They used BP and learning vector quantization (LVQ) neural networks to build four diagnostic models; Cancer/Normal, M0/M1, carcinoembryonic antigen (CEA) testing (<5/≥5), and clinical staging (I–II/III–IV). The gene discussed is CEACAM5; the disease is cancer.