Thirty days. That's how much time a woman typically has between when she is diagnosed with breast cancer and when she begins her treatment. There's a lot to learn in that one short month. What lab tests are necessary - when, and how to interpret them. What treatment options are right for your particular kind of cancer-mastectomy, radiation, chemotherapy. What doctors you'll need-general surgeon, reconstruction surgeon, oncologist-and how you'll interview them to choose the best ones for your needs. What is the science behind integrative therapies-diet, supplements, exercise, massage-and which ones can give you the most bang for the buck to enhance your outcome? Preparing for your breast cancer treatment can be like completing a whole medical residency in one short month. Julie A. Buckley, MD, a functional medicine specialist, found herself in just this situation when she was diagnosed with breast cancer in 2009. She teamed with her breast reconstruction surgeon, Ankit Desai, MD, to find the answers to these questions and more. Together Drs. Buckley and Desai have created the comprehensive guide every newly diagnosed breast cancer patient needs to take control of her cancer treatment and to guide her through the myriad medical, emotional, and lifestyle issues she'll face. Practical, and brimming with optimism, Buckley and Desai make the cutting edge of breast health science accessible. This book will empower you to knowledgeably and confidently make the decisions that will save-and enhance-your life.

This book provides a review and a research of a special type of classification technique which is known as cost-sensitive data mining. Cost-sensitive data mining is an essential technique of data mining for applications like fraud-detection and loan-approval where the cost of misclassification of a sample is critical. It provides an overview of many algorithms which falls under this cluster. Proposed algorithms namely, CSExtension1, CSExtension2, CSExtension3, CSExtension4 and CSExtension5 are implemented and tested as an extension to data mining tool weka by the author of this book. These all algorithms provide adequate results for the parameters, cost-of-misclassificaiton and number of high cost errors. At the end, it gives new directions to its readers for unexplored areas in the same domain.