Scientists created an algorithm that analyzes a cancer biopsy and pairs spatial information with gene expression to better understand the disease.
Tracking brainwave patterns and symptoms in patients with depression, researchers used artificial intelligence to predict best treatment options.
Ethical and legal issues accompany the potential benefits of using computer vision-based ambient intelligence in health care.
A Stanford biomedical data scientist discusses how computational modeling of big data could help improve personalized chemotherapy selection in the future.
Through genetic tests and databases of symptoms, doctors in a network of clinical centers help families determine what is affecting their children's health.
Researchers at Stanford are mining millions of de-identified patient records using machine learning to determine long-term safety of medical devices.
At a recent talk on campus, Amy Abernethy, an FDA principal deputy commissioner, discussed her career and her work to facilitate clinical advances.
At day two of the Big Data in Precision Health conference, DJ Patil shared how he discovered data science and was hired by the Obama administration.
At the Big Data in Precision Health conference, clinicians discussed using patient health data to enhance primary care through the Humanwide pilot project.
Speakers at Stanford's Big Data in Precision Health conference discuss how their work with big data impacts and informs sleep research.
Stanford Medicine's Big Data in Precision Health conference unites people who create, study and use information from big data to improve health.
Before the Big Data in Precision Health conference, Don Rucker, the national coordinator for health IT, discusses the government's role in health data.
Stanford scientists and their collaborators tracked the health of over 100 people for several years, flagging early signs of disease.
Ahead of the Big Data in Precision Health conference, Emma Huang from Johnson & Johnson Innovations discusses collaborations between industry and academia.
Maja Matarić, a robiticist at the University of Southern California, plans to speak about socially assistive robotics at Big Data in Precision Health.
By scouting for a particular immune cell in the blood, scientists can tell which patients with a lung-scarring disease are at higher risk for death.
