Stanford researchers at the Lee Lab have developed a method to understand whole-brain circuit mechanisms underlying neurological disease and its application to predict the outcome of therapeutic interventions.
Stanford researchers have developed an expanded catalog of compact transcription effector domains and fused them onto DNA binding domains to engineer synthetic transcription factors.
Active manipulation of light beams is required for a range of emerging optical technologies, including sensing, optical computing, virtual/augmented reality, dynamic holography, and computational imaging.
Stanford researchers in Zhenan Bao's Group have developed a nanomesh sensor printed directly on the hand that uses an AI-trained model to detect multiple movement types from a single sensor.
Stanford scientist has developed a computational method that extracts quantitative imaging features that reproducibly describe lesion phenotypes associated with treatment response and clinical outcomes in cancer.
Researchers at Stanford University have established a deep learning segmentation algorithm for non-contrast CT images to aid clinicians in decision making and improve the speed of symptom to treatment in acute ischemic stroke
Stanford researchers have developed a geometric deep learning based novel method to aid in identification and discovery of novel drug scaffolds as well as to optimize known scaffolds, as a means to combat the major challenge in drug discovery.
Stanford inventors have created a novel, interactive, highly scalable computational approach for representing dynamic brain activity as a network for use in clinical settings.
Stanford Researchers have discovered fluorinated acetal electrolytes for lithium metal batteries that demonstrate fast stabilization of lithium metal, compatibility with high-voltage cathodes, and low cell impedance.
Researchers at Stanford University and the CZ Biohub San Francisco have developed a strategy for retrieving and cloning antibody DNA from single cells within a pooled library of cells, enabling the rapid and low-cost cloning and expression of native human antibodies for functi
Stanford inventors have developed an information theoretic, seizure detection algorithm for electroencephalography (EEG) towards improving diagnosis, management, and treatment of patients with epilepsy.
Researchers from Stanford University have developed an algorithm for electromagnetic device prototyping which optimizes geometric shape based on physical functionality.
Stanford researchers have made a genetic mouse model to mimic the human LOXHD1 p.R1090Q mutation as a means to further investigate, understand and combat human Age-Related Hearing Loss (ARHL).
Researchers at Stanford have developed a methodology for deep learning-based image reconstruction by incorporating the physics or geometry priors of the imaging system with deep neural networks.