Potential applications of artificial intelligence for optimizing the treatment of patients with esophageal metaplasia and hiatal hernias

Background. Barrett’s esophagus is the only known histological precursor of esophageal adenocarcinoma. Combining mo­dern endoscopic treatment methods with the capabilities of artificial intelligence can significantly improve treatment outcomes, increase diagnostic accuracy, and enable a personalized approach to the management of Barrett’s esophagus. Objective: to improve methods for the diagnosis, monitoring, and treatment of Barrett’s esophagus through the application of artificial intelligence. Materials and me­thods. A prospective study was conducted involving 96 patients with Barrett’s esophagus combined with hiatal hernia, 52 males and 44 females. Their mean age was 54.4 ± 12.3 years. Particular attention was paid to clinical prediction in detecting dysplasia, as well as to the efficacy of endoscopic argon plasma coagulation (APC) for different types of Barrett’s esophagus, utilizing artificial intelligence. Results. Reflux esophagitis was diagnosed in 71.1 % of cases, most commonly LA grade A (30.9 %). Type I hiatal hernia was found in 45.8 % of patients, type III in 50 %, and type IV in 4.2 %. Morphological analysis revealed intestinal metaplasia with low-grade dysplasia in 45.26 % of cases, high-grade dysplasia in 4.21 %, and high-grade dysplasia combined with Abrikosov tumor in 1.05 %. Endoscopic treatment included conventional APC in 30 patients and hybrid APC in 65. Single-stage conventional APC was performed in 36.7 % of cases, while two-stage treatment was used in 63.3 %. Hybrid APC was applied in a single stage in 78.8 % of patients and in two stages in 21.2 %. Postoperative complications occurred less frequently after hybrid APC. Conclusions. Hybrid argon plasma coagulation, compared to conventional treatment methods, is the preferred option for endoscopic management of Barrett’s esophagus due to its high safety profile and effective eradication of metaplastic epithelium. The use of artificial intelligence enables the selection of individualized treatment strategies, which enhances clinical effectiveness, reduces complication rates, and optimizes the economic aspect of care.