

Tadavarthi Y, Vey B, Krupinski E, Prater A, Gichoya J, Safdar N, et al. The state of radiology AI: considerations for purchase decisions and current market offerings. Radiol Artif Intell. 2020;2:e200004.

Article  PubMed  PubMed Central  Google Scholar 

Newman-Toker DE, Peterson SM, Badihian S, Hassoon A, Nassery N, Parizadeh D, et al. 2022 Diagnostic errors in the emergency department: a systematic review. AHRQ Comparative Effectiveness Reviews. 22(23):EHC043

George MP, Bixby S. Frequently missed fractures in pediatric trauma: a pictorial review of plain film radiography. Radiol Clin North Am. 2019;57:843–55.

Article  PubMed  Google Scholar 

Lee A, Colen DL, Fox JP, Chang B, Lin IC. Pediatric hand and upper extremity injuries presenting to emergency departments in the United States: epidemiology and health care-associated costs. Hand. 2021;16:519–27.

Article  PubMed  Google Scholar 

Zech JR, Ezuma CO, Patel S, Edwards CR, Posner R, Hannon E, et al. Artificial intelligence improves resident detection of pediatric and young adult upper extremity fractures. Skeletal Radiol. 2024;53:2643–51.

Article  PubMed  Google Scholar 

Zech JR, Jaramillo D, Altosaar J, Popkin CA, Wong TT. 2023 Artificial intelligence to identify fractures on pediatric and young adult upper extremity radiographs. Pediatr Radiol

Mongan J, Moy L, Kahn CE. 2020 Checklist for artificial intelligence in medical imaging (CLAIM): a guide for authors and reviewers. Radiology: Artificial Intelligence. 2:e200029

Guermazi A, Tannoury C, Kompel AJ, Murakami AM, Ducarouge A, Gillibert A, et al. Improving radiographic fracture recognition performance and efficiency using artificial intelligence. Radiology. 2022;302:627–36.

Article  PubMed  Google Scholar 

Dong A, Jong MS-Y, King RB. 2020 How does prior knowledge influence learning engagement? The mediating roles of cognitive load and help-seeking. Front Psychol. 11:591203

Brod G. Toward an understanding of when prior knowledge helps or hinders learning. NPJ Sci Learn. 2021;6:24.

Article  PubMed  PubMed Central  Google Scholar 

Thompson RA, Zamboanga BL. Prior knowledge and its relevance to student achievement in introduction to psychology. Teach Psychol. 2003;30:96–101.

Article  Google Scholar 

Awan OA. The flipped classroom: how to do it in radiology education. Acad Radiol. 2021;28:1820–1.

Article  PubMed  Google Scholar 

Ali MF, Nadeem N, Khalid F, Anwar NM, Nabie G, Docherty C. SonoGames: sounds of the right kind introducing gamification into radiology training. BMC Res Notes. 2021;14:341.

Article  PubMed  PubMed Central  Google Scholar 

Duong MT, Rauschecker AM, Rudie JD, Chen P-H, Cook TS, Bryan RN, et al. Artificial intelligence for precision education in radiology. Br J Radiol. 2019;92:20190389.

Article  PubMed  PubMed Central  Google Scholar 

Lanier MH, Wheeler CA, Ballard DH. A new normal in radiology resident education: lessons learned from the COVID-19 pandemic. Radiographics. 2021;41:E71–2.

Article  PubMed  Google Scholar 

Rowe SP, Chu LC, Solnes LB, Soyer P, Fishman EK. Radiology education and training 2022–2032: are we in danger of fighting yesterday’s war? J Am Coll Radiol. 2023;20:103–4.

Article  PubMed  Google Scholar 

Santomartino SM, Putman K, Beheshtian E, Parekh VS, Yi PH. Evaluating the robustness of a deep learning bone age algorithm to clinical image variation using computational stress testing. Radiol Artif Intell. 2024;6:e230240.

Article  PubMed  PubMed Central  Google Scholar 

Cheng C-T, Chen C-C, Fu C-Y, Chaou C-H, Wu Y-T, Hsu C-P, et al. Artificial intelligence-based education assists medical students’ interpretation of hip fracture. Insights Imaging. 2020;11:119.

Article  PubMed  PubMed Central  Google Scholar 

Chen Y, Sun Z, Lin W, Xv Z, Su Q. 2024 Artificial intelligence in the training of radiology residents: a multicenter randomized controlled trial. J Cancer Educ [Internet]. Available from: https://doi.org/10.1007/s13187-024-02502-0