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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.
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