New machine learning study suggest the presence of at least nine gender “expressions”.
Artificial intelligence has unimaginable potential to revolutionize medicine. We cover the latest technology breakthroughs of machine learning and deep learning algorithms that process mindboggling amounts of data, spot even the smallest detail in medical images and help medical professionals in designing treatment plans.
To better leverage cancer data for research, scientists are developing an artificial intelligence-based natural language processing tool to improve information extraction from textual pathology reports.
By adding infrared capability to the ubiquitous, standard optical microscope, researchers hope to bring cancer diagnosis into the digital era.
Usind deep learning and digital scanning of conventional hematoxylin and eosin-stained tumor tissue sections, researchers have developed a clinically useful prognostic marker.
A deep learning model can identify sleep stages as accurately as an experienced physician.
A novel method of combining advanced optical imaging with an artificial intelligence algorithm produces accurate, real-time intraoperative diagnosis of brain tumors.
Using a computer algorithm, scientists at Uppsala University have identified a promising new treatment for neuroblastoma.
An AI has successfully found features in pathology images from human cancer patients, without annotation, that could be understood by human doctors.
A deep neural network model helps predict healthcare visits by elderly people, with the potential to save millions.
A software tool uses artificial intelligence to recognize cancer cells from digital pathology images — giving clinicians a powerful way of predicting patient outcomes.
An AI platform can analyze genomic data extremely quickly, picking out key patterns to classify different types of colorectal tumors and improve the drug discovery process.
A new statistical technique from the field of machine learning is now making it possible to predict the success of smartphone-based interventions more accurately.
Researchers have discovered that a population of neurons in the brain’s frontal lobe contain stable short-term memory information within dynamically-changing neural activity.
Using machine learning, a prototype microscope teaches itself the best illumination settings for diagnosing malaria.