Combining artificial intelligence, mathematical modeling, and brain imaging data, researchers shed light on the neural processes that occur when people use mental abstraction.
Blood tests revealed specific epigenetic biomarkers for schizophrenia. Researchers applied machine learning to analyze the CoRSIVs region of the human genome to identify the schizophrenia biomarkers. Testing the model with an independent data set revealed the AI technology can detect schizophrenia with 80% accuracy.
Researchers propose a novel computational framework that uses artificial intelligence technology to disentangle the relationship between perception and memory in the human brain.
Artificial intelligence technology was able to accurately predict attachment in young children.
A new artificial intelligence algorithm can find the quickest trajectory to fly a drone through a series of waypoints on a circuit. The AI proved to be faster at controlling the drone and completing the track than two world-class human pilots.
A new brain-machine interface allows wearers to wirelessly control a wheelchair or robotic arm by simply imagining an action. The neuroprosthesis could help improve the quality of life for those with disabilities.
Researchers created a new human brain model using machine learning-based optimization of required user profile information.
Combining artificial intelligence technology with speech analysis, researchers report while AI can be used to assess speech patterns for signs of Alzheimer's, the specific task assigned to the person being tested plays a critical role in the accuracy of diagnosis.
Combining machine learning with neuroimaging data, researchers identified a brain region that appears to govern contextual associations.
Combining deep learning algorithms with robotic engineering, researchers have developed a new robot able to combine vision and touch.
Using data from brain activity, researchers were able to replicate the song of zebra finches in exact detail.
A new deep learning algorithm is superior to human experts in distinguishing between retinal ganglion cells in healthy patients and in those with glaucoma. The AI system could potentially help improve the diagnosis of both eye and brain diseases.
