Performing a new task based solely on verbal or written instructions, and then describing it to others so that they can reproduce it, is a cornerstone of human communication that still resists artificial intelligence (AI). A team from the University of Geneva (UNIGE) has succeeded in modelling an artificial neural network capable of this cognitive prowess.

Researchers have developed a new, interpretable artificial intelligence (AI) model to predict 5-year breast cancer risk from mammograms, according to a new study published today in Radiology, a journal of the Radiological Society of North America (RSNA).

One in 8 women, or approximately 13% of the female population in the U.S., will develop invasive breast cancer in their lifetime and 1 in 39 women (3%) will die from the disease, according to the American Cancer Society.

There are thousands of diseases worldwide with no cure or available treatments. Traditional drug discovery and development takes decades and billions of dollars and more than 90% of these drugs fail in clinical trials. The emergence of artificial intelligence (AI) holds promise for streamlining and improving the entire process. However, ushering in a new era of AI-driven drug discovery requires costly and lengthy validation in preclinical cell, tissue, and animal models and human clinical trials.

When you teach a child how to solve puzzles, you can either let them figure it out through trial and error, or you can guide them with some basic rules and tips. Similarly, incorporating rules and tips into AI training - such as the laws of physics - could make them more efficient and more reflective of the real world. However, helping the AI assess the value of different rules can be a tricky task.

It can be challenging to gauge the quality of online news - questioning if it is real or if it is fake. When it comes to health news and press releases about medical treatments and procedures the issue can be even more complex, especially if the story is not complete and still doesn’t necessarily fall into the category of fake news.

Score another one for artificial intelligence. In a recent study, 151 human participants were pitted against ChatGPT-4 in three tests designed to measure divergent thinking, which is considered to be an indicator of creative thought.

Divergent thinking is characterized by the ability to generate a unique solution to a question that does not have one expected solution, such as "What is the best way to avoid talking about politics with my parents?"

Artificial intelligence (AI) helped clinicians to accelerate the design of diabetes prevention software, a new study finds.

Publishing online March 6 in the Journal of Medical Internet Research, the study examined the capabilities of a form of artificial intelligence called generative AI or GenAI, which predicts likely options for the next word in any sentence based on how billions of people used words in context on the internet.