Research | February 2020

According to a new AI simulation, the Wuhan coronavirus could kill 52.9 million people within 45 days—and infect 2.5 billion overall.

Researchers out of Wuhan, China, have developed a new AI-based quality improvement system for colonoscopies, sharing their findings in The Lancet: Gastroenterology & Hepatology.

When AI first started gaining popularity in healthcare, many providers were critical, skeptical or just avoided learning about the technology altogether. However, according to a new analysis, the time has come for cardiologists to step up and pay close attention.

AI models can be trained to predict outcomes in meningioma patients, according to new research published in npj Digital Medicine. The study’s authors even developed a free smartphone app so others can explore their work.

Researchers have found they can use microbe samples—and a little help from machine learning techniques—to predict someone’s age.

Machine learning (ML) can provide significant value in the field of palliative care. However, researchers still have a lot of unexplored ground to cover before the technology reaches its full potential.

Machine learning-based algorithms can predict how patients will respond to antidepressants, according to new research published in Nature Biotechnology. The secret, the authors revealed, is electroencephalography (EEG) data.

AI can help improve malaria screening in low-resource settings, according to a new study published in the Journal of Digital Imaging. The model developed by researchers is as precise as human experts—and “several orders of magnitude” faster.

AI models can be trained to predict outcomes for patients receiving thrombolysis for acute ischemic stroke (AIS), according to a new study published in the Journal of the Neurological Sciences.

Dermatologists need to be more involved in the development of AI technologies designed to evaluate skin cancer, according to a new analysis published in the Journal of the American Academy of Dermatology.