Big Data

By tracking which scientific papers are cited by patents, researchers can quantify which studies contribute to real-world applications.

The report documents key trends steering the industry’s future, including a maturing digital health market, new health laws opening patient access to data, and artificial intelligence gaining regulatory traction for medical use.

Researchers used artificial intelligence and de-identified data from electronic health records to identify the safest types of hip implants.

In an interview, computational biologist Tina Hernandez-Boussard discusses analyzing the value of electronic health records as a source of information in the clinic.

Invisible sensors, machine learning for disease diagnoses, big data in the clinic and more took the stage as topics at this year’s Big Data in Precision Health Conference.

Years-long tracking of individuals’ biology helped define what it meant for them to be healthy and showed how changes from the norm could signal disease, a Stanford-led study reports.

Sylvia Plevritis, director of the Stanford Center for Cancer Systems Biology, has been tapped to lead the Department of Biomedical Data Science.

Stanford scientists and their collaborators have devised an algorithm to predict the risk of a disease that, untreated, can lead to heart attack or stroke.

The online portal provides researchers with fast access to tools, data platforms, health-related databases and data-science experts.

Researchers at Stanford have created an algorithm that, guided by previous research, lays out the DNA sequences most likely to align with antimicrobial properties.

In a matter of seconds, a new algorithm read chest X-rays for 14 pathologies, performing as well as radiologists in most cases, a Stanford-led study says.