Deep learning is a subset of machine learning in Artificial Intelligence (AI)
that has networks capable of learning unsupervised, unstructured or
unlabelled data. Deep Learning plays a vital role in the early detection
of cancer.
A study published by NVIDIA showed that deep learning drops error rate
for breast cancer diagnoses by 85%. In addition to being the second
leading cause of death, cancer also has significant and increasing
impacts on economy. Fortunately, deep learning has shown capabilities in
achieving higher diagnostic
accuracy results in comparison to many domain experts. While this may
be an issue of contention with physicians, for many would-be victims the
technology can’t come soon enough.
Researchers from Oregon State University were able to use deep learning for the extraction of meaningful features from gene expression data,
which in turn enabled the classification of breast cancer cells. They
have used the technology to extract genes considered useful for cancer
prediction, as well as potentially useful cancer biomarkers,
for the detection of breast cancer. Researchers in China also
developed DeepGene, an advanced cancer type classifier based on deep
learning that addresses the obstacles in existing somatic point
mutation based cancer classification (SMCC) studies. Results showed that
DeepGene outperforms three widely adopted existing classifiers, as it
was able to extract the high-level features between combinatorial
somatic point mutations and specific cancer types. Deep learning can be
used to measure the size of tumors undergoing treatment and detect new
metastases that might be overlooked.
Early cancer detection and prognosis is
one of several important healthcare areas where deep learning
technology has been applied. The use of deep learning in
oncology increases the chances that one day, machines may help
researchers find a coveted cure and prevention methods for the
development of cancer.
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