TY - JOUR
T1 - Ai for doctors—a course to educate medical professionals in artificial intelligence for medical imaging
AU - Hedderich, Dennis M.
AU - Keicher, Matthias
AU - Wiestler, Benedikt
AU - Gruber, Martin J.
AU - Burwinkel, Hendrik
AU - Hinterwimmer, Florian
AU - Czempiel, Tobias
AU - Spiro, Judith E.
AU - Dos Santos, Daniel Pinto
AU - Heim, Dominik
AU - Zimmer, Claus
AU - Rückert, Daniel
AU - Kirschke, Jan S.
AU - Navab, Nassir
N1 - Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/10
Y1 - 2021/10
N2 - Successful adoption of artificial intelligence (AI) in medical imaging requires medical professionals to understand underlying principles and techniques. However, educational offerings tailored to the need of medical professionals are scarce. To fill this gap, we created the course “AI for Doctors: Medical Imaging”. An analysis of participants’ opinions on AI and self-perceived skills rated on a five-point Likert scale was conducted before and after the course. The participants’ attitude towards AI in medical imaging was very optimistic before and after the course. However, deeper knowledge of AI and the process for validating and deploying it resulted in significantly less overoptimism with respect to perceivable patient benefits through AI (p = 0.020). Self-assessed skill ratings significantly improved after the course, and the appreciation of the course content was very positive. However, we observed a substantial drop-out rate, mostly attributed to the lack of time of medical professionals. There is a high demand for educational offerings regarding AI in medical imaging among medical professionals, and better education may lead to a more realistic appreciation of clinical adoption. However, time constraints imposed by a busy clinical schedule need to be taken into account for successful education of medical professionals.
AB - Successful adoption of artificial intelligence (AI) in medical imaging requires medical professionals to understand underlying principles and techniques. However, educational offerings tailored to the need of medical professionals are scarce. To fill this gap, we created the course “AI for Doctors: Medical Imaging”. An analysis of participants’ opinions on AI and self-perceived skills rated on a five-point Likert scale was conducted before and after the course. The participants’ attitude towards AI in medical imaging was very optimistic before and after the course. However, deeper knowledge of AI and the process for validating and deploying it resulted in significantly less overoptimism with respect to perceivable patient benefits through AI (p = 0.020). Self-assessed skill ratings significantly improved after the course, and the appreciation of the course content was very positive. However, we observed a substantial drop-out rate, mostly attributed to the lack of time of medical professionals. There is a high demand for educational offerings regarding AI in medical imaging among medical professionals, and better education may lead to a more realistic appreciation of clinical adoption. However, time constraints imposed by a busy clinical schedule need to be taken into account for successful education of medical professionals.
KW - Artificial intelligence
KW - Clinical translation
KW - Continuing medical education
KW - Machine learning
KW - Medical imaging
UR - http://www.scopus.com/inward/record.url?scp=85116271932&partnerID=8YFLogxK
U2 - 10.3390/healthcare9101278
DO - 10.3390/healthcare9101278
M3 - Article
AN - SCOPUS:85116271932
SN - 2227-9032
VL - 9
JO - Healthcare (Switzerland)
JF - Healthcare (Switzerland)
IS - 10
M1 - 1278
ER -