Abstract: Breast cancer research over the last decade has been tremendous and the novel methods being develop help in the early detection, in setting the stages of the therapy and in assessing the response of the patient to the treatment. Some of the studies look very promising and their use in future may decrease the radiation dose to the patient. This paper studies various techniques used for the diagnosis of breast cancer. Different methods are explored for their merits and de-merits for the diagnosis of breast lesion. It was found that the recent use of the combination of Artificial Neural Networks in most of the instances give accurate results for the diagnosis of breast cancer and their use can also be extended to other diseases.
I. INTRODUCTION
Breast cancer is the second leading cause of deaths in women worldwide [1-4], the risk increasing with the age. Breast cancer affects not only women but also men and animals. Only 1% of all the cases are found in men. There are two types of breast lesions- malignant and benign. The Radiologists study various features to distinguish between the malignant tumour and benign tumour. 10%-30% of the breast cancer lesions are missed because of the limitations of the human observers [5, 6]. The malignant tumour is in many cases misdiagnosed and its late diagnosis reduces the chances of survival of the patient. Early and accurate diagnosis is essential for patient’s timely recovery. Identifying the women at risk is an important strategy in improving the number of women suffering from breast cancer. Conventionally, biopsy was used for the diagnosis, nowadays mammography, breast MRI, ultrasonography, BRCA testing etc. are done. When a number of tests are performed on a patient it becomes ...
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Breast cancer is one of the most common and important diseases that affect women and ovarian cancer is the fourth most common cause of cancer mortality in American women1. These cancers are triggered by germline mutations on the C-terminal of a gene called BRCA1 (or “Breast Cancer 1, Early Onset Gene”) tumor suppressor. The BRCA1 gene is located on the long (q) arm of chromosome 17 at region 2 band 1, consists of 24 exons and encodes a multidomain protein of 1863 amino acid residues in human2. The BRCA1 proteins produced from BRCA1 gene help preventing cells from growing and dividing too rapidly or in an uncontrolled way3. The family of BRCA1 genes is called RING-type zinc fingers or RNF. The BRCA1 protein is characterized within the superfamily of Rad9-like proteins which consist of C-terminal BRCT repeats that assist in the binding of phosphorylated proteins in the DNA damage response and DNA repair4. Like many other genes involved in familial cancer, BRCA1 appears to encode a tumor suppressor, a protein that acts as a negative regulator of tumor growth1. BRCA1 proteins are important in genomic stability so loss of their function can cause genetic instability which lead to tumourigenesis. Thus, the sequence of BRCA1 protein is analyzed to the understanding the protein’s function in the development of the cancers.
Over the past decade breast cancer has become one of the most predominant diseases in the United States. Breast cancer starts out as a malignant tumor in the tissues of the breast which is formed from the uncontrolled growth of abnormal breast cells. Breast cancer is the most common cancer in women, but it can also appear in men. (Stephan, 2010)
Surgical Oncology is a subset of oncology that focuses on the surgical management of cancer. Though, it has not been ratified by a Board certification, this area of expertise is coming to its own by the success of combined treatment with chemotherapy, radiation, and targeted biological treatments. Through developing technology, such as the iKnife, surgery to target tumorous cells is becoming a necessary and popular field of medicine and is a very viable option for cancer procedures, both for treatment and prevention. This paper will explore the probability of a breast cancer patient undergoing more than one surgery given that surgery is the best treatment option. The purpose of this investigation is to determine the effectiveness and accuracy of breast cancer operations in completely eliminating tumorous cells based on size of tumor and location/accessibility. By no means is this a medically sponsored or medically recommended paper and the exploration should be read with this in mind.
Giurescu, M., Hu, T., & Obembe, O. (2010). Role of imaging in breast cancer detection.
The fact that the study was conducted by qualified medical doctors authenticated the process of the study since the researchers had good knowledge of breast cancer. The study was also conducted in two separate countries, which widened the scope of the study thereby increasing the applicability in terms of geography.
About 12% of women in the United States will develop breast cancer in their lifetime, more than any other type of cancer (www.breastcancer.org, 2015). Many people lack the knowledge of how breast cancer is developed. Some people think they will not get cancer because they do not smoke cigarettes, but this is not the only cause of cancer developing in the breast. Anyone can get cancer. Everyone is potentially at risk for developing some form of Cancer (American Cancer Society, 2015).
Stergiou, C., & Siganos, D. (2011, August 6). Neural Networks. Retrieved August 6, 2011, from
According to Breast Cancer Statistics, Breast cancer usually occurs in women between the ages of 35 and 65, even though fifty percent of all breast cancer is of women sixty-five and older (Breast Cancer Statistics, 2008). Although the cause of cancer is unknown, there are factors that increase the chances of getting it. These facto...
In the United States, starting from the first breast cancer case in 1930s to today, a woman's lifetime risk of breast cancer increases to one eighth (Gray et al.). Continuously increasing breast cancer rate has caused a lot of concerns among not only ordinary people but also scientists. For decades, scientists have been working on the causes of breast cancer in order to find the corresponding methods of treatment. However, only about 25% of the breast cancer cases got explained (Brody et al.); till today, heredity, lifetime exposure to environmental estrogen (the female sex hormone), and the dietary fat are the only major known causes (“Cover Story: Breast Cancer and Environment”). For the 75% unexplained breast cancers cases, scientists, through various of researches, have come up with several hypothetical breast cancer causes, in which synthetic chemicals and environmental radiations are the major ones.
Treatment for primary, localized breast cancer commonly includes surgical interventions based on tumor type, size, and stage. Certain procedures such as a local excision or lumpectomy conserve more of a woman’s breast than others, where only the breast lump and surrounding area of tissue are removed. A mastectomy is a more radical procedure that removes the entire breast. After a mastectomy, some women choose to have breast reconstructive surgery to restore their sense of body integrity (LeMone et al., 2011). Recently, surgical techniques have improved, resulting in less radical and invasive surgeries. The increase in breast conserving surgery has been related to screening mammograms. On average, screening for breast cancer detects tumors in smaller and earlier stages, enabling patients to begin treatment before the cancer advances to more invasive stages (Watts, 2013).
Today in the United States, Breast Cancer occurs in about one in eight women which is currently the most common cancer among women. The number of cases is expected to decrease due to the advancements in technology and dedicated researchers. Scientists have put an estimated 4.8 billion dollars towards the research every year to help find a cure or a new treatment for breast cancer ("STAT Facts Breast Cancer"). Researchers have found causes, put in research and theories that help with understanding treatments, prevention and also common symptoms and coping mechanisms.
Breast Cancer is defined as “a group of solid tumor malignancies arising in the tissues of the breast” (Sarah Crawford, Richard Alder, 2013) in human and other mammals. It can happen to both men and women. For women, breast cancer is one of the leading causes of cancer death. According to National Cancer Institute, in the United States, the 2014 estimated new cases and deaths of female from breast cancer are 232,670 and 40,000, respectively. For male, it’s 430 deaths out of 2,360 new cases. From these numbers, we can see that women in the U.S. are greatly affected by breast cancer, thus, it’s not difficult to imagine the impact on a worldwide level. Although these numbers look frightening, people can actually survive from breast cancer if it is detected early and treated properly, so it is extremely important for all of us, especially women, to have a better understanding of breast cancer.
“Estimated to be diagnosed in 1 of every 8 women in their lifetime, breast cancer continues to present a public health concern (Haber 2322)”. Breast cancer is not biased. It affects men and women of all races and ages. “Cancer represents 30% of the burden posed by no communicable diseases in the Region of the Americas of the World Health Organization (Luciani, Silvana 640)”. In men it affects less than 1 percent of the population. Routine mammograms and checkups are not only healthy but can also save lives. Giving the doctor thirty minutes of your time could ultimately mean the difference between life and death in some cases.
Artificial neural networks are systems implemented on computer systems as specialized hardware or sophisticated software that loosely model the learning and remembering functions of the human brain. They are an attempt to simulate the multiple layers of processing elements in the brain, called neurons. These elements are implemented in such a way so that the layers can learn from prior experience and remember their outputs. In this way, the system can learn to recognize certain patterns and situations and apply these to certain priorities and output appropriate results. These types of neural networks can be used in many important situations such as priority in an emergency room, for financial assistance, and any type of pattern recognition such as handwritten or text-to-speech recognition.
Machine learning systems can be categorized according to many different criteria. We will discuss three criteria: Classification on the basis of the underlying learning strategies used, Classification on the basis of the representation of knowledge or skill acquired by the learner and Classification in terms of the application domain of the performance system for which knowledge is acquired.