Artificial Intelligence (AI) Competency and Educational Needs: Results of an AI Survey of Members of the European Society of Pediatric Endoscopic Surgeons (ESPES)
<b>Background</b>: Advancements in artificial intelligence (AI) and machine learning (ML) are set to revolutionize healthcare, particularly in fields like endoscopic surgery that heavily rely on digital imaging. However, to effectively integrate these technologies and drive future innova...
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MDPI AG
2024-12-01
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| author | Holger Till Hesham Elsayed Maria Escolino Ciro Esposito Sameh Shehata Georg Singer |
| author_facet | Holger Till Hesham Elsayed Maria Escolino Ciro Esposito Sameh Shehata Georg Singer |
| author_sort | Holger Till |
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| description | <b>Background</b>: Advancements in artificial intelligence (AI) and machine learning (ML) are set to revolutionize healthcare, particularly in fields like endoscopic surgery that heavily rely on digital imaging. However, to effectively integrate these technologies and drive future innovations, pediatric surgeons need specialized AI/ML skills. This survey evaluated the current level of readiness and educational needs regarding AI/ML among members of the European Society of Pediatric Endoscopic Surgeons (ESPES). <b>Methods</b>: A structured survey was distributed via LimeSurvey to ESPES members via email before and during the 2024 Annual Conference. Responses were collected over four weeks with voluntary, anonymous participation. Quantitative data were analyzed using descriptive statistics. <b>Results</b>: A total of 125 responses were received. Two-thirds (65%) of respondents rated their AI/ML understanding as basic, with only 6% reporting advanced knowledge. Most respondents (86%) had no formal AI/ML training. Some respondents (31%) used AI/ML tools in their practice, mainly for diagnostic imaging, surgical planning, and predictive analytics; 42% of the respondents used these tools weekly. The majority (95%) expressed interest in further AI/ML training, preferring online courses, workshops, and hands-on sessions. Concerns about AI/ML in pediatric surgery were high (85%), especially regarding data bias (98%). Half of respondents (51%) expect AI/ML to play a significant role in advancing robotic surgery, oncology, and minimally invasive techniques. A strong majority (84%) felt that the ESPES should lead AI education in pediatric surgery. <b>Conclusions</b>: This survey presents the ESPES with a unique opportunity to develop a competency map of its membership’s AI/ML skills and develop targeted educational programs, thus positioning the society to take the lead in AI education and the advancement of AI solutions in pediatric endosurgery. |
| format | Article |
| id | doaj-art-835398bedcad40508b5fdb28dcb1471d |
| institution | Kabale University |
| issn | 2227-9067 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Children |
| spelling | doaj-art-835398bedcad40508b5fdb28dcb1471d2025-01-24T13:26:57ZengMDPI AGChildren2227-90672024-12-01121610.3390/children12010006Artificial Intelligence (AI) Competency and Educational Needs: Results of an AI Survey of Members of the European Society of Pediatric Endoscopic Surgeons (ESPES)Holger Till0Hesham Elsayed1Maria Escolino2Ciro Esposito3Sameh Shehata4Georg Singer5Department of Pediatric and Adolescent Surgery, Medical University of Graz, 8036 Graz, AustriaDepartment of Pediatric and Adolescent Surgery, Medical University of Graz, 8036 Graz, AustriaDivision of Pediatric Surgery, Federico II University Hospital, 80131 Naples, ItalyDivision of Pediatric Surgery, Federico II University Hospital, 80131 Naples, ItalyDepartment of Pediatric Surgery, University of Alexandria, Alexandria 5424041, EgyptDepartment of Pediatric and Adolescent Surgery, Medical University of Graz, 8036 Graz, Austria<b>Background</b>: Advancements in artificial intelligence (AI) and machine learning (ML) are set to revolutionize healthcare, particularly in fields like endoscopic surgery that heavily rely on digital imaging. However, to effectively integrate these technologies and drive future innovations, pediatric surgeons need specialized AI/ML skills. This survey evaluated the current level of readiness and educational needs regarding AI/ML among members of the European Society of Pediatric Endoscopic Surgeons (ESPES). <b>Methods</b>: A structured survey was distributed via LimeSurvey to ESPES members via email before and during the 2024 Annual Conference. Responses were collected over four weeks with voluntary, anonymous participation. Quantitative data were analyzed using descriptive statistics. <b>Results</b>: A total of 125 responses were received. Two-thirds (65%) of respondents rated their AI/ML understanding as basic, with only 6% reporting advanced knowledge. Most respondents (86%) had no formal AI/ML training. Some respondents (31%) used AI/ML tools in their practice, mainly for diagnostic imaging, surgical planning, and predictive analytics; 42% of the respondents used these tools weekly. The majority (95%) expressed interest in further AI/ML training, preferring online courses, workshops, and hands-on sessions. Concerns about AI/ML in pediatric surgery were high (85%), especially regarding data bias (98%). Half of respondents (51%) expect AI/ML to play a significant role in advancing robotic surgery, oncology, and minimally invasive techniques. A strong majority (84%) felt that the ESPES should lead AI education in pediatric surgery. <b>Conclusions</b>: This survey presents the ESPES with a unique opportunity to develop a competency map of its membership’s AI/ML skills and develop targeted educational programs, thus positioning the society to take the lead in AI education and the advancement of AI solutions in pediatric endosurgery.https://www.mdpi.com/2227-9067/12/1/6artificial intelligencemachine learningimage analysissurgical planningdata biaspediatric surgery |
| spellingShingle | Holger Till Hesham Elsayed Maria Escolino Ciro Esposito Sameh Shehata Georg Singer Artificial Intelligence (AI) Competency and Educational Needs: Results of an AI Survey of Members of the European Society of Pediatric Endoscopic Surgeons (ESPES) Children artificial intelligence machine learning image analysis surgical planning data bias pediatric surgery |
| title | Artificial Intelligence (AI) Competency and Educational Needs: Results of an AI Survey of Members of the European Society of Pediatric Endoscopic Surgeons (ESPES) |
| title_full | Artificial Intelligence (AI) Competency and Educational Needs: Results of an AI Survey of Members of the European Society of Pediatric Endoscopic Surgeons (ESPES) |
| title_fullStr | Artificial Intelligence (AI) Competency and Educational Needs: Results of an AI Survey of Members of the European Society of Pediatric Endoscopic Surgeons (ESPES) |
| title_full_unstemmed | Artificial Intelligence (AI) Competency and Educational Needs: Results of an AI Survey of Members of the European Society of Pediatric Endoscopic Surgeons (ESPES) |
| title_short | Artificial Intelligence (AI) Competency and Educational Needs: Results of an AI Survey of Members of the European Society of Pediatric Endoscopic Surgeons (ESPES) |
| title_sort | artificial intelligence ai competency and educational needs results of an ai survey of members of the european society of pediatric endoscopic surgeons espes |
| topic | artificial intelligence machine learning image analysis surgical planning data bias pediatric surgery |
| url | https://www.mdpi.com/2227-9067/12/1/6 |
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