An international consensus panel of 68 leading bariatric and metabolic surgery (BMS) from 35 countries has concluded that there are numerous potential roles of artificial intelligence (AI) in BMS however, certain concerns and ethical considerations must be addressed. The panel said AI could improve education and training, decision-making and planning, cost management and supportive systems, prediction of outcomes and patient follow-ups. Furthermore, advances in AI-driven robotics and AI-integrated genomic data applications have the potential to revolutionise the future of BMS.
An international consensus group was invited to participate in a modified Delphi process to build consensus. Of the 28 statements evaluated, a consensus of at least 70% was achieved for all, with 25 statements reaching consensus in the first round and the remaining three in the second round. Experts agreed that AI has the potential to enhance the evaluation of surgical skills in BMS by providing objective, detailed assessments, enabling personalised feedback, and accelerating the learning curve.
Most experts also recognized AI’s role in identifying qualified candidates for BMS referrals, helping patient and procedure selection, and addressing specific clinical questions.
However, concerns were raised about the potential overreliance on AI-generated recommendations. The consensus emphasized the need for ethical guidelines governing AI use and the inclusion of AI’s role in decision-making within the patient consent process. Furthermore, the results suggest that AI education should become an essential component of future surgical training. Advancements in AI-driven robotics and AI-integrated genomic applications were also identified as promising developments that could significantly shape the future of BMS.
Education and training
The experts achieved consensus that AI has the potential to provide a more objective and detailed evaluation of surgical skills in BMS, enabling personalized feedback and accelerating the learning curve for BMS procedures. It may enhance the quality of training, optimize faculty time, expand the educational capacity of institutions, and simplify bariatric surgical education while streamlining operative steps in BMS. Additionally, AI could play a significant role in improving patient education before BMS. However, patients should be thoroughly informed about how AI is utilised in their care and its impact on treatment modalities.
Decision making and planning
Most experts agreed that AI can assist in identifying qualified candidates for the referral process for BMS, as well as in both patient and surgical procedure selection, and can help answer certain clinical questions. However, there is a potential risk that healthcare providers may become overly reliant on AI recommendations.
Cost and supportive system
The experts reached a consensus on AI’s role in supporting systems by integrating it with Electronic Health Records to identify patterns in social determinants of health that impact BMS outcomes. This integration can help reduce healthcare costs related to BMS by optimising surgical processes and enhancing patient outcomes.
Prediction and follow-ups
The experts’ consensus indicated that AI can aid in predicting weight loss outcomes, post-BMS complications, readmission rates, and remission or relapse of obesity-related medical conditions following MBS. Additionally, AI-powered wearable devices can support postoperative monitoring.
Ethical issues
Most experts agree that AI use should adhere to ethical guidelines and that its role in decision-making should be included in the patient consent process.
AI systems must ensure that personal data is processed lawfully, and individuals must be informed about how their data is used. This aligns with ethical guidelines that prioritize patient autonomy and privacy. In addition, General Data Protection Regulation (GDPR) imposes strict requirements on AI systems, particularly in healthcare. For example, AI algorithms must be explainable, and decisions made by AI must be subject to human oversight. This ensures that AI systems do not operate as “black boxes” and that patients retain control over their data. Compliance with GDPR also requires that AI systems are designed with privacy-by-design principles, minimising data collection and ensuring data security.
The findings were featured in the paper, ‘International expert consensus on the current status and future prospects of artificial intelligence in metabolic and bariatric surgery’, published in Scientific Reports.
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