AI is increasingly being used in medicine to support human expertise. A study has now illustrated the enormous potential of human/computer collaboration.
Students at Cranfield University have designed computer models that can identify COVID-19 in X-rays.
Scientists have developed an experimental diagnostic test for COVID-19 that can visually detect the presence of the virus in 10 minutes.
Transforming how common health conditions are diagnosed using point-of-care and wearable bio diagnostic devices is the goal of a new University of South Australia project.
Researchers at King’s College London, Massachusetts General Hospital and health science company ZOE have developed an AI diagnostic that can predict whether someone is likely to have COVID-19 based on their symptoms.
Radiologists are investigating people's medical conditions and pregnancies remotely thanks to an ESA-backed robotic technology.
Researchers have developed a new approach to early diagnosis of lung cancer: a urine test that can detect the presence of proteins linked to the disease.
An AI algorithm is capable of diagnosing 134 skin disorders and supporting specialists by augmenting the accuracy of diagnoses and predicting treatment options.
A portable surveillance device powered by machine learning can detect coughing and crowd size in real time, then analyze the data to directly monitor flu-like illnesses trends.
The UNC School of Medicine lab of Jason Franz, PhD, created virtual reality experiments to show how a potentially portable and inexpensive test could reduce falls and related injuries in people with multiple sclerosis.
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.