A homogeneous ensemble method for predicting gastric cancer based on gastroscopy reports

Abstract

Gastroscopy is important for finding suspicious stomach lesions, screening for gastric cancer, and providing early diagnoses. Due to the differences in the levels of diagnosis and treatment among gastroscope doctors, clinical diagnosis based on gastroscopy is limited by low diagnostic sensitivity and specificity to gastric cancer. An assistive system for gastroscopy report analysis can be helpful to improve the success rate of gastric cancer detection. In this study, a homogeneous ensemble decision support system for gastric cancer screening (Endo‐GCS) that performs word segmentation, feature extraction, and gastric cancer screening on text‐based gastroscopy reports is proposed. The proposed Endo‐GCS method establishes a progressive local weighting algorithm that improves the overall prediction performance of the homogeneous ensemble model in gastric cancer screening. An optimal threshold estimation algorithm is developed to minimize the negative impact of misdiagnosis and missed diagnoses. Through a comparative experimental study using real gastroscopy report data, the pathological examination conclusion is the gold standard. The sensitivity of the proposed Endo‐GCS method is 88.27%, the specificity is 77.84%, and the accuracy is 82.11%, which significantly improved the sensitivity 65.49% and the accuracy 80.5% of the gastroscopic diagnosis results, respectively.

Diagnostic value of MRI-DWI signal intensity value combined with serum PGI, PGII and CA199 in early gastric cancer

“…Most patients diagnosed progress to middle and late, and are prone to metastasis, increasing the risk of mortality (3)(4). At present, CT, gastroscopy is often used to diagnose gastric cancer, including CT examination (5) Gastroscope, as a gold standard, is widely used in the diagnosis of gastric mucosal lesions which is invasive and the patient acceptance is poor (6). Both people have limitations.…”