How deep learning can improve cancer diagnoses - AI News

In December, Brazilian federal auditor Luis Andre Dutra e Silva improved the accuracy of cervical cancer screening by 81 percent using the Intel Deep Learning SDK and GoogleNet using Caffe to train a Supervised Semantics-Preserving Deep Hashing (SSDH) network. The driving factor behind the deep learning-based research that Silva and others are working on is that, as a leading cause of death, cancer affects millions of lives every year. Early detection and diagnosis can save not only billions of dollars but also countless lives. Much of the data generated from research, trials and tests, however, comes from incompatible and innumerable sources that can be complex and labour-intensive to properly examine. As a result, the bulk of this data remains largely underutilised.