Machine learning could help identify infants at risk of jaundice
Machine learning is a form of AI that may be able to help doctors predict jaundice risk.
Machine learning is a form of AI that may be able to help doctors predict jaundice risk.
A recent study found no cases of HDFN or autoimmune hemolytic anemia in women or their children despite the presence of these antibodies.
Extending delivery at or beyond 34 weeks and performing an IUT around that time could be beneficial in pregnancies complicated with HDFN.
The patient was found to have a partial D variant called DBT that is difficult to detect with standard serologic testing.
Standardized guidelines regarding Rhesus D practices among women undergoing first trimester abortions should be fine tuned.
Parents of children with HDFN who use online forums are vulnerable to misleading and often incorrect information, a recent study found.
A recently published study highlighted how late anemia caused hemolytic disease of the fetus and newborn should be treated.
Newborns with HDFN face a greater risk of necrotizing enterocolitis, a dangerous intestinal condition, especially after certain treatments.
A new case study emphasizes the importance of accurately identifying rare blood antibodies in pregnancy for the management of HDFN.
A recent review outlines the current recommendations for treating complications of HDFN, including jaundice, anemia and iron overload.