Raman spectroscopy and machine learning for early detection of gastric cancer and Helicobacter pylori with gastric juice.

ABSTRACT: Gastric cancer is a leading cause of cancer-related mortality and highlights the need for early detection of gastric cancer and Helicobacter pylori (HP) infection, which is a major risk factor. Early non-invasive and convenient diagnostic tools capable of capturing the dynamic molecular alterations during carcinogenesis and HP infection is needed. In this study, we use Raman spectroscopy and machine learning algorithms to detect different gastric lesions and HP infection condition with gastric juice samples. 133 patients from Peking University Third Hospital were involved and categorized into groups based on histopathological diagnosis: early gastric cancer (EGC), dysplasia (DYS), intestinal metaplasia (IM), and chronic superficial gastritis (CSG), with further classification based on HP i

SUBMITTER: Fu W 

PROVIDER: S-EPMC12534471 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature