Diagnosis of ovarian cancer based on mass spectra of blood samples

The early detection of cancer is crucial for successful treatment, and medical researchers have investigated a number of early-diagnosis techniques. Recently, they have discovered that some cancers affect the concentration of certain molecules in the blood, which allows early diagnosis by analyzing the blood mass spectrum. Researchers have developed several techniques for the analysis of the mass-spectrum curve, and used them for the detection of prostate, ovarian, breast, bladder, pancreatic, kidney, liver, and colon cancers. We have continued this work and applied data mining to the diagnosis of ovarian cancer. We have identified the most informative points of the mass-spectrum curve, and then used decision trees, support vector machines, and neural networks to determine the differences between the curves of cancer patients and healthy people.