Do Treatment Choices by Artificial Intelligence Correspond to Reality? Retrospective Comparative Research with Necrotizing Enterocolitis as a Use Case.

IF 3.1 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES
Medical Decision Making Pub Date : 2025-05-01 Epub Date: 2025-03-12 DOI:10.1177/0272989X251324530
Rosa Verhoeven, Stella Mulia, Elisabeth M W Kooi, Jan B F Hulscher
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引用次数: 0

Abstract

BackgroundIn cases of surgical necrotizing enterocolitis (NEC), the choice between laparotomy (LAP) or comfort care (CC) presents a complex, ethical dilemma. A behavioral artificial intelligence technology (BAIT) decision aid was trained on expert knowledge, providing an output as "x percentage of experts advise laparotomy for this patient." This retrospective study aims to compare this output to clinical practice.DesignVariables required for the decision aid were collected of preterm patients with NEC for whom the decision of LAP or CC had been made. These data were used in 2 BAIT model versions: one center specific, built on the input of experts from the same center as the patients, and a nationwide version, incorporating the input of additional experts. The Mann-Whitney U test compared the model output for the 2 groups (LAP/CC). In addition, model output was classified as advice for LAP or CC, after which the chi-square test assessed correspondence with observed decisions.ResultsForty patients were included in the study (20 LAP). Model output (x percentage of experts advising LAP) was higher in the LAP group than in the CC group (median 95.1% v. 46.1% in the center-specific version and 97.3% v. 67.5% in the nationwide version, both P < 0.001). With an accuracy of 85.0% by the center-specific and 80.0% by the nationwide version, both showed significant correspondence with observed decisions (P < 0.001).LimitationsWe are merely examining a proof of concept of the decision aid using a small number of participants from 1 center.ConclusionsThis retrospective study demonstrates that treatment choices by artificial intelligence align with clinical practice in at least 80% of cases.ImplicationsFollowing prospective validation and ongoing refinements, the decision aid may offer valuable support to practitioners in future NEC cases.HighlightsThis study assesses the output of behavioral artificial intelligence technology in deciding between laparotomy and comfort care in surgical necrotizing enterocolitis.The model output aligns with clinical practice in at least 80% of patient cases.Following prospective validation, the decision aid may offer valuable support to physicians working at the neonatal intensive care unit.

人工智能的治疗选择是否符合现实?以坏死性小肠结肠炎为例的回顾性比较研究。
在手术坏死性小肠结肠炎(NEC)的病例中,选择剖腹手术(LAP)还是舒适护理(CC)是一个复杂的伦理困境。行为人工智能技术(BAIT)决策辅助系统接受了专家知识的培训,输出结果为“x百分比的专家建议该患者进行剖腹手术”。这项回顾性研究的目的是将这一结果与临床实践进行比较。辅助决策所需的设计变量收集已做出LAP或CC决定的NEC早产儿患者。这些数据被用于2个版本的BAIT模型:一个是特定于中心的,建立在与患者相同中心的专家的输入基础上,另一个是全国版本,纳入了其他专家的输入。Mann-Whitney U检验比较两组的模型输出(LAP/CC)。此外,模型输出被分类为LAP或CC的建议,之后卡方检验评估与观察到的决策的对应关系。结果共纳入40例患者(LAP 20例)。LAP组的模型输出(专家建议LAP的x百分比)高于CC组(中位数95.1% vs .中心特定版本46.1%,97.3% vs .全国版本67.5%,均为P P
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来源期刊
Medical Decision Making
Medical Decision Making 医学-卫生保健
CiteScore
6.50
自引率
5.60%
发文量
146
审稿时长
6-12 weeks
期刊介绍: Medical Decision Making offers rigorous and systematic approaches to decision making that are designed to improve the health and clinical care of individuals and to assist with health care policy development. Using the fundamentals of decision analysis and theory, economic evaluation, and evidence based quality assessment, Medical Decision Making presents both theoretical and practical statistical and modeling techniques and methods from a variety of disciplines.
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