Lauren Silverman is the Health, Science & Technology reporter/blogger at KERA News. She received a Peabody Award for her contribution to NPR’s Ebola coverage in 2014 and has won several regional awards; an honorable mention for Edward R. Murrow awards, as well as the Texas Veterans Commission’s Excellence in Media Awards in the radio category.
Lauren Silverman
From this contributor
U.S. travel ban threatens to worsen nation’s doctor shortage
The U.S. medical system depends on doctors from other countries, who often work in areas in desperate need of providers.
U.S. travel ban threatens to worsen nation’s doctor shortage
Women aren’t taking first place in top medical journals
There’s a gender gap in who gets top billing on medical studies published in several of the most prestigious research journals.
Women aren’t taking first place in top medical journals
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The term ‘model organism’ should be reserved for biological systems
By referring to artificial neural networks as model organisms, we run the risk of distorting funding priorities and disregard the explanatory power of a shared evolutionary history across biological organisms.
The term ‘model organism’ should be reserved for biological systems
By referring to artificial neural networks as model organisms, we run the risk of distorting funding priorities and disregard the explanatory power of a shared evolutionary history across biological organisms.
New phase of BRAIN Initiative spawns basal ganglia ‘parts list’
With a standardized cell naming system and infrastructure for data collection and analysis, the basal ganglia project sets the stage for a whole-brain primate atlas.
New phase of BRAIN Initiative spawns basal ganglia ‘parts list’
With a standardized cell naming system and infrastructure for data collection and analysis, the basal ganglia project sets the stage for a whole-brain primate atlas.
Machine-learning model spots autism-linked variants that scramble splicing
The model provides a way to investigate genetic variation in regions of the genome whose functions have been difficult to interpret.
Machine-learning model spots autism-linked variants that scramble splicing
The model provides a way to investigate genetic variation in regions of the genome whose functions have been difficult to interpret.