Using microbubbles and ultrasound, researchers have created a cancer treatment that kills tumor cells and recruits immune cells to the tumor.
Stanford researchers are devising new ways to tackle cancer through better, more sophisticated diagnostics and treatments.
Stanford Medicine will be the first to use a new technology that aims to heighten precision of radiation therapy in cancer patients.
Stanford bioengineer Manu Prakash and his team have transformed full-face snorkel masks into reusable personal protective equipment for health care workers.
Researchers are using artificial intelligence to detect abnormalities in the heart through an algorithm that assesses the rate that a heart pumps blood.
Scientists create a new 3D lung cancer model to better reveal the drivers of cancer, and in doing so, find a new gene that may be a possible drug target.
Fathers with chronic illnesses may have a higher risk of having a child who is preterm, has low birth weight, or needs NICU care.
Two scientists, who are married, team up in the lab to apply concepts from theoretical genetics to better understand health care fragmentation.
A team led by Howard Chang has contributed key technology to enable new experimental cancer therapy that uses CRISPR to edit immune cells.
Lasers, heat maps, fluorescence and real-time imaging help guide surgeons who are developing new ways to enhance precision brain surgery.
Scientists develop a technology to find "jumping genes," a type of genetic element that may contribute to antibiotic resistance.
Scientists at Stanford have developed a new PET scan tracer that flags both pancreatic cancer and a lung disease known as idiopathic pulmonary fibrosis.
A new approach to biobanking that streamlines sample storage and processing is enabling Stanford scientists and doctors to pursue new lines of research.
Scientists have used CRISPR-Cas9 screens to reveal more about how the bacteria behind Legionnaire's disease infects humans.
Researchers at Stanford are mining millions of de-identified patient records using machine learning to determine long-term safety of medical devices.
Researchers at Stanford have devised an algorithm that predicts how likely a diagnostic test, when repeated, will yield useful information.
