Deep Learning Outperforms Standard Machine Learning in Biomedical Research Applications, Research Shows

Geordia State University : Compared to standard machine learning models, deep learning models are largely superior at discerning patterns and discriminative features in brain imaging, despite being more complex in their architecture, according to a new study in Nature Communications led by Georgia State University.

Advanced biomedical technologies such as structural and functional magnetic resonance imaging (MRI and fMRI) or genomic sequencing have produced an enormous volume of data about the human body. By extracting patterns from this information, scientists can glean new insights into health and disease. This is a challenging task, however, given the complexity of the data and the fact that the relationships among types of data are poorly understood.

Can These Artificial Intelligence Apps Improve Mental Health?

Columbia: More than 20 percent of Americans will have symptoms of depression or anxiety this year, but only one in five of them will get adequate treatment. Increasingly, people are turning to smart phone apps for help. There’s only one problem: none of the thousands of mental health apps available have so far been adequately tested to see if they provide relief.