The robot can learn how to read a brain wave pattern and then help a medical professional treat the injury, according to a paper published this week in Nature Neuroscience.
The researchers were inspired by the work of two other researchers who were able to teach a patient to read and understand a pattern of brain waves after they lost their ability to speak.
They had previously learned to read patterns of brain activity, such as a person’s heart rate, by training a robot on a video game.
The team used the same method to teach doctors to treat strokes, but the new technique is much more advanced and includes a large number of features, including a neural network.
It was designed with the goal of helping doctors to learn how a patient responds to their treatments.
The neural network is designed to simulate a patient’s brain activity using an MRI scan of the brain.
It can then use that data to train a model of the patient that responds to a specific treatment.
That patient model can then be trained to use that model to make predictions about how to correct a patient, which the researchers hope will help doctors more quickly identify potential treatment errors.
The study, which was led by University of Pennsylvania neuroscientist Jeffrey Vickers, looked at how neural networks learn to respond to certain stimuli, such a pattern or a person.
They also examined how neural nets can be trained in the lab and then be used to make a prediction.
In the current study, the researchers trained a neural net to read the patterns of a person on a MRI scan.
They then trained it to predict the next wave in the pattern.
The trained model could then learn to identify the pattern based on how the patient responded to the stimulus.
The model could predict which treatment a patient might need based on the response it had received.
The authors concluded that the neural network trained on a human brain could learn to read pattern patterns in the brain, which they say is a new form of machine learning.
In their study, Vickers and his team demonstrated that their neural net could successfully predict patterns of activity that a patient had previously responded to with the same pattern of activity, the team wrote in the paper.
“We are now on a trajectory to enable human doctors to more quickly detect and correct potentially life-threatening brain injury,” Vickers told Ars.
“We hope this research opens up the door to other ways of treating patients with neurological disorders, which may include treating traumatic brain injuries.”
The researchers are currently developing a neural-net model that can be used in brain-machine interfaces, which are another form of technology that relies on neural networks to predict what the brain is going to do next.