Artificial Intelligence Use in Daily and Professional Life among Pediatric Surgeons in India: A Roadmap for Adoption Based on Online Survey Results

ABSTRACT

Background:

Artificial intelligence (AI) is transforming the various domains of medicine, including pediatric surgery, where precision and timely decision-making are critical. However, the real-world integration of AI in pediatric surgery, particularly in low- and middle-income countries such as India, remains underexplored. We propose a roadmap for the adoption of AI based on our survey results for Indian Association of Pediatric Surgeons (IAPS).

Objective:

This survey aimed to evaluate the awareness, utilization, and perspectives of pediatric surgeons in India regarding AI in both professional and personal settings, as well as to identify barriers and opportunities for its integration into clinical practice.

Methodology:

A cross-sectional survey was conducted among the members of the IAPS, utilizing a structured online questionnaire. Quantitative data were analyzed using the descriptive statistics and Chi-square tests, whereas qualitative responses were thematically analyzed.

Results:

A total of 74 pediatric surgeons participated in the survey. While 60.8% were somewhat familiar with AI, only 47.3% used AI in their clinical practice, primarily for diagnostic imaging (31.1%) and administrative tasks (23%). Perceived benefits included enhanced diagnostic accuracy (45.9%) and improved surgical care (37.8%), yet barriers such as data privacy (39.2%) and concerns over reliability (51.4%) were prevalent. Personal AI adoption was high (70.3%), with virtual assistants and health-tracking apps being most common. Additionally, 86.4% of respondents anticipated AI becoming integral to pediatric surgery within the next decade.

Conclusion:

Despite limited clinical adoption, there is strong interest among pediatric surgeons in India for AI-focused training and integration. Addressing barriers such as ethical concerns, data privacy, and cost could catalyze AI’s potential to revolutionize pediatric surgical care. Our roadmap addressing these challenges through targeted education, ethical guidelines, and better integration strategies will be essential for harnessing AI’s full potential in pediatric surgery.

INTRODUCTION

Artificial intelligence (AI) has emerged as a powerful tool across the various fields of medicine, including pediatric surgery. With its ability to process large datasets, identify patterns, and provide predictive insights, AI holds transformative potential in diagnostics, decision-making, and surgical planning.[1] In pediatric surgery, where patient outcomes depend on precise and timely interventions, AI applications such as computer vision and machine learning have demonstrated utility in improving surgical accuracy and reducing complications.[2]

Globally, the integration of AI in pediatric surgical care remains in its infancy, with limited studies exploring its real-world application, especially in low- and middle-income countries (LMICs) like India. This survey aims to bridge this gap by evaluating the awareness, utilization, and perception of AI among pediatric surgeons in India. It also examines the challenges and ethical considerations surrounding AI’s integration into clinical workflows. This survey will help us at organizational and institutional levels to explore the interventions necessary to train pediatric surgeons about AI and adopt AI tools in surgical teaching, training, patient management, social outreach, and research. We propose a roadmap for the adoption of AI based on our survey results for the Indian Association of Pediatric Surgeons (IAPS).

METHODOLOGY

This cross-sectional study was conducted to assess the awareness, usage, and perspectives on AI among pediatric surgeons in India. An online questionnaire was designed and distributed to capture the data on the key aspects of AI integration into both professional and personal practices.

Survey design

The survey included the several key domains to explore the awareness, familiarity, and perspectives of pediatric surgeons regarding AI. Demographic information such as age group, gender, years of clinical experience, type of practice (public sector, private sector, academic institution, or others), and primary area of specialization within pediatric surgery were collected using a structured Google form [Supplementary Material]. Participants’ awareness and familiarity with AI in healthcare were assessed, including their self-assessed knowledge level on a predefined scale and sources of information about AI, such as professional training, online resources, or peer discussions. The survey further investigated the current professional applications of AI, such as its use in diagnostic imaging (e.g., AI-assisted radiology), surgical planning and simulation, patient monitoring, follow-up care, and research tasks like literature review and data analysis. Participants provided insights into the perceived benefits of AI, including enhanced diagnostic accuracy, improved surgical outcomes, increased efficiency, and educational advancements, along with challenges like high costs, ethical concerns, lack of training, and limited access to resources. The survey also delved into AI utilization in personal life, such as virtual assistants, recommendation systems, and home automation, and its perceived impact on both day-to-day tasks and professional workflows. Finally, the survey sought participants’ perspectives on the anticipated role of AI in pediatric surgery over the next 5–10 years, highlighting areas where AI could provide significant benefits, such as remote surgery, education, and patient care, while addressing the concerns about over-reliance on AI, ethical dilemmas, and its potential impact on clinical decision-making and surgeon autonomy. The survey included multiple-choice questions, Likert-scale items (e.g., ranging from strongly disagree to strongly agree), and open-ended prompts to capture nuanced opinions.

Distribution and data collection

The survey link was distributed through WhatsApp groups to the members of the IAPS. Participation was voluntary, and no incentives were provided. All responses were anonymized to ensure confidentiality. A total of 74 pediatric surgeons completed the survey during the data collection period.

Data analysis

Quantitative data were analyzed using the descriptive statistics to summarize demographic profiles, AI utilization rates, and trends in perceived benefits and challenges. Results were expressed as frequencies, percentages, and graphical representations. Associations between variables, such as experience level and AI adoption, were evaluated using the Chi-square tests.

Qualitative responses from the open-ended questions were thematically analyzed to identify recurring insights and opinions, providing a richer understanding of surgeon perspectives on AI integration in both clinical practice and personal life.

RESULTS

The survey analyzing AI use among pediatric surgeons gathered responses from 74 participants, revealing diverse insights. Demographics showed a broad age distribution, with 28.4% under 40 years, 35.1% aged 40–49 years, and 27% aged 50–59 years [Figure 1a]. Over half (51.4%) specialized in General Pediatric Surgery, followed by 21.6% in Pediatric Urology [Figure 1b], and 50% practiced in academic hospitals, with 29.7% working in private hospitals [Figure 1c]. Professional experience ranged widely, with 31.1% having 11–20 years of practice, while 29.7% reported more than 20 years of experience [Figure 1d].

Figure 1.

Demographics (a) age distribution (b) area of specialisation (c) practice setting (d) experience as pediatric surgeon

Regarding familiarity and attitude toward AI, 60.8% were somewhat familiar with AI, and 12.2% reported high familiarity [Figure 2a]. Attitudes were predominantly positive, with 41.9% being very positive and 37.8% somewhat positive, while only 4.1% expressed a somewhat negative view [Figure 2b]. Nearly half (45.9%) believed AI somewhat enhanced pediatric surgical care, and 37.8% perceived significant enhancements [Figure 2c].

Figure 2.

Familiarity and attitudes towards artificial intelligence (a) familiarity (b) attitudes (c) perceived benefits. AI: Artificial intelligence

In clinical practice, 52.7% of respondents reported not utilizing AI, but among users, AI was applied primarily for diagnostic imaging (31.1%), administrative tasks (23%), and surgical planning (12.2%). Daily use was reported by 18.9%, weekly by 16.2%, and 33.8% indicated no use [Figure 3a].

Figure 3.

Artificial intelligence usage in clinical practice (a) frequency of current use (b) diagnostic accuracy (c) improvement in patient outcomes. AI: Artificial intelligence

For effectiveness and impact, AI was deemed highly effective for diagnostic support by 9.5% and moderately effective by 27% [Figure 3b]. Moderate improvements in patient outcomes were noted by 27%, although 44.6% observed no significant impact [Figure 3c].

AI’s use in research was prominent, with applications in writing support (54.1%), literature reviews (43.2%), reference management (29.7%), and data analysis (28.4%) [Figure 4a]. Monthly use was the most common (20.3%), and 40.5% reported moderate improvements in research quality [Figure 4b and c].

Figure 4.

Artificial intelligence usage for research related tasks (a) applications (b) frequency (c) impact (d) comfort. AI: Artificial intelligence

Regarding comfort and concerns, 48.7% were comfortable using AI for data analysis and writing, while accuracy, ethical issues, over-reliance on technology, and data privacy were major concerns [Figures 4d and 5a]. In personal life, 70.3% adopted AI tools like virtual assistants (58.1%) and health tracking apps (54.1%), but 58.1% expressed discomfort about data privacy.

Figure 5.

(a) Concerns about using artificial intelligence (AI) in pediatric surgery (b) role replacement by AI (c) AI integration into pediatric surgical practice (d) interest in receiving further AI training. AI: Artificial intelligence

Looking ahead, 62.2% anticipated AI replacing specific tasks in pediatric surgery to a limited extent [Figure 5b], and 86.4% believed it would become integral in the next decade [Figure 5c]. Training interest was strong, with 75.7% favoring AI-focused education [Figure 5d]. Preferred learning resources included online courses (73%), workshops (66.2%), and conferences (44.6%). These findings underscore the evolving role of AI in pediatric surgery, its current limitations, and the need for targeted training to optimize its potential.

DISCUSSION

The integration of AI in pediatric surgery holds immense potential for transforming clinical practices, particularly in improving diagnostic accuracy, optimizing surgical planning, and enhancing patient outcomes. Studies indicate that neural networks and ensemble models are highly effective in predicting the surgical outcomes and adverse events, often achieving accuracy levels comparable to clinical experts.[2] This survey sought to explore the awareness, attitudes, and current usage of AI among pediatric surgeons in India. The findings reveal a cautious but optimistic outlook toward AI, highlighting its potential to enhance both clinical and research practices in pediatric surgery, while also addressing several challenges.

A significant portion of respondents (60.8%) reported being somewhat familiar with AI, with 12.2% claiming high familiarity. This indicates a growing awareness of AI’s potential, though familiarity is still emerging. Similar findings were reported in other studies, where familiarity with AI among healthcare professionals was positively associated with a willingness to adopt new technologies.[3] Furthermore, the predominance of positive attitudes toward AI (79.7%) suggests a readiness to integrate AI into clinical workflows. This optimism is consistent with research that highlights the promise of AI to revolutionize healthcare, particularly in diagnostic imaging and predictive analytics.[4]

Despite the high awareness, only 47.3% of respondents currently use AI in their clinical practices. The most common applications reported were diagnostic imaging (31.1%) and administrative tasks (23%). Global trends of AI adoption in surgery also indicate that early applications have focused on diagnostics and decision support rather than autonomous tasks.[3] Diagnostic support tools, such as AI-assisted radiology, have demonstrated substantial promise in reducing diagnostic errors and enhancing image interpretation.[5] However, the limited use of AI in surgical planning and patient monitoring highlights the need for further development and access to these tools in the clinical settings.

The frequency of AI use was also revealing. While 33.8% of respondents reported never using AI in clinical practice, those who did use AI predominantly did so on a daily or weekly basis. This suggests that for those already using AI, it is becoming an integral part of their workflow, but broader adoption may be hindered by factors such as cost, technical challenges, and the need for additional training. Furthermore, the lack of AI adoption in clinical practice could be attributed to challenges in integrating AI into existing medical systems, particularly in resource-constrained settings such as India. Furthermore, external validation remains a critical hurdle. In a systematic review, Elahmedi et al. found that only a small proportion of AI models for pediatric surgery had undergone rigorous validation, limiting their real-world applicability.[2]

The perception of AI’s effectiveness in improving diagnostic accuracy and patient outcomes was mixed. While 35.1% respondents believed AI had a significant impact on patient outcomes, the majority (44.6%) reported no discernible effect. These results are consistent with studies in other medical fields, where AI tools have been shown to improve diagnostic accuracy but have yet to demonstrate consistent, measurable impacts on patient outcomes across all the clinical scenarios.[6] This discrepancy may be due to variability in AI tool performance across different specialties or the lack of comprehensive long-term data on AI’s clinical outcomes.

In the research context, AI is more widely adopted, with 54.1% of respondents using AI for writing support and 43.2% for literature reviews. This aligns with the growing use of AI in academic medicine, particularly for tasks such as data analysis and systematic reviews.[7] AI tools have been shown to significantly expedite the research process, with AI-driven algorithms aiding in the analysis of large datasets, identifying research trends, and even generating literature reviews.[8] However, concerns about AI’s reliability (48.6%) and its potential to undermine academic integrity were prevalent, underscoring the need for standardized protocols and ethical guidelines for AI use in research.

Ethical concerns related to AI usage were a major theme in this study. Over half of the respondents (51.4%) expressed concerns about AI’s accuracy and reliability, while 39.2% were worried about data privacy. These results are similar to a survey among German surgeons which revealed that most surgeons are optimistic about AI’s potential, but challenges like ethical concerns, medico-legal liabilities, and data security remain prevalent.[3] These concerns mirror global discussions on the ethical implications of AI in healthcare, including issues such as algorithmic bias, transparency, and accountability.[9] The risk of over-reliance on AI was another significant concern (45.9%), reflecting fears that AI could diminish the clinical decision-making capacity of surgeons and lead to the erosion of essential skills over time. These concerns emphasize the importance of developing AI systems that are transparent, explainable, and aligned with ethical healthcare practices.

Interestingly, the majority of respondents (70.3%) reported using AI technologies in their personal lives, with virtual assistants and health-tracking apps being the most common applications. This contrasts with their more cautious approach to using AI in professional settings, which may reflect the difference in perceived risk and the regulated environment of healthcare. Personal use of AI technologies has been shown to foster greater comfort with AI, which could help facilitate its adoption in professional contexts.[10] However, concerns over data privacy (58.1% discomfort) in personal use further underscore the need for robust data protection measures in both clinical and personal AI applications.

This study has several limitations, including a relatively small sample size and the potential for selection and nonresponder’s bias, as respondents were self-selected from a specific professional group (IAPS members). As the response rate is unknown, the survey is not an absolute representation of the population of Pediatric Surgeon in India. Moreover, in the present survey, the respondents have not been evaluated based on their city of working (Tier 1–3) which could identify the beneficiaries for more targeted approach in creating awareness about use of AI. Future research should aim to include a more diverse sample of pediatric surgeons from the different regions of India and other LMICs to provide a more comprehensive understanding of AI’s impact globally. Additionally, longitudinal studies assessing the actual clinical outcomes and the long-term effects of AI on surgical practice will be essential for evaluating the full potential of AI in pediatric surgery.

Looking to the future, the survey respondents expressed significant interest in further training on AI technologies, with 75.7% indicating a desire for AI-focused education. This is critical, as training and continuous professional development have been identified as key factors in the successful adoption of new technologies in healthcare.[11] Additionally, 62.2% believed AI could replace certain tasks in pediatric surgery, while 86.4% anticipated its increasing integration into pediatric surgical practices over the next decade. This highlights recognition of AI’s potential to enhance surgical practices, particularly in areas such as autonomous surgical systems, improved robotic assistance, and telemedicine integration for delivering remote surgical expertise.[12]

Based on the survey results, the IAPS propose the following road map to familiarize the pediatric surgeons with AI and adopt AI tools in Pediatric Surgery [Figure 6]. The application of AI in Pediatric Surgery in various fields is depicted in Table 1, allowing wide exploration of the subject and its applicability.[2,13] The above roadmap shall provide an opportunity to explore the ability of the AI in favourably affecting our clinical, academic, research, healthcare and organizational efficiency.

Figure 6.

Indian association of pediatric surgeons’ roadmap for adoption of artificial intelligence for the benefit of clinicians, patients, students and researchers. AI: Artificial intelligence

Table 1.

Possible areas of exploration in pediatric surgery for development of artificial intelligence-driven models in patient care

Application	Description	Example
Decision support and operative planning	Using ML algorithms to predict outcomes and assist in surgical decision-making	Identifying which patients with biliary atresia would benefit from Kasai portoenterostomy versus those requiring liver transplantation
	ML models supporting pathway decisions in VUR management	Classifying risk to help surgeons decide if a patient is a candidate for surgery, antibiotic prophylaxis, or conservative management
	ML models to predict postoperative risks and complications	Predicting the likelihood of surgical site infections after neonatal surgeries
Computer vision and radiomics	AI-powered imaging analysis for diagnostic and planning purposes	Identifying the fistula site and level of malformation in anorectal malformations, guiding the surgical approach using radiographs and dye studies
	Radiomic analysis for classification and staging of tumors	Classifying Wilms tumors, assessing preoperative staging by identifying vessel invasion and metastatic spread on CT scans
Intraoperative structure assessment and measurements	AI-driven tools to measure structures and identify critical anatomy during surgery	Measuring Roux loop length during hepatico-jejunostomy or adolescent bariatric surgeries
	Identifying critical structures intraoperatively helping inexperienced surgeons bridge the skill gap	Ensuring the safety of structures like the vas deferens in laparoscopic inguinal surgeries
	Identifying critical structures in complex neonatal surgeries	Identifying esophagus, aorta, and trachea during esophageal atresia repair
Surgical simulation	Virtual learning environments powered by AI for practicing procedures	Simulating complex surgeries like craniofacial reconstruction or pediatric tumor resections
Real-time instrument tracking and educational tools	Monitoring surgical instrument maneuvers during minimally invasive surgery	Provide objective feedback on minimal access surgery skill levels, ambidexterity and tremors
	AI-based platforms for training and identifying learning curve of surgeons	Virtual reality systems for practicing laparoscopic surgery techniques with real-time feedback on performance
Augmented reality in surgery	Real-time overlays of anatomical landmarks using AI and imaging	Guiding pediatric surgeons during liver resection or correcting scoliosis
Personalized recovery plans	AI-generated tailored postsurgical care regimens/ERAS protocols	Optimizing recovery timelines and reducing hospital stay duration for gastroschisis repair
Genomic analysis integration	Using AI to interpret genetic data for syndromes and tumor profiling	Identifying genetic markers in pediatric oncology cases like neuroblastoma

VUR: Vesicoureteral reflux, AI: Artificial intelligence, ML: Machine learning, CT: Computed tomography, ERAS: Enhanced recovery after surgery

“AI is a misnomer; it should be called Augmenting Intelligence” which reflects the paradigm shift in understanding AI’s role in enhancing (“Re-Placing” rather than replacing), human capabilities.[14] The foundation of artificial or augmenting intelligence is indeed the aggregation and processing of massive datasets. However, biases inherent in the data or the algorithms can lead to unintended consequences. While the integration of AI is not without challenges, including ethical concerns and potential misuse, history demonstrates humanity’s capacity to adopt emerging technologies responsibly to advance societal welfare.

CONCLUSION

The findings from this survey suggest that while AI adoption in pediatric surgery in India remains in its early stages, there is significant interest in its potential to improve diagnostic accuracy, enhance surgical planning, and transform patient care. However, concerns about data privacy, AI’s reliability, and the need for appropriate training remain significant barriers. Our roadmap addressing these challenges through targeted education, ethical guidelines, and better integration strategies will be essential for harnessing AI’s full potential in pediatric surgery.

Conflicts of interest

There are no conflicts of interest.

SUPPLEMENTARY MATERIAL

Survey questionnaire on artificial intelligence use in daily and professional life among pediatric surgeons

Purpose: This survey aims to understand the attitudes and experiences of Pediatric Surgeons regarding the use of Artificial Intelligence (AI) in their professional and personal lives, including clinical practice, research activities, and daily life. Your responses are anonymous and will be used solely for research purposes.

SECTION 1: DEMOGRAPHIC INFORMATION

• 1. What is your age?

  • Under 30
  • 30-39
  • 40-49
  • 50-59
  • 60 and above

• 2. What is your primary area of specialization within Pediatric Surgery?

  • General Pediatric Surgery
  • Pediatric Urology
  • Pediatric GI and HB Surgery
  • Pediatric Thoracic Surgery
  • Pediatric Oncosurgery
  • In Training
  • Other (please specify): _

• 3. What is your current practice setting?

  • Academic Hospital
  • Private Hospital
  • Private Practice
  • Public Hospital
  • Other (please specify): _

• 4. How many years have you been practicing as a Pediatric Surgeon?

  • Less than 5 years
  • 5-10 years
  • 11-20 years
  • More than 20 years

SECTION 2: GENERAL ATTITUDES TOWARD AI

• 5. How familiar are you with AI?

  • Very familiar
  • Somewhat familiar
  • Neutral
  • Somewhat unfamiliar
  • Very unfamiliar

• 6. What is your general attitude toward AI in healthcare?

  • Very positive
  • Somewhat positive
  • Neutral
  • Somewhat negative
  • Very negative

• 7. To what extent do you believe AI can enhance the quality of pediatric surgical care?

  • Greatly enhances
  • Somewhat enhances
  • Neutral
  • Somewhat detracts
  • Greatly detracts

SECTION 3: PROFESSIONAL USE OF AI IN CLINICAL PRACTICE

• 8. In which of the following areas do you currently use AI in your clinical practice? (Select all that apply)

  • Diagnostic Imaging (e.g., radiology, MRI, CT scans)
  • Surgical Planning
  • Patient Monitoring
  • Clinical Decision Support Systems
  • Administrative Tasks (e.g., scheduling, billing)
  • I do not use AI in clinical practice
  • Other (please specify): _

• 9. How often do you use AI tools in your clinical practice?

  • Daily
  • Weekly
  • Monthly
  • Rarely
  • Never

• 10. How effective do you find AI in assisting with diagnostic accuracy?

  • Very effective
  • Somewhat effective
  • Neutral
  • Somewhat ineffective
  • Very ineffective

• 11. Do you feel that AI has improved patient outcomes in your practice?

  • Yes, significantly
  • Yes, somewhat
  • No change
  • No, it has negatively impacted
  • Not applicable

SECTION 4: PROFESSIONAL USE OF AI IN RESEARCH AND ACADEMIC WORK

• 12. Do you use AI tools or applications for research-related tasks? (Select all that apply)

  • Data Analysis and Interpretation
  • Literature Review
  • Writing Assistance (e.g., grammar checks, generating drafts)
  • Reference Management
  • Statistical Modelling
  • I do not use AI for research-related tasks
  • Other (please specify): _

• 13. How often do you use AI tools for research-related tasks?

  • Daily
  • Weekly
  • Monthly
  • Rarely
  • Never

• 14. Have AI tools positively impacted the quality or efficiency of your research activities?

  • Yes, significantly
  • Yes, to some extent
  • No change
  • No, they have negatively impacted
  • Not applicable

• 15. Which AI-based tools or software have you used for paper writing and publication tasks? (Select all that apply)

  • Grammar and Style Checkers (e.g., Grammarly)
  • AI-assisted Writing Platforms (e.g., ChatGPT)
  • Plagiarism Detection Tools
  • Reference Management Software with AI (e.g., EndNote, Mendeley)
  • AI-driven Journal Recommendation Tools
  • I do not use AI tools for paper writing and publication tasks
  • Other (please specify): _

• 16. How useful do you find AI tools for enhancing your academic writing and research publications?

  • Very useful
  • Somewhat useful
  • Neutral
  • Somewhat unuseful
  • Not useful at all

• 17. Do you feel comfortable relying on AI for tasks such as data analysis or research writing in Pediatric Surgery?

  • Very comfortable
  • Somewhat comfortable
  • Neutral
  • Somewhat uncomfortable
  • Very uncomfortable

• 18. What are your primary concerns about using AI in research and academic work? (Select all that apply)

  • Data Privacy and Security
  • Accuracy and Reliability of AI-generated Outputs
  • Ethical Concerns (e.g., plagiarism, originality)
  • Over-reliance on Technology
  • Lack of Control over AI Processes
  • Other (please specify): _

SECTION 5: PERSONAL USE OF AI

• 19. Do you use AI-powered applications in your personal life (e.g., virtual assistants, smart home devices, etc.)?

  • Yes
  • No

• 20. If yes, which of the following AI applications do you use in your personal life? (Select all that apply)

  • Virtual Assistants (e.g., Siri, Alexa)
  • Health Tracking Apps (e.g., fitness trackers, sleep monitors)
  • Smart Home Devices (e.g., thermostats, lighting)
  • AI-based Recommendations (e.g., streaming services, online shopping)
  • Other (please specify): ________

• 21. How comfortable are you with AI having access to your personal data?

  • Very comfortable
  • Somewhat comfortable
  • Neutral
  • Somewhat uncomfortable
  • Very uncomfortable

SECTION 6: CHALLENGES AND CONCERNS

• 22. What are your primary concerns about using AI in pediatric surgery? (Select all that apply)

  • Data Privacy and Security
  • Reliability and Accuracy
  • Lack of Personal Interaction with Patients
  • Cost and Accessibility
  • Ethical Considerations
  • Other (please specify): _

• 23. Do you believe AI could potentially replace certain aspects of your role as a Pediatric Surgeon?

  • Yes, to a large extent
  • Yes, to a limited extent
  • No, not at all

SECTION 7: FUTURE OUTLOOK AND TRAINING

• 24. Do you believe AI will become more integrated into pediatric surgical practices over the next decade?

  • Definitely
  • Probably
  • Neutral
  • Probably not
  • Definitely not

• 25. Are you interested in receiving further training or education on AI technologies relevant to your practice?

  • Yes, definitely
  • Yes, to some extent
  • No, not really
  • No, not at all

• 26. What resources would you find helpful for learning more about AI in healthcare? (Select all that apply)

  • Workshops or Seminars
  • Online Courses
  • Professional Conferences
  • Reading Materials (e.g., journals, books)
  • Other (please specify): _

SECTION 8: OPEN-ENDED QUESTIONS

• 27. In your opinion, what is the most significant benefit of AI in pediatric surgery?

• 28. What is your greatest concern about the increasing use of AI in healthcare?

• 29. Are there any specific areas in pediatric surgery where you would like to see more AI development or support?

Funding Statement

Nil.