Esophageal adenocarcinoma (EAC) is a highly lethal cancer, with a five-year survival rate of less than 20 percent. Although a precursor lesion to EAC, called Barrett’s esophagus (BE), is present in roughly seven percent of middle-aged adults, less than one percent of BE patients will progress to EAC, making it difficult to determine which individuals are at risk of developing this deadly cancer.
Combining machine learning with statistical methods can provide accurate models for disease risk prediction
Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding