A coronavirus app coupled with machine intelligence will soon enable an individual to get an at-home risk assessment based on how they feel and where they've been in about a minute.
A wearable sensor could help doctors remotely detect critical changes in heart failure patients days before a health crisis occurs and could prevent hospitalization.
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.
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.
Ensembles created using models submitted to the RSNA Pediatric Bone Age Machine Learning Challenge convincingly outperformed single-model prediction of bone age.
Dementia screening could be as easy as using a smartphone app that listens to elderly people speak.
Radiologists assisted by deep learning based software were better able to detect malignant lung cancers on chest X-rays.
Researchers show that deep learning algorithms perform similar to human experts when classifying blood samples from patients suffering from acute myeloid leukemia.
Researchers have shown that AI can evaluate written messages by patients with severely diseased livers to detect language abnormalities associated with liver disease.