Diagnosis of ovarian cancer based on mass spectra of blood samples
Hong Tang, Yelena Mukomel, and Eugene Fink
In Proceedings of the IEEE International Conference
on Systems, Man, and Cybernetics, pages 3444-3450, 2004.
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
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.