Combining brain activity data with artificial intelligence, researchers generated faces based upon what individuals considered to be attractive features.
Combining microscopy with artificial intelligence, researchers were able to visualize the complex architecture of interconnected neurons in live C. elegans.
Summary: An artificial neural network has identified a potential mechanism for the impaired decision-making often seen in schizophrenia patients, which involves the reduced activity of NMDA receptors.
A new machine-learning algorithm is more accurate at determining personality traits based on selfie photographs than humans are.
A 3D printed hand which uses a computer interface to learn can replicate hand movements.
A new deep learning algorithm can reliably determine what visual stimuli neurons in the visual cortex respond best to.
A new deep learning system is able to predict, with great accuracy, how different brain areas respond to specific words. The model also found concepts localized to the auditory cortex are less dependent on context.
A new convolutional neural network uses PET brain scans to detect biological signs of Alzheimer's disease years before the symptoms appear, researchers report.
Researchers at MIT have developed a new deep learning neural network that can identify speech patterns indicative of depression from audio data. The algorithm, researchers say, is 77% effective at detecting depression.
Researchers have created an artificial neural network from synthetic DNA that is able to correctly identify handwritten numbers.
Researchers have created a new audio-visual model that harnesses the power of deep neural networks that can isolate and enhance speech under natural conditions.
A new computer algorithm may help to identify sexual predators who target children in chatrooms. The algorithm, dubbed CATT, can identify language differences and self-disclosure in conversations to provide a risk assessment of potential predators, researchers report.
