Researchers have successfully used two different machine learning algorithms to predict three common symptoms—sleep disturbance, anxiety and depression—experienced by cancer patients undergoing chemotherapy. The team's findings were published in PLOS One.

The team, led by Terisa P. Gabrielsen, PhD, assistant professor at Brigham Young University in Provo, Utah, successfully conducted structural and functional MRI scans of 37 children and adolescents between the ages of 7 and 17 years with autism—including 17 with less-developed language skills, according to research published online Jan. 2 in the journal Molecular Autism.

Using a technique that combines two MRI scans, researchers have developed an objective way to monitor concussions, according to a study published in NeuroImage: Clinical.

Researchers out of the University of Surrey in the U.K. created an artificial intelligence (AI) platform that can predict which cancer patients are most at risk for experiencing common symptoms associated with the disease.

Researchers from the University of Adelaide in Australia have developed a biopsy imaging needle that could help surgeons identify at-risk brain blood vessels during neurosurgery and avoid fatal cerebral bleeding, according to research published in the journal Science Advances.

Using x-ray diffraction, researchers identified patterned neurological changes during brain trauma based specifically on the force applied during the event. The findings may provide insight into what injuries correlate to specific types of damage.

Radiomic features extracted from CT images accurately distinguished small-cell lung cancer from benign nodules, according to a retrospective study published Dec. 18 in Radiology.

What does the brain of 3.67 million year old hominin known as Little Foot look like? Thanks to Micro-CT scans of the ancient fossil, researchers reconstructed its brain and are learning more about the organ’s early evolution.