To improve the accuracy of risk prediction, screening and treatment outcome of cancer, we aim to establish a medical database that includes standardized and structured clinical diagnosis and treatment information, image features, pathological features, and multi-omics information and to develop a multi-modal data fusion-based technology system using artificial intelligence technology based on database.
Participants with the suspected of lung cancer/node, or stomach cancer/lesion, or colorectal cancer/leision
Participants that have signed informed consent.
Participants with detailed electronic medical records, image records, pathological records, multi-omics information, and other important clinical diagnostic information.
Healthy participants with no clinical diagnosis of lung cancer/node, or stomach cancer/lesion, or colorectal cancer/leision.
Participants with primary clinical and pathological data missing.
Participants lost to follow-up.
Participants with too poor medical image quality to perform segment and mark ROI accurately