Topic List : Precision Health
Blood biomarkers predict labor onset
About three weeks before delivery, a pregnant woman’s body shifts into a pre-labor phase characterized by changes in immune, hormonal and blood-clotting signals.
Using population data to prevent disease in individuals
In a virtual chat, the School of Medicine’s dean and the chair of epidemiology and population health discussed how the seemingly distinct fields can intersect to boost health equity.
Digital health tools aid in weight loss
Digital health tools, such as diet-tracking apps, increase engagement in weight loss programs, helping users shed pounds, according to a new study.
Study reveals molecular effects of exercise
Researchers at the School of Medicine have shown how exercise changes the body at a molecular level and have identified blood markers of fitness.
Wearable devices for predicting illness?
Researchers from Stanford Medicine and their collaborators aim to predict the onset of viral infection through data provided by wearable technology. What they need now are participants.
Smart toilet can flag disease
A disease-detecting “precision health” toilet can sense multiple signs of illness through automated urine and stool analysis, a new Stanford study reports.
Stanford's COVID-19 testing provided for Bay Area hospitals
Stanford’s test for COVID-19, caused by the novel coronavirus, is rapidly expanding capacity to serve patients in the Bay Area and beyond. Researchers hope to soon be able to process more than 1,000 tests per day.
Potential treatment for lingering Lyme disease
Screening thousands of drugs, Stanford scientists determined that in mice, azlocillin, an antibiotic approved by the Food and Drug Administration, eliminated the bacteria that causes Lyme disease.
Stanford-led teams nab top clinical research prizes
Winning studies were chosen by members of the Clinical Research Forum, a nonprofit foundation that promotes the understanding of clinical research and its impact on health and health care.
Brain waves can determine drug response
Researchers used electroencephalography and artificial intelligence to identify individuals who would likely respond to sertraline, the antidepressant marketed as Zoloft.