Topic List : Big Data
Examining value of predictive algorithms
Big-data analysts engaged in lively debate on machine learning strategies at a colloquium organized by the Division of Epidemiology.
Big data conference set for May 23-24
The two-day conference will feature leaders from academia, government and industry who harness immense data sets to more precisely predict, diagnose and treat disease.
Weight flux alters molecular profile
Stanford scientists have found links between changes in a person’s weight and shifts in their microbiome, immune system and cardiovascular system.
Predicting, preventing a second stroke
Using health records, Stanford researchers developed an algorithm for scoring the risk of a stroke patient experiencing a heart condition known as atrial fibrillation, a major risk factor for a second stroke.
Stanford launches health care trends report
The inaugural issue of the report shows that big data will transform health care in the future but that more needs to be done to train doctors and patients in data management and analysis.
Data sifting finds hidden gene partnerships
Targeting backup biological pathways often used by cancers can lead to more efficient drug development and less-toxic therapies. Stanford researchers have developed a new way to identify these pathways.
Integrating diverse data key to precision health
At the Big Data in Biomedicine Conference, Dean Lloyd Minor said a key goal is tackling population health and disease prevention, not just waiting for illness to strike.
Crowdsourcing autism data
Many areas across the globe have few autism experts, leading to delayed care for kids who live there. Stanford scientists have launched a crowdsourcing project to pinpoint such geographic gaps, and find ways to fill them.
Big data conference set for May 24-25
The two-day event at Stanford will focus on ways of using big data to advance precision health.
Team places third in data analysis contest
The Stanford-led team used the data to develop and validate a clinical decision score that identifies patients likely to experience benefits when undergoing intensive blood pressure treatment.