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

Abstract

Background: In 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. Design: Variables 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. Results: Forty 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). Limitations: We are merely examining a proof of concept of the decision aid using a small number of participants from 1 center. Conclusions: This retrospective study demonstrates that treatment choices by artificial intelligence align with clinical practice in at least 80% of cases. Implications: Following prospective validation and ongoing refinements, the decision aid may offer valuable support to practitioners in future NEC cases. This 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.