A Systematic Review on Breast Cancer Disease Diagnosis with Different Datasets

Abstract

Breast malignancy is an affliction when breast containers evolve cruelly without expiring.
These are disastrous units that set the clump and deadlock different sane cells to drive perfectly
and therefore restrict the usual serving of the body. These lumps concede possibly favorable or
diseased, contingent upon the part of the breast where tumor composition begun. It is very
authoritative to pinpoint this ailment at boot camp so concerning get suitable medication timely
in accordance with its kind and level with a view to help the affected person to vanquish the
affliction and win the conflict of continuation. To help humans for the identical, few computer
advocated structures are pre-owned so as to investigate the ailment that would help the
oncologist in preserving their time of spotting the affliction that maybe used in medicating to
a greater extent and bestowing them the reward of survival. This review expounds the basic
knowledge of the disease as well as its severity. This paper reviews as well as compares various
systems developed with different datasets to diagnose the disease and found that although the
systems developed using Wisconsin dataset, MIAS dataset and DDSM dataset give high
accuracy up to 99% but these require a fearful procedure to be undertaken by women so as to
collect the data, such as biopsy or mammography which frightens the patients and thus many
women take a step back to go for this procedure and sometimes remain undiagnosed. On
throwing a light upon a new dataset i.e. Coimbra dataset we found that it requires the
attributes(anthropometric data) that can be collected by simple blood analysis which is a
fearless and painless procedure for patients to be undertaken but very few research has been
done using this dataset and the systems developed so far with this dataset have achieved the
accuracy of 91% which could be increased by working more upon it and thus adding state of
the art to the field where the disease could be diagnosed accurately with easy procedure of tests.