Breast Cancer: Advancement in Diagnostic and Treatment

Diagnosis And Modeling Techniques

It is well recognized that in treatment and diagnostic of breast cancer, clinicians are often presented with identical clinical information. However, unfortunately clinicians can act in different ways depending on their knowledge and experience which highlighted the need to introduce diagnostic tools to support the scientific homogeneity and accountability of healthcare decisions and actions. The benefits expected from such actions include an overall reduction in cost, improved quality of care as well as patient and public opinion satisfaction. Recently, computer-based medical data processing research has yielded methods and tools for managing the task away from the hospital management level and closer to the desired disease and patient management level.

In search of an accurate tool for distinguish and diagnostic cancer lesions various techniques have been proposed. Recent research focuses primarily on the application of computer vision and for early lesion identification in mammograms and breast-imaging volumes through computer-aided diagnostics (CAD) tools with particular emphasis on computational diagnostics methodology for the analysis of molecular disease mechanisms in cancer. To this end, advanced applications of information and disease process modeling technologies have already demonstrated an ability to significantly augment clinical decision making. One of the main obstacles that need to be overcome is the development of systems that treat both information and knowledge as clinical objects with same modeling requirements. Here we briefly describe some of the existing computational models used for classification of the types of breast lesion in brief here.