New guidelines for reporting on experiments with medical AI aim to ensure that such research is transparent, rigorous, and reliable. Spirit-AI and Consort-AI are complementary protocols designed to improve the quality of clinical trials for AI-based interventions.

Convolutional neural networks are good at recognizing disease symptoms in medical scans of patients who were injected with iodine-based dye, that makes their organs more visible. But some patients can’t take the dye. Now synthetic scans from a GAN are helping CNNs learn to analyze undyed images.

The White House called for new funding for AI research including a constellation of research centers. Nonetheless, the U.S. government’s annual spending on the technology still would lag behind that of several other...

A prosthetic leg that learns from the user’s motion could help amputees walk more naturally. Researchers from the University of Utah designed a robotic leg that uses machine learning to generate a human-like stride.

Neural networks are famously bad at interpreting input that falls outside the training set’s distribution, so it’s not surprising that some models are certain that cat pictures show symptoms of Covid-19. A new approach won’t mistakenly condemn your feline to a quarantine.

A new report details the role of AI in China’s effort to fight the coronavirus. Researchers at Synced, a China-based AI publication, describe how nearly 90 machine learning products have contributed to the country’s pandemic response.

Companies in Africa and the Middle East are building AI capacity in very different ways, a new study found. AI is growing fast in both regions despite shortages of talent and data.

A cat rotated by any number of degrees is still a cat. It takes a lot of rotated training images to teach convolutional filters this simple fact. A new filter design has this common-sense knowledge built-in.

Researchers are drawing up blueprints for drugs to fight Covid-19. Machine learning is identifying those most likely to be effective. Covid Moonshot, an international group of scientists in academia and industry, is crowdsourcing designs for molecules with potential to thwart the coronavirus.

Like nurses who can’t decipher a doctor’s handwriting, machine learning models can’t decipher medical scans — without labels. Conveniently, natural language models can read medical records to extract labels for X-ray images.

Israeli and American hospitals are using an algorithm to flag individuals at high risk for Covid-19 complications.

Researchers have rushed out a battery of AI-powered tools to combat the coronavirus, but an assessment of dozens of models is a wake-up call for machine learning engineers.

An AI-driven alarm system helps rescue patients before infections become fatal. The problem: Machine learning can spot patterns in electronic health data indicating where a patient’s condition is headed that may be too subtle for doctors and nurses to catch.

Eric Topol is one of the world’s leading advocates for AI in medicine. Below he shares his insights into the fusion of AI and medicine and advice for machine learning engineers who want to get involved.

Doctors are overwhelmed by clerical work. Healthcare-savvy voice assistants are picking up the slack.