Cerebral palsy is among the leading causes of childhood disability worldwide. According to the World Health Organization (WHO), it affects an estimated 2β3 out of every 1000 live births.
Early diagnosis is critical for improving outcomes and ensuring effective rehabilitation. Yet detecting cerebral palsy within the first 12 months of life remains a difficult task in modern medicine. An infantβs brain develops at a remarkable speed, and traditional MRI scans are difficult to interpret due to the low contrast between gray and white matter β the tissues that form the cerebral cortex and support higher brain functions.
An MRI testing procedure typically takes 20β40 minutes, but interpreting the images and preparing a report can take an experienced radiologist anywhere from several hours to several days. For longitudinal monitoring, workload and turnaround times increase substantially as clinicians may need to review large volumes of follow-up scans.
"The worldβs first AI solution for assessing brain development in infants under 12 months of age. The neural network automates MRI analysis, cutting processing time from several days to just minutes."
Do you understand how big of a difference this is from days to minutes!!
This is what AI is supposed to do, not p0rn or chatbots but curing diseases and discovering signs of central nervous system disorders in infants.
@theospress
