The use of data mining approaches in medical domains is increasing rapidly. This is mainly because the effectiveness of these approaches to classification and prediction systems has improved, particularly in relation to helping medical practitioners in their decision making. This type of research has become important for finding ways to improve patient outcomes, reduce the cost of medicine, and...

Introduction: Lack of a proper method for early detection and diagnostic errors in medicine are some fundamental problems in treating cancer. Data analysis techniques may significantly help early diagnosis. The current study aimed at applying and evaluating neural networks and decision tree algorithm on breast cancer patients’ data for early cancer prediction. Methods: In the current stu...

Introduction: Lack of a proper method for early detection and diagnostic errors in medicine are some fundamental problems in treating cancer. Data analysis techniques may significantly help early diagnosis. The current study aimed at applying and evaluating neural networks and decision tree algorithm on breast cancer patients’ data for early cancer prediction. Methods: In the current stu...

Researchers have made considerable progress in last few decades in understanding mechanisms underlying pathogenesis of breast cancer, its phenotypes, its molecular and genetic changes, its physiology, and its prognosis. This has allowed us to identify specific targets and design appropriate chemical entities for effective treatment of most breast cancer phenotypes, resulting in increased patien...

prediction, diagnosis, recovery and recurrence of the breast cancer among the patients are always one of the most important challenges for explorers and scientists. nowadays by using of the bioinformatics sciences, these challenges can be eliminated by using of the previous information of patients records. in this paper has been used adaptive nero fuzzy inference system and data mining techniqu...

The invasiveness and low survivability on the part of patients associated with cancer continues to raise global concern. Different approaches have been used in treatment restoration normalcy patients. However, most therapeutic strategies employed are challenged high cost, efficacy, toxicity, multiple side effects. In recent times, emergent studies provided evidence that functional foods their b...

Modeling of second primary lung cancer (SPLC) patients' survival prediction has important theoretical significance and practical needs. Cancer survivability may provide advice for better clinical decisions personalized medicine. The Surveillance, Epidemiology, End Results (SEER) program provides large data sets analysis with machine learning methods. SPLC cases are identified labeled from the S...

Application of data mining methods as a decision support system has a great benefit to predict survival of new patients. It also has a great potential for health researchers to investigate the relationship between risk factors and cancer survival. But due to the imbalanced nature of datasets associated with breast cancer survival, the accuracy of survival prognosis models is a challenging issue...

the present research is a field study in order to investigate scale and ways of doing breast self examination (bse). 270 nurses employed by the medical sciences university’s hospitals related to the ministry of health, and medical education in city of tehran are selected and involved in research on the basis of simple random sampling. the data collection tool was a protrayed questionnaire which...