Researchers aim to speed up developing drugs against brain diseases through cutting-edge technology. They are generating an innovative technology platform based on high-density microelectrode arrays and 3D networks of human neurons.
Artificial intelligence has unimaginable potential to revolutionize medicine. We cover the latest technology breakthroughs of machine learning, deep learning algorithms, neural networks and pattern recognition that process mindboggling amounts of data, spot even the smallest detail in medical images and help medical professionals in designing treatment plans.
Researchers used an artificial intelligence (AI) algorithm to sift through terabytes of gene expression data to look for shared patterns in patients with past pandemic viral infections, including SARS, MERS and swine flu.
The University of Texas at San Antonio (UTSA) has established a wearables and artificial intelligence laboratory to provide precision treatment plans to improve learning among those diagnosed with autism spectrum disorder (ASD).
A team of engineers from Rensselaer Polytechnic Institute and clinicians from Massachusetts General Hospital developed a deep learning algorithm that can help assess a patient's risk of cardiovascular disease with the same low-dose computerized tomography (CT) scan used to screen for lung cancer.
A new study from the Mayo Clinic found that differences between a person's age in years and his or her biological age, as predicted by an artificial intelligence (AI)-enabled EKG, can provide measurable insights into health and longevity.
AI-driven healthcare has the potential to transform medical decision-making and treatment, but these algorithms must be thoroughly tested and continuously monitored to avoid unintended consequences to patients.
Trained to see patterns by analyzing thousands of chest X-rays, a computer program predicted with up to 80 percent accuracy which COVID-19 patients would develop life-threatening complications within four days.
Artificial intelligence could help to optimise the development of antibody drugs. This leads to active substances with improved properties, also with regard to tolerability in the body.
Human-machine interaction is complex. Researchers investigate a new form of interaction between humans and machines.
Researchers combined motion analysis that uses smartphone application and machine learning that uses an anomaly detection method, thereby developing a technique to easily screen for carpal tunnel syndrome.
Researchers have created a machine learning model that helps identify bipolar disorder at earlier stages.