A machine learning model using routine lab data at 3 months postdiagnosis accurately predicted mortality or liver transplant risk in autoimmune hepatitis.
San José Spotlight on MSNOpinion
Kim: Expanding educational pathways for adult students with IDD
For most people, walking across a stage in a cap and gown signals the start of adulthood. However, for individuals with ...
18 小时on MSN
Learning to see after being born blind: Brain imaging study highlights infant adaptability
Some babies are born with early blindness due to dense bilateral congenital cataracts, requiring surgery to restore their ...
Role models can provide you (and your children) with someone to look up to, model good behaviors, and scaffold reasonable, ...
A brief period of blindness right after birth can have lasting effects on how the brain processes visual detail—but surprisingly, not on how it recognizes faces, objects, or words. The team studied ...
Children's Hospital Los Angeles researchers report that physical inactivity, routine checkups, binge drinking, lack of ...
7 天on MSN
I went to an adult sleepaway camp in my 40s. Surrounded by women in their 60s and 70s, I ...
I hoped my time at adult summer camp would help me cope with complicated feelings about midlife. I met older women who ...
Machine learning predicted ASD using sex-specific prenatal/perinatal factors: pregestational BMI, socioeconomic status, maternal age, and more.
As lessons are in motion and routines become more familiar, the demands of professional learning can take a back seat to the ...
The gpt-oss models are being tested for use on sensitive military computers. But some defense insiders say that OpenAI is ...
4 天on MSN
Machine-learning model could save costs, improve liver transplants, Stanford-led research shows
A machine learning-based model predicts how long it will take an organ donor to die after removing life support, aiding surgeons in deciding whether organs can be successfully transplanted.
The WEA was founded in 1903 on the lofty principles of empowering working people to improve their own lives, participate more ...
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