Breast Cancer Dataset: A Case Study

California Highway Patrol officers on Thursday were investigating a carjacking after the driver of a pink tow truck dedicated to an Arcata breast cancer center was forced to pull over along Highway 96 and robbed at gunpoint.

Mrs. Sheena a 69-year-old religious Jewish lady, admitted in internal medicine ward with abdominal pain and intestinal obstruction. She was diagnosed with breast cancer that had metastasized to the liver and bone. She was treated with a combination of anticancer drugs without response. Her family consisted of five children, four of whom were married with children and grandchildren. One of the patient's daughters, a 37-year-old single woman, had been diagnosed with stage II breast cancer. After a lumpectomy, she refused chemotherapy because of her desire to have a child. She only told her oldest brother about her illness; it was their secret. Mrs. Sheena’s mother and two of her sisters died because of breast cancer.

The area I am concentrating is the feature extraction and Feature selection of clinical image.

without living a healthy lifestyle. Making sure to take care of ones body is an important factor in the prevention of breast cancer.

Dr. Bartell tries to put across the point that, as much as we try, we cannot relate all aspects of the experiences we have had in life. Most of the details of how we live our lives are either forgotten or that sometimes, we just don’t want to disclose some details. The delivery of some kinds of information has to be censored. This is especially the case when addressing patients that are vulnerable to shock and mental stress. Dr. Bartell says, “Cancer patient information literature is developed within such paradigms, and offers vulnerable patients a narrative in which to situate themselves in a moment of disruption and destabilization” (Bartell, 6). Doctors have to be sensitive in their delivery of information to cancer patients to slowly guide them in the acceptance of their conditions.

Lydia is a 45-year-old Caucasian premenopausal female who is visiting her PCP for her annual physical examination. Part of her physical examination includes a 'ladies exam' including PAP smear and breast examination. On breast exam you note a small, painless lump in the right upper outer quadrant. There is no nipple discharge but dimpling was noted around the area of the lump when sitting upright. Lydia does practice breast self examination but not regularly. She has never had a mammogram. She is used to having lumps in her breast that seem to come and go with her menses and was told, in the past, she has fibrocystic breast disease. This particular lump did not resolve after her period, but she did not think anything of it since it was not painful.

For this assignment I decided to critique a website from the topic breast cancer. I started my search by typing breast cancer in the google engine. I then clicked on page eight until I found a website with a .com. I clicked on the article about breast cancer, then went to website the article was provided by. Critiquing a website can be difficult do to constant evolving of technology. As a result, the accuracy of a website need to be updated continuously. To ensure that your website is . I evaluated the EMedicineHealth website using the Evaluating Internet Research Sources from Robert Harris (Harris, 2010). This consists of an acronym for evaluation CARS (credibility, accuracy, reasonableness, and support). It was with this tool

Breast cancer is the most common cause of cancer-related death among females in the world. It is known for “have both a genetic and non-genetic etiology” (Milne et al., 2010). It involves a combination of several factors- such as “genetic, environmental and behavioral risk factors”- that are unique to each individual (Nickels et al., 2013). This type of cancer is represented by a malignant tumor manifested in breast cells such as the line duct and line lobules cells, just to name a few. Because there are different types of breast cancer, it is harder to create an effective treatment or therapy that would lower or prevent its death rates. Despite advances in technology but lack of monetary support, there is a higher prevalence in African countries (U.S. breast cancer statistics, 2013). It has been found that “two thirds of breast tumors express estrogen receptors” (Lopez-Tarruella & Schiff, 2007). Because of this, growth factor receptor signaling and hormone therapies have been shown as promising treatments to prevent and/or to find a cure for this cancer.

Diagnosis is the process of finding the cause of a health problem. This problem is detected through physical examination. Most of the tests to find out if you have breast cancer also show the stage of where your cancer is at. The following are a few tests done for diagnosis. Medical History test is a record of present symptoms, risk factors and medical events/problems a person has had in the past. This includes a personal history of breast disease or breast cancer, hormone replacement therapy, previous radiation therapy to the chest, and a family history of breast cancer, other cancers and symptoms that may relate to breast cancer. A Physical examination a doctor will do the Clinical breast examination test (CBE) to check the breast and lymph

I received a letter from my dentist, Dr, Thomas Seerveld, DMD, stating that he is retiring. He has been skillful and considerate of mine and my mother's entire health concerns. During my search to find another dentist, I visited the Holistic Dental Association's website and saw your name listed as an active member.

Breast cancer is a disease that starts when an abnormal, uncontrolled cell growth occurs in the tissues of the breast. In a healthy body, cells grow, divide, and die in an orderly way, but once a damage or a mutation happens in the genetic material of the cell (which is found in the DNA) it results in cells that do not die. They continue to grow and divide uncontrollably and form abnormal cells that the body does not need. They can also metastasize, which means they invade other tissues through the bloodstream or lymph vessels. In contrast, in normal cells, when DNA is damaged the cell either repairs the damage or dies (Sudhakar 2009).

Women diagnosed with Stage 1 breast cancer in which the tumour is two centimeters or smaller in size and the cancer has not spread outside the breast can be fairly optimistic they will beat the disease. The odds are also very good for Stage 2 in which the cancer has reached the lymph nodes. The five-year survival rate for this group is about 86 per cent.

six cycles of neoadjuvant single-agent cisplatin, and only4 (15%) achieved complete response (CR), after exclusion

It is one of the biggest challenges in data mining. It is a predictive modeling task with the specific aim of predicting the value of a single nominal variable based on the known values of other variables. Classification is the task of generalizing known structure to apply to new data. Classification is a data mining function that assigns items in a collection to target categories or classes. The goal of classification is to accurately predict the target class for each case in the data. A classification task begins with a data set in which the class assignments are known. Classifications are discrete and do not imply order. Continuous, floating-point values would indicate a numerical, rather than a categorical, target. A predictive model with a numerical target uses a regression algorithm, not a classification algorithm. The simplest type of classification problem is binary classification. In binary classification, the target attribute has only two possible values: for example, high credit rating or low credit rating. Multiclass targets have more than two values: for example, low, medium, high, or unknown credit rating the model build (training) process, a classification algorithm finds relationships between the values of the predictors and the values of the target. Different classification algorithms use different techniques for finding relationships. These relationships are summarized in a model, which can then be

The machine learning techniques that were utilized in this data analysis project were both applied to the Iris Data Set available at the UCI Machine Learning Repository (http://archive.ics.uci.edu/ml/datasets/Iris). This data was entered into a text file and saved with a .csv extension, then this .csv file was fed into the WEKA software for analysis. One of the techniques utilized was a simple visualization of the data spread, which has some predictive power in clearly demonstrating the spread of the data and thus the likelihood of obtaining the basic measurements of sepal length and width and petal length and width. The algorithm for this is simple, similar to what Excel or any basic spreadsheet can accomplish, yet is still demonstrative of machine learning in one of its simplest forms as earliest conceived (Andrieu et al, 2003). The second round of analysis conducted was a cross-validation analysis, which has more predictive power and is indicative of the stronger analytic powers available in machine learning as it forms a basic prediction of how accurate other predictions will be that is, the algorithm that is used to analyze the data also analyzes and adjusts itself in order to determine how close a fit it can come to the data (Bishop, 2006). The results of these analyses show a fairly normal distribution for sepal length and width but irregular distributions for petal length and width that would require a slightly different approach to certain modes of