AI-Driven Smart Device for Non-Invasive Detection of Peptic Ulcers for Sustainable Healthcare

Peptic ulcer disease (PUD) is a widespread issue globally, including in Bangladesh. It is largely caused by Helicobacter pylori (H. pylori) bacteria. H. pylori infects the human digestive tract and is a leading reason of gastric inflammation, peptic ulcers, and gastric cancer. Ritual diagnostic methods, though beneficial, often involve invasive procedures that cause patient discomfort. Recent Artificial Intelligence (AI) advancements have opened doorways for noninvasive diagnosis. This study proposed a device that gathers biomarker information through multiple sensors. The biomarker information was used to develop a supervised machine-learning model based on a dataset of 1190 samples. The machine learning model reached a precision of 96 percent on the train and test dataset. A survey of 100 randomly selected individuals revealed that 68 percent believe AI could improve diagnostic accuracy in a non-invasive manner, thereby reducing patient discomfort. This research introduces a novel method for the non-invasive diagnosis of PUD for sustainable healthcare.