Researchers in Prof. Karl Deisseroth's laboratory have used optogenetic tools to develop an animal model for social dysfunction by precisely targeting defined neural circuit elements.
Researchers in Prof. Karl Deisseroth's laboratory have used optogenetic tools to develop an animal model for anxiety by precisely identifying, creating, resolving, and targeting defined neural circuit elements.
Researchers in Prof. Karl Deisseroth's laboratory have developed a portfolio of microbial opsin proteins that can be used for precise and modular photosensitization components that enable optical control of specific cellular processes.
Researchers in Dr. Karl Deisseroth's lab have developed a selective approach to treat anxiety. Anxiety is characterized by several features that are coordinately regulated by diverse neuronal system outputs.
Researchers in Prof. Karl Diesseroth's laboratory have discovered a Dopamine receptor type 2 specific promoter (D2SP) that can be used to transfect, identify and isolate Dopamine R2 (D2R)-expressing cells.
Stanford researchers at the Taylor Lab have developed software subroutines that can be used together with the open source software system Simvascular to improve the simulation of blood flow in modeling coronary arteries.
Developed at the Taylor Lab, Simvascular is an open source software package encompassing an entire cardiovascular modeling and simulation pipeline from image segmentation, three-dimensional (3D) solid modeling, and mesh generation, to
Stanford researchers have developed an algorithm using deep learning architectures to predict cardiac function (ejection fraction) and trace the endocardium of the left ventricle from ultrasound echocardiogram videos.
Researchers in the Fan group have developed a method for epitaxial growth of double heterojunction semiconductor diodes capable of suppressing parasitic non-radiative recombination effects.
The Bronte-Stewart lab has designed an algorithm for calculating neural activity burst duration to better manage closed loop deep brain stimulation in patients with Parkinson's disease.
Stanford researchers have created a portable, wearable device for long-term nystagmus tracking to better diagnose episodic vertigo. Current methods utilize head goggles in video nystagmography to monitor eye movement while the patient is in a clinical setting.
Stanford researchers have developed CheXpert which can reduce noise and identify several pathologies on x-rays with very high accuracy via machine learning. CheXpert can read photos of x-rays from a mobile phone and is robust to noise.