Cancer analysis and prediction is the utmost important research field for well-being of humankind. The Cancer data are analyzed and predicted using machine learning algorithms. Most of the researcher claims the accuracy of the predicted results within 99%. However, we show that machine learning algorithms can easily predict with an accuracy of 100% on Wisconsin Diagnostic Breast Cancer dataset. We show that the method of gaining accuracy is an unethical approach that we can easily mislead the algorithms. In this paper, we exploit the weakness of Machine Learning algorithms. We perform extensive experiments for the correctness of our results to exploit the weakness of machine learning algorithms. The methods are rigorously evaluated to validate our claim. In addition, this paper focuses on correctness of accuracy. This paper report three key outcomes of the experiments, namely, correctness of accuracies, significance of minimum accuracy, and correctness of machine learning algorithms.
Results: A total of 10 688 adult patient samples representing 40 untreated primary tumor types and 26 adjacent-normal tissues were used for training. Demographic data were not available for all data sets. Among the training data set, 5157 of 10 244 (50.3%) were male and the mean (SD) age was 58.9 (14.5) years. An accuracy rate of 99% was obtained for primary epithelioid mesotheliomas tested (125 of 126). The remaining 85 mesotheliomas had a mixed etiology (sarcomatoid mesotheliomas) and were correctly identified as a mixture of their primary components, with potential implications in resolving subtypes and incidences of mixed histology.
Cancer is one of the leading causes of death in the U.S., and is expected to be the number one killer in 16 years. Men are more likely to die of cancer than women, but scientific advancements like antibiotics, vaccines, and chemotherapy have decreased how often people die of cancer. Prostate cancer is the leading cancer for males, but there are other cancers men should protect themselves against as well. Prostate cancer is the number one cancer risk for men, and the number two cancer killer (after lung cancer). About one man in seven will be diagnosed with prostate cancer during his lifetime, according to the American Cancer Society.
Fighter, warrior, hero - some of the terms you might see used to describe people with cancer. But according to a new survey, for some with the illness the words are seen as inappropriate rather than uplifting. The UK poll by Macmillan Cancer Support of 2,000 people who have or had cancer found "cancer-stricken" and "victim" were also among the least-liked terms. The charity said it showed how "divisive" simple descriptions of cancer can be. Calling a person's cancer diagnosis a "war" or a "battle" and saying they had "lost their battle" or "lost their fight" when they died, were other unpopular descriptions, according to the poll carried out by YouGov.