An artificial intelligence (AI) tool helps doctors predict the cancer risk in lung nodules seen on CT, according to a new study published in the journal Radiology.

Pulmonary nodules appear as small spots on the lungs on chest imaging. They have become a much more common finding as CT has gained favor over X-rays for chest imaging.

Researchers at the University of California San Diego have developed a smartphone app that could allow people to screen for Alzheimer's disease, ADHD and other neurological diseases and disorders - by recording closeups of their eye.

The app uses a near-infrared camera, which is built into newer smartphones for facial recognition, along with a regular selfie camera to track how a person’s pupil changes in size.

Researchers at Karolinska Institutet in Sweden have studied how the screen habits of US children correlates with how their cognitive abilities develop over time. They found that the children who spent an above-average time playing video games increased their intelligence more than the average, while TV watching or social media had neither a positive nor a negative effect. The results are published in the journal Scientific Reports.

A new computer-aided diagnostic tool developed by KAUST (King Abdullah University of Science & Technologym, Saudi Arabia) scientists could help overcome some of the challenges of monitoring lung health following viral infection.

Like other respiratory illnesses, COVID-19 can cause lasting harm to the lungs, but doctors have struggled to visualize this damage.

An innovative mobile phone application was found to be as good as expert gastroenterologists at characterizing stool specimens, according to a study by Cedars-Sinai. The artificial intelligence (AI) used in the smartphone app also outperformed reports by patients describing their stool specimens.

Compared with computers, the human brain is incredibly energy efficient. Scientists are therefore drawing on how the brain and its interconnected neurons function for inspiration in designing innovative computing technologies. They foresee that these brain-​inspired computing systems, will be more energy efficient than conventional ones, as well as better at performing machine-​learning tasks.

Using an artificial intelligence (AI) tool that emulates how humans visualize and is trained to recognize and classify images, investigators constructed a model that predicts the postoperative recurrence of Crohn disease with high accuracy by evaluating histological images. The AI tool also revealed previously unrecognized differences in adipose cells and significant differences in the extent of mast cell infiltration in the subserosa, or outer lining of the intestine, comparing patients with and without disease recurrence.