A software tool for determination of breast cancer treatment methods using data mining approach.
In this work, breast cancer treatment methods are determined using data mining. For this purpose, software is developed to help to oncology doctor for the suggestion of application of the treatment methods about breast cancer patients. 462 breast cancer patient data, obtained from Ankara Oncology Hospital, are used to determine treatment methods for new patients. This dataset is processed with Weka data mining tool. Classification algorithms are applied one by one for this dataset and results are compared to find proper treatment method. Developed software program called as "Treatment Assistant" uses different algorithms (IB1, Multilayer Perception and Decision Table) to find out which one is giving better result for each attribute to predict and by using Java Net beans interface. Treatment methods are determined for the post surgical operation of breast cancer patients using this developed software tool. At modeling step of data mining process, different Weka algorithms are used for output attributes. For hormonotherapy output IB1, for tamoxifen and radiotherapy outputs Multilayer Perceptron and for the chemotherapy output decision table algorithm shows best accuracy performance compare to each other. In conclusion, this work shows that data mining approach can be a useful tool for medical applications particularly at the treatment decision step. Data mining helps to the doctor to decide in a short time.
Cakır
Abdülkadir
A
Department of Electronics-Computer Education, Süleyman Demirel University, Isparta, Turkey. cakir@tef.sdu.edu.tr
Demirel
Burçin
B
D000367:Age Factors; D000465:Algorithms; D001943:Breast Neoplasms / Q000175:diagnosis / Q000628:therapy*; D057225:Data Mining; D020000:Decision Support Systems, Clinical / Q000295:instrumentation*; D005260:Female; D006801:Humans; D008297:Male; D008593:Menopause; D009367:Neoplasm Staging; D011379:Prognosis; D012985:Software Design; D016019:Survival Analysis