Researchers at CZ Biohub SF and Stanford have developed unique fusion proteins that have broad therapeutic benefits for the treatment of infection by existing and future coronaviruses.
Researchers at Stanford have developed an innovation that will enhance the depth of the imaging capabilities for optical coherence tomography (OCT) imaging.
Stanford researchers in the Bao lab have developed a new fabrication method to create stretchable transistors for electronic skin. It produces a soft, stretchable material capable of sensing pressure, temperature, strain, and more.
Researchers at Stanford have developed a biodegradable device and platform carrier of biologics for promoting faster bone healing of large bone defects, fractures, and non-union.
Stanford researchers in the Bao Lab have developed damage-resistant stretchable electronic materials and devices that can be used in wearable electronics.
Stanford researchers have developed strain-sensitive, stretchable, and self-healable semiconducting film. The researchers have created a multiplexed sensory transistor array using this material which can detect strain distribution by surface deformation.
This technology is a category of colorful low-emissivity paints that form bilayer coatings, designed to enhance thermal insulation. Maintaining optimal thermal environments poses significant challenges for human comfort, energy efficiency, and sustainability.
Immune checkpoint blockade, a class of immunotherapy treatment which works by blocking inhibitory receptors on T cells to improve immune responses, has proven to be a remarkable clinical advance in the treatment of many diseases, particularly in cancer.
Knee osteoarthritis is the most common cause of musculoskeletal pain in adults, leading to limited mobility and various health issues. This breakthrough technology developed by Stanford researchers offers a promising solution.
Stanford researchers at the Snyder Lab have developed a novel software application, called the Metabolic Subphenotype Predictor, which predicts if a patient is insulin resistant through continuous glucose monitoring.
Stanford scientists have created a statistical framework for interpreting next generation sequencing data which obviates the need for sequence alignment references in the most common and fundamental problems in genomics.
This software is a transformative technology in the fields of AI and digital image processing, offering a breakthrough approach to convolution, particularly for large-scale images.