Mouse show different facial expression depending on their emotional state. Using machine learning, researchers were able to link five different emotional states to the facial expressions of mice. Read More
A new machine learning algorithm can predict which tumors were lower-grade gliomas or glioblastoma brain cancer with a high degree of accuracy. Read More
Combining advance microscopy techniques and artificial intelligence, researchers reconstruct the entire vascular network of a mouse brain down to its finest details. Read More
A new computer model captures the human visual system's ability to quickly generate a detailed scene description from an image. Read More
Combining neuroimaging data with machine learning technology, researchers discover children with well-connected brain hubs have either very specific cognitive problems, such as poor listening skills, or no cognitive difficulties at all. Children with poorly connected hubs have widespread and severe cognitive difficulties. Read More
A new deep learning algorithm helped researchers identify a powerful new antibiotic compound that kills many of the world's most problematic, disease-causing bacterias, including those which have so far been resistant to common antibiotics. Read More
AI model determined three key features that accurately predict subsequent, severe disease in COVID-19 patients. The three features were levels of the liver enzyme ALT, reported myalgia, and hemoglobin levels. Based on these three factors, the AI was able to determine ARDS risk with 80% accuracy. Read More
Researchers have developed a portable surveillance device that uses machine learning to detect coughing and crowd size in real-time. The system can use the data to directly monitor flu-like illnesses, community trends, and virus spread potential. The system could help monitor the spread of infection and provide a public health response during an epidemic. Read More
The brain quickly transitions from one network to another in regular patterns. The transition trajectories constitute a temporal circuit where the conscious brain cycles through a structured pattern of states over time. Read More
Combining neuroimaging data with artificial intelligence, researchers have identified two distinct neuroanatomical subtypes of schizophrenia. The first, more typical subtype is associated with a lower widespread volume of gray matter compared to healthy controls. In the second subtype, gray matter volume is largely similar to healthy brains. Read More
Researchers have created a hybrid neural network where biological and artificial neurons in different parts of the world were able to communicate via the internet through a hub of memristive synapses. Read More
Brain activity while in a resting state can predict how empathetic a person is. Researcher used a combination of neuroimaging data and machine learning to identify subtle patterns in brain activity associated with empathy. Read More
