Researchers in Prof. Yi Cui's laboratory have used a novel electrospinning process to fabricate a unique, transparent, highly conductive metal nanofiber material that could be used to replace indium tin oxide (ITO) in transparent electrodes.
Researchers in Prof. Steven Chu's laboratory have developed a fundamentally new method of acoustic imaging to improve resolution of ultrasound diagnostics.
Stanford researchers in the Dai Lab have developed the first ultra-bright cubic-phase erbium-based rare-earth nanoparticles (α-ErNPs) with down-shifting luminescence at ~ 1600 nm for in vivo NIR-IIb (1500-1700 nm) imaging with deep penetration and high clarity.
Researchers at Stanford have developed a targeted delivery system using carbon nanotubes to specifically deliver cardiovascular drugs to treat atherosclerosis. A feature of atherosclerotic plaque is the accumulation of apoptotic cells.
Stanford researchers at the Camarillo Lab have designed a real-time screening device system for predicting risk of concussion resulting from head impacts.
Engineers at the Khuri-Yakub Group have designed a non-surgical alternative for treating epilepsy using ultrasonic technology which can detect, localize, and suppress epileptic seizures in epileptic patients.
Ultrasound complements mammography as an imaging modality for breast cancer detection, especially in patients with dense breast tissue, but its utility is limited by low diagnostic accuracy.
Heart failure has a prognosis worse than most cancers and affects over five million people in the United States alone. Although some medications for heart failure exist, many patients develop side effects or do not respond favorably to existing medications.
Researchers at Stanford are developing methods of using arginine vasopressin (AVP) to improve social abilities of children with autism spectrum disorder (ASD). Autism is a neurodevelopmental disorder characterized by social impairments (e.g.
Researchers at Stanford have developed methods of using CRISPR/Cas9-mediated genome editing to treat patients with EGFR-mutant non-small-cell lung cancer (NSCLC). Approximately 85% of lung cancers are NSCLC.
Stanford researchers have developed a new machine learning method for extracting gait parameters, such as cadence, step length, peak knee flexion, and Gait Deviation Index (GDI), from a single video.
Stanford researchers have proposed a novel, in vivo, real-time epifluorescence imaging method in the second near-infrared region using single-walled carbon nanotubes (SWNTs).
Dr. Manish Saggar at Stanford University has developed a new method to visualize and quantify transitions in brain activity, which may be used as a diagnostic tool for mental illness.