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.
Stanford scientists have developed a device to distinguish the molecule-specific signatures of diseased exosomes isolated from glioblastoma patients. The device is portable, disposable, and low-cost, enabling point-of-care assessment of disease.
Stanford researchers have developed a predictive biomarker for hepatocellular carcinoma (HCC) recurrence post-treatment that provides key spatial distribution information about cell interaction.
Stanford researchers in the Quake Lab have patented methods to apply DNA sequencing to analyze the variable regions of the antibody heavy chain in order to profile immune diversity in zebrafish.
Stanford researchers have created a new strategy for collecting and integrating human microbiome, multi-omics, and immune cell activation data that reveals new insights into the roles of different bacterial strains in human health.
Researchers at Stanford have developed a novel deep-learning-based tool called CytoTRACE2 that interprets single-cell RNA sequencing (scRNA-seq) to enable the discovery of regenerative cells across all tissue types and novel targets in cancer and other diseases.
Early detection of ovarian cancer is crucial, with a 5-year survival rate exceeding 90%. Once this early window has been missed, the 5-year survival rate precipitously drops below 50%.
Stanford researchers in Dr. Mahajan's laboratory have discovered biomarkers to differentiate between infectious (endophthalmitis) and non-infectious uveitis; and, to accurately categorize the types of infectious uveitis.
The cost of DNA and RNA sequencing have decreased in recent years to aid effective research and clinical applications; however, the labor time and throughput of preparing DNA and RNA sequencing libraries remains a challenge.
Stanford researchers have developed easyBAT, a simplified solution integrating a microfluidic sample preparation device with a fully automated analysis pipeline for rapid, accurate and accessible solution for food allergy diagnosis at the point-of-care.
Stanford researchers have developed a new, low-cost method for tumor methylation profiling that enables tumor classification even from low amounts of fragmented DNA characteristic of liquid biopsies.
Stanford inventors have developed a novel diagnostic tool that identifies distinct immune signatures in the peripheral blood of osteoarthritis patients using mass cytometry (CyTOF) and applied machine learning.