Deep Learning

It would be an understatement to say that things can get pretty hectic in a hospital emergency room … enough so that staff occasionally administer the wrong medication. Soon, however, AI-enabled wearable cameras could help keep that from happening.

Trained on simple heart rate data, an AI model can predict an episode of atrial fibrillation 30 minutes in advance. With plans to incorporate it into a smartphone so it can analyze data from a smartwatch, the model would act as an early warning system.

Researchers developed an AI algorithm that automatically analyzes chest X-rays to rapidly detect COVID-19 infection with more than 98% accuracy, distinguishing between normal X-rays and X-rays from people with viral pneumonia.

Researchers have used AI to screen photographs of children’s retinas to diagnose autism with 100% accuracy. The findings suggest AI is a viable screening tool for early diagnosis, especially when access to a specialist child psychiatrist is limited.

In what will soon be commonplace in drug research, scientists have used an artificial-intelligence algorithmic program to identify a compound, currently used in antimalarial treatment, that can effectively reverse the bone deterioration of osteoporosis.

Using a deep-learning AI model, researchers have turned the humble chest X-ray into a more powerful tool for diagnosing heart problems. They say their novel approach could be used as a quick and accurate way of assessing heart function.

Using AI to spot melanoma in its early stages is an exciting possibility, and a new deep-learning system developed by Harvard and MIT scientists promises a new level of sophistication, by using a method known as the “ugly duckling” criteria.

A new algorithm has been developed to detect coronary artery disease solely from patient facial photos. The algorithm needs more refinement but experts suggest there are ethical considerations to resolve before a system like this can be deployed.

Ordinarily, if you want to create a lifelike 3D digital model of someone's face, a 3D scanner and/or multiple cameras are required. Now, however, scientists from Carnegie Mellon University have created a system that lets a smartphone do the job.

When a doctor prescribes a patient more than one drug they have no way to predict whether that combination will have an adverse side effect. A new system from Stanford University presents a novel solution – an AI-driven computer system than can predict the consequences of combining two drugs.

It seems we can add medical imaging to the list of fields about to be revolutionized by deep learning computers. A Chinese startup has revealed that its intelligent assisted diagnosis software for X-Ray and CT scans has already looked at over 200,000 scans in trials at 20 hospitals around China.