While artificial agents (AA) such as Artificial Intelligence are being extensively developed, a popular belief that AA will someday surpass human intelligence is growing. The present research examined whether this common belief translates into negati...
BACKGROUND: Risky behaviors can lead to huge economic and health losses. However, limited efforts are paid to explore the genetic mechanisms of risky behaviors.
We present a possible method of Artificial Intelligence (AI) based applications that can effectively filter noise-sensitive bone scintigraphy images. The use of special AI, based on preliminary examinations, allows us to significantly reduce study ti...
Current artificial intelligence (AI) in medicine has high performance, particularly in diagnostic and prognostic image analysis, but, in everyday clinical practice, evidence-based results of AI remain limited. In this forum, are analyzed the characte...
There is significant interest in the development and application of deep neural networks (DNNs) to neuroimaging data. A growing literature suggests that DNNs outperform their classical counterparts in a variety of neuroimaging applications, yet there...
Despite recent breakthroughs in machine learning, current artificial systems lack key features of biological intelligence. Whether the current limitations can be overcome is an open question, but critical to answer, given the implications for society...
We used two simple unsupervised machine learning techniques to identify differential trajectories of change in children who undergo intensive working memory (WM) training. We used self-organizing maps (SOMs)-a type of simple artificial neural network...