Researchers at Stanford have developed, for the first time, a component analysis algorithm that does not require any assumption on the data structure or data generation process to find out the important components or trends in data.
Stanford researchers have developed a statistical method to map tissue activity distribution and photon attenuation, correcting for attenuation in real time without a transmission scan, using Positron Emission Tomography.
This invention describes a new type of spreadsheet that instead of using arithmetic to relate data entries uses logical relationships. This fundamentally changes how the spreadsheet works and increases the user's ability to manipulate and extrapolate scenarios.
Researchers in Dr. Leonore Herzenberg's lab at Stanford University have developed a portfolio of data management, storage, and analysis technologies that may be used for large data sets.
This patented, automated data analytics tool sorts and analyzes large data sets by identifying and creating clusters of data. The algorithm intakes data and then groups them into clusters, groupings, or populations of data.