| 1 |
Arrighi JA, Mendes LA, McConnaughey S; ACC Competency Management Committee. Competency-based medical education for fellowship training during the COVID-19 pandemic [J]. J Am Coll Cardiol, 2021, 77(13): 1681-1683.
|
| 2 |
Jabbour S, Fouhey D, Shepard S, et al. Measuring the impact of ai in the diagnosis of hospitalized patients: a randomized clinical vignette survey study [J]. JAMA, 2023, 330(23): 2275-2284.
|
| 3 |
Cheungpasitporn W, Thongprayoon C, Kashani KB. Advances in critical care nephrology through artificial intelligence [J]. Curr Opin Crit Care, 2024, 30(6): 533-541.
|
| 4 |
Gruda D. Three ways ChatGPT helps me in my academic writing [J]. Nature, 2024. Epub ahead of print.
|
| 5 |
Cooper A, Rodman A. AI and medical education - a 21st-century Pandora's Box [J]. N Engl J Med, 2023, 389(5): 385-387.
|
| 6 |
Liu VX. The future of AI in critical care is augmented, not artificial, intelligence [J]. Crit Care, 2020, 24(1): 673.
|
| 7 |
Charow R, Jeyakumar T, Younus S, et al. Artificial intelligence education programs for health care professionals: scoping review [J]. JMIR Med Educ, 2021, 7(4): e31043.
|
| 8 |
中国住院医师培训精英教学医院联盟. 中国住院医师培训精英教学医院联盟住院医师核心胜任力框架共识 [J]. 协和医学杂志, 2022, 13(1): 17-23.
|
| 9 |
Barrett H, Bion JF. An international survey of training in adult intensive care medicine [J]. Intensive Care Med, 2005 31(4): 553-561.
|
| 10 |
CoBaTrICE Collaboration, Bion JF, Barrett H. Development of core competencies for an international training programme in intensive care medicine [J]. Intensive Care Med, 2006, 32(9): 1371-1383.
|
| 11 |
Hu X, Xi X, Ma P, et al. Consensus development of core competencies in intensive and critical care medicine training in China [J]. Crit Care, 2016, 20(1): 330.
|
| 12 |
Bruno RR, Wolff G, Wernly B, et al. Virtual and augmented reality in critical care medicine: the patient's, clinician's, and researcher's perspective [J]. Crit Care, 2022, 26(1): 326.
|
| 13 |
Patrawalla P, Mayo P, Morris A. Closing the competency gap: preparing for the New Pulmonary and Critical Care Medicine and Critical Care Medicine Accreditation Council on graduate medical education requirements for critical care ultrasound training [J]. Chest, 2024, 166(2): 257-258.
|
| 14 |
Pastis NJ, Vanderbilt AA, Tanner NT, et al. Construct validity of the Simbionix bronch mentor simulator for essential bronchoscopic skills [J]. J Bronchology Interv Pulmonol, 2014, 21(4): 314-321.
|
| 15 |
Ost D, DeRosiers A, Britt EJ, et al. Assessment of a bronchoscopy simulator [J]. Am J Respir Crit Care Med, 2001, 164(12): 2248-2255.
|
| 16 |
Cold KM, Xie S, Nielsen AO, et al. Artificial intelligence improves novices' bronchoscopy performance: a randomized controlled trial in a simulated setting [J]. Chest, 2024, 165(2): 405-413.
|
| 17 |
Seam N, Lee AJ, Vennero M, et al. Simulation Training in the ICU [J]. Chest, 2019, 156(6): 1223-1233.
|
| 18 |
Fernandez R, Rosenman ED, Olenick J, et al. Simulation-based team leadership training improves team leadership during actual trauma resuscitations: a randomized controlled trial [J]. Crit Care Med, 2020, 48(1): 73-82.
|
| 19 |
Semeraro F, Cascella M, Montomoli J, et al. Comparative analysis of AI tools for disseminating CPR guidelines: Implications for cardiac arrest education [J]. Resuscitation, 2025, 208: 110528.
|
| 20 |
Collins JW, Marcus HJ, Ghazi A, et al. Ethical implications of AI in robotic surgical training: a Delphi consensus statement [J]. Eur Urol Focus, 2022, 8(2): 613-622.
|
| 21 |
Knopp MI, Warm EJ, Weber D, et al. AI-enabled medical education: threads of change, promising futures, and risky realities across four potential future worlds [J]. JMIR Med Educ, 2023, 9: e50373.
|