Researchers have introduced PlasmidHawk, a bioinformatics approach for DNA sequence analysis to help identify the source of engineered plasmids of interest.READ MORE
A research team is tackling the debilitating neurological condition epilepsy with a powerful new seizure predicting mathematical model that will give patients an accurate warning five minutes to one hour before they are likely to experience a seizure, offering enhanced freedom for the patient and cutting the need for medical intervention.READ MORE
Researchers have published a paper documenting the ability of an innovative AI system, dubbed Go-Explore, to outperform both human and state-of-the-art algorithmic rivals at an entire suite of classic Atari 2600 games now used as benchmarks for machine intelligence.
In using data from human motion perception studies, researchers have trained an artificial neural network to estimate the speed and direction of image sequences. The study uses the system to describe how space and time information is combined in our brain to produce our perceptions, or misperceptions, of moving images.READ MORE
A new study has found that the percentage of individuals willing to sacrifice their own safety increased by two-thirds when informed that their peers were more likely to sacrifice their own safety, programming their vehicle to hit a wall rather than hit pedestrians who were at risk.READ MORE
Using machine learning tools to analyze hundreds of proteins, UT Southwestern researchers have identified a group of biomarkers in blood that could lead to an earlier diagnosis of children with autism spectrum disorder (ASD) and, in turn, more effective therapies sooner.
Diabetes is a permanent condition that requires lifetime care, and the incidence is rising. To help manage it, an artificial pancreas system can be utilized which has been upgraded with an AI algorithm. The system automatically measures blood sugar levels to infuse the appropriate amount of insulin into the blood.READ MORE