Stanford researchers have developed a versatile computational approach for easily visualizing and analyzing multidimensional molecular data, such as flow cytometry data.
A team of Stanford researchers has developed ReMatch, an efficient, data-driven DER (distributed energy resources) planning and decision support framework that accounts for a range of complexities to optimize energy resource planning.
Engineers in Prof. Khuri-Yakub's laboratory have developed ultrasonic methods for non-invasive flow meters to accurately measure flow rate, pressure, velocity and other parameters of gas or liquid traveling through a pipe.
The Zhenan Bao Research Group at Stanford University developed and manufactured a photo-curable, directly patternable, stretchable, and highly conductive polymer that is ideal for bioelectronic applications, and stretchable electronic devices.
Dr. Andrea Meredith and Dr. Richard Aldrich have generated a viable mouse knockout KCNMA1, the gene encodes the pore-forming subunit of the BK large conductance calcium-activated potassium channel (also called KCa1.1, SLO1, and MaxiK).
Engineers in Prof. Khuri-Yakub's laboratory have developed ultrasonic methods for non-invasive flow meters to accurately measure flow rate, pressure, velocity profile and other parameters of gas or liquid traveling through a pipe.
Stanford researchers have formulated a statistical model to determine the risk of breast cancer recurrence with unprecedented accuracy in women 5 – 20 years after initial diagnosis.
Stanford researchers have developed a stretchable, low power consumption, highly tunable resistive pressure sensor and organic electrochromic device (ECD). This electronic skin detects and distinguishes varying pressure through real-time visible color change.
Researchers in Prof. Juan Santiago's laboratory have developed a novel isotachophoresis (ITP) method to easily and seamlessly integrate various electrophoresis-based detection techniques with ITP preconcentration.
Stanford researchers at the Chichilnisky lab have patented an artificial retina framework for dynamic electrical stimulation to improve the performance of electronic visual implants.
Researchers in Prof. Michael McGehee's laboratory have developed a glass architecture that employs reversible metal electrodeposition for fast-switching smart windows with high contrast ratio and durable cycle life.
Stanford inventors have developed an information theoretic, seizure detection algorithm for electroencephalography (EEG) towards improving diagnosis, management, and treatment of patients with epilepsy.
Stanford scientists have developed PVSeg, a tool that automatically segments vascular and perivascular compartments in brain MRI data. This innovative tool can identify non-demented individuals at increased risk of developing dementia and accelerated brain atrophy.
When examining one or higher dimensional data, researchers frequently aim to identify individual subsets (clusters) of objects within the dataset. With high-dimensional data (>3 dimensions), the data become progressively more sparsly distributed in space.