Use of artificial intelligence in paediatric anaesthesia: a systematic review

Antel, Ryan; Sahlas, Ella; Gore, Geneviève; Ingelmo, Pablo

doi:10.1016/j.bjao.2023.100125

Cited by 5 publications

(6 citation statements)

References 69 publications

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“…Risk prediction tools are helpful to physicians as they can not only streamline patient evaluation but also increase accuracy of prognostic assessment and ensure adequate subsequent care [9]. Applications using AI in pediatric perioperative care may help identify risk factors of perioperative adverse events, prioritize care, and ultimately reduce patient morbidity and mortality [2 ▪ ] (Table 1).…”

Section: Risk Prediction In Pediatric Perioperative Carementioning

confidence: 99%

“…It involves studying algorithms that provide machines with the capability to reason and carry out tasks like problem-solving and decision-making. In practical terms, AI involves developing computer systems that can emulate intelligent behaviors such as learning, reasoning, and solving problems [2 ▪ ].…”

Section: Introductionmentioning

confidence: 99%

“…Nevertheless, its utilization in pediatric anesthesia has not progressed as much. Antel et al [2 ▪ ] recently described seven themes of AI application in pediatric anesthesiology: anesthetic depth estimation, risk factor prediction, physiological parameter monitoring, airway device selection, intubation aid, anesthetic decision guidance, and operating room scheduling.…”

Section: Introductionmentioning

confidence: 99%

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Advances in pediatric perioperative care using artificial intelligence

Dundaru-Bandi,

Antel,

Ingelmo

2024

Current Opinion in Anaesthesiology

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Purpose of this review This article explores how artificial intelligence (AI) can be used to evaluate risks in pediatric perioperative care. It will also describe potential future applications of AI, such as models for airway device selection, controlling anesthetic depth and nociception during surgery, and contributing to the training of pediatric anesthesia providers. Recent findings The use of AI in healthcare has increased in recent years, largely due to the accessibility of large datasets, such as those gathered from electronic health records. Although there has been less focus on pediatric anesthesia compared to adult anesthesia, research is on- going, especially for applications focused on risk factor identification for adverse perioperative events. Despite these advances, the lack of formal external validation or feasibility testing results in uncertainty surrounding the clinical applicability of these tools. Summary The goal of using AI in pediatric anesthesia is to assist clinicians in providing safe and efficient care. Given that children are a vulnerable population, it is crucial to ensure that both clinicians and families have confidence in the clinical tools used to inform medical decision- making. While not yet a reality, the eventual incorporation of AI-based tools holds great potential to contribute to the safe and efficient care of our patients.

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Section: Risk Prediction In Pediatric Perioperative Carementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Advances in pediatric perioperative care using artificial intelligence

Dundaru-Bandi,

Antel,

Ingelmo

2024

Current Opinion in Anaesthesiology

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“…AI can be integrated in pain management protocols, drug delivery systems, and in critical care monitoring [9]. In addition, there is emerging literature that encourages the application of AI among special patients' groups, such as in pediatric anesthesia, which holds potential for ultimately improving patient safety and outcomes [10].…”

Section: Introductionmentioning

confidence: 99%

Attitudes of Jordanian Anesthesiologists and Anesthesia Residents towards Artificial Intelligence: A Cross-Sectional Study

Bsisu,

Alqassieh,

Aloweidi

et al. 2024

JPM

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Success in integrating artificial intelligence (AI) in anesthesia depends on collaboration with anesthesiologists, respecting their expertise, and understanding their opinions. The aim of this study was to illustrate the confidence in AI integration in perioperative anesthetic care among Jordanian anesthesiologists and anesthesia residents working at tertiary teaching hospitals. This cross-sectional study was conducted via self-administered online questionnaire and includes 118 responses from 44 anesthesiologists and 74 anesthesia residents. We used a five-point Likert scale to investigate the confidence in AI’s role in different aspects of the perioperative period. A significant difference was found between anesthesiologists and anesthesia residents in confidence in the role of AI in operating room logistics and management, with an average score of 3.6 ± 1.3 among residents compared to 2.9 ± 1.4 among specialists (p = 0.012). The role of AI in event prediction under anesthesia scored 3.5 ± 1.4 among residents compared to 2.9 ± 1.4 among specialists (p = 0.032) and the role of AI in decision-making in anesthetic complications 3.3 ± 1.4 among residents and 2.8 ± 1.4 among specialists (p = 0.034). Also, 65 (55.1%) were concerned that the integration of AI will lead to less human–human interaction, while 81 (68.6%) believed that AI-based technology will lead to more adherence to guidelines. In conclusion, AI has the potential to be a revolutionary tool in anesthesia, and hesitancy towards increased dependency on this technology is decreasing with newer generations of practitioners.

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“…These can help optimize patient care and improve safety by recognizing inefficient and potentially dangerous patterns, especially in electronic medical record platforms. (2)(3)(4)(5) Artificial intellegence also assists in risk assessment, risk mitigation planning, and patient communication. According to some assessments even outperforming physicians in empathy and effectiveness.…”

mentioning

confidence: 99%

Artificial Intelligence (AI) in Perioperative Medicine

Brannigan

2023

Wits Journal of Clinical Medicine

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Use of artificial intelligence in paediatric anaesthesia: a systematic review

Cited by 5 publications

References 69 publications

Advances in pediatric perioperative care using artificial intelligence

Advances in pediatric perioperative care using artificial intelligence

Attitudes of Jordanian Anesthesiologists and Anesthesia Residents towards Artificial Intelligence: A Cross-Sectional Study

Artificial Intelligence (AI) in Perioperative Medicine

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