ARTIFICIAL INTELLIGENCE IN GASTROINTESTINAL SURGERY

Artificial_Intelligence_in_Gastrointestinalkapak

ARTIFICIAL INTELLIGENCE (AI) IN STOMACH DISEASES

Özlem Zeliha Sert

Sultangazi Haseki Education and Research Hospital, Department of Gastrointestinal Surgery, İstanbul, Türkiye

Sert ÖZ. Artificial Intelligence (AI) in Stomach Diseases. Çaycı HM, ed. Artificial Intelligence (AI) in Gastrointestinal Surgery. 1st ed. Ankara: Türkiye Klinikleri; 2025. p.45-52.

ABSTRACT

Artificial intelligence (AI) is a general expression encompassing various techniques employed to address a specific issue through a computational approach that simulates human intelligence. Currently, the researches in various clinical areas have shown that image evaluation using AI can be employed to examine compositions and characteristics that are quite hard to recognize with the naked eye. The implementation of AI tools is considered as an innovative and encouraging strategy to enhance medical effectiveness in explanatory imaging, increase the clarity of outcomes, and aid determining for the identification and protection of diseases. Images from endoscopy is appropriate for deep-learning evaluation, which may transform how care is provided in stomach diseases. It is clear that AI will be crucial in distinguishing between non-malignant and malignant diseases of the stomach, also in the early diagnosis of stomach cancer. Although endoscopic techniques have a significant impact in the diagnosis of stomach diseases, it is often quite challenging to make a diagnosis. The AI-driven gastric cancer diagnostic system has shown a high degree of diagnostic precision and possesses the capability to distinguish non-neoplastic conditions, such as benign gastric ulcers and dysplasia. On the other hand, artificial intelligence has made significant advancements in determining the invasion degree of gastric cancer. This chapter aims to assess the fundamental components of various neural network architectures used for evaluating stomach disorders by analyzing the execution of distinct prototypes in crucial duties, like identifying or describing lesions (for example, distinguishing between benign and non-benign stomach lesions). To achieve this, we present a summary of current developments and upcoming possibilities in deep learning techniques utilized for examining endoscopic images of the stomach disease.

Keywords: Artificial intelligence; Gastric cancer; Deep learning; Endoscopy; Stomach disease

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