Artificial intelligence (AI) can scan a chest X-ray and diagnose if an abnormality is fluid in the lungs, an enlarged heart or cancer. But being right is not enough, said Ngan Le, a University of Arkansas assistant professor of computer science and computer engineering. We should understand how the computer makes its diagnosis, yet most AI systems are black boxes whose "thought process" even their creators cannot explain.

Today, nearly every American - 91% - owns a cellphone that can access the internet, according to the Pew Research Center. In 2011, only about one-third did. Another study finds they average 5 hours and 16 minutes a day staring at small screens.

With that rapid infiltration has come widespread concern about the negative psychological effects of being chronically online.

Diet and sleep, which are essential for human survival, are interrelated. However, recently, various services and mobile applications have been introduced for the self-management of health, allowing users to record and gather data on their eating and sleeping habits.

A study finds that 65.8% of adults surveyed had low trust in their health care system to use artificial intelligence responsibly and 57.7% had low trust in their health care systems to make sure an AI tool would not harm them.

The research letter was published in JAMA Network Open.

Psychologists warn that AI's perceived lack of human experience and genuine understanding may limit its acceptance to make higher-stakes moral decisions.

Artificial moral advisors (AMAs) are systems based on artificial intelligence (AI) that are starting to be designed to assist humans in making moral decisions based on established ethical theories, principles, or guidelines.

Coronary artery disease is the leading cause of death globally. One of the most common tools used to diagnose and monitor heart disease, myocardial perfusion imaging (MPI) by single photon emission computed tomography (SPECT), uses a radioactive tracer and special camera to provide detailed images of blood flow to the heart, helping doctors detect coronary artery disease and other cardiovascular abnormalities.

A groundbreaking study led by USC Assistant Professor of Computer Science Ruishan Liu has uncovered how specific genetic mutations influence cancer treatment outcomes - insights that could help doctors tailor treatments more effectively. The largest study of its kind, the research analyzed data for more than 78,000 cancer patients across 20 cancer types. Patients received immunotherapies, chemotherapies and targeted therapies.