Big Data
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Evaluating papers through patents
By tracking which scientific papers are cited by patents, researchers can quantify which studies contribute to real-world applications.
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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.
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Tapping EHRs to evaluate medical devices
Researchers used artificial intelligence and de-identified data from electronic health records to identify the safest types of hip implants.
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Real-world data in the clinic
In an interview, computational biologist Tina Hernandez-Boussard discusses analyzing the value of electronic health records as a source of information in the clinic.
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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.
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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.
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New biomedical data science chair named
Sylvia Plevritis, director of the Stanford Center for Cancer Systems Biology, has been tapped to lead the Department of Biomedical Data Science.
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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.
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Data science website launched
The online portal provides researchers with fast access to tools, data platforms, health-related databases and data-science experts.
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How AI could help create antibiotics
Researchers at Stanford have created an algorithm that, guided by previous research, lays out the DNA sequences most likely to align with antimicrobial properties.
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Algorithm success in screening for disease
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.
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