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.