Topic List : Precision Health
Stanford Medicine unveils 2020 Health Trends Report
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.
New Stanford Hospital: The future is here
This issue contains stories behind the development of the new hospital as well as articles about the work being done there.
E.H.R. event tackles privacy, workload
Speakers at Stanford Medicine’s second symposium on electronic health records discussed ways to increase patients’ access to data while maintaining security and decreasing the documentation burden for physicians.
Cancer-drug combo extends life about 9 months
The results of a phase-3 clinical trial led by a Stanford researcher showed that two targeted treatments can extend the lifespan and delay the need for chemotherapy in women with a common type of metastatic breast cancer.
Possible drug target for cardiomyopathy
Stanford researchers have uncovered how a genetic mutation contributes to a heart disease known as familial dilated cardiomyopathy. Existing drugs correct the defect in heart cells grown in a petri dish, suggesting a new therapeutic target.
Dynamic predictions help patients
Using in-game win probability techniques, Stanford researchers devised a way to better predict a cancer patient’s outcome at any point during treatment. The approach could also inform treatment decisions.
Big data, the patient and the provider
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.
Pilot program for precision health
A Stanford clinical trial that provided proactive, personalized care to participants detected overlooked health conditions and risks.
Revealing health through big data
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.
Identifying familial hypercholesterolemia
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.