Research into the potential benefits of artificial intelligence for comprehending the intricate
biology of cancer has grown as a result of the widespread use of deep learning and …

Gastric cancer is a leading contributor to cancer incidence and mortality globally. Recently,
artificial intelligence approaches, particularly machine learning and deep learning, are …

Upper gastrointestinal cancers, mainly comprising esophageal and gastric cancers, are
among the most prevalent cancers worldwide. There are many new cases of upper …

Accurate survival prediction is crucial for doctors to choose appropriate treatment options
and make prognoses for gastric cancer patients. While machine learning algorithms have …

Relying solely on a single medical data for cancer diagnosis may increase the risk of
misdiagnosis and missed diagnosis. Multi-modal data provides comprehensive information …

Background The potential of the application of artificial intelligence and biochemical markers
of oxidative stress to predict the prognosis of older patients with gastric cancer (GC) remains …

Several authors have shown that hematological parameters can be used to detect poor
prognosis in patients with cancer. Thus, such features could be used in artificial intelligence …

Background Oxidative stress process plays a key role in aging and cancer; however,
currently, there is paucity of machine-learning model studies investigating the relationship …

Background: Hebei Province is a high-risk area for gastric cancer in China, and there is
currently no survival prediction model for gastric cancer patients in Hebei Province. This …

Background Paclitaxel is commonly used as a second-line therapy for advanced gastric
cancer (AGC). The decision to proceed with second-line chemotherapy and select an …