Mijin Kim and Daniel Heller of the Nanomedicine Lab at Memorial Sloan Kettering Cancer Center have developed an array of carbon nanotube sensors that can “sniff” cancer using AI. The human nose can detect a trillion different scents,...
CompCyst is a proof-of-concept study, led by Anne Marie Lennon at Johns Hopkins, which uses AI to more accurately determine which pancreatic cysts will become cancerous. The test evaluates molecular and clinical markers in cyst fluids,...
MIT CSAIL professor Regina Barzilayand Harvard/MGH professor Constance Lehman have developed a deep learning model that can predict breast cancer, from a mammogram, up to five years in the future. The model learned subtle breast tissue patterns that...
Luis Parada and Sloan Kettering colleagues are focusing on cancer stem cells as a new approach to glioblastoma. Like normal stem cells, cancer stem cells have the ability to rebuild a tumor, even after most...
Dina Katabiand MIT CSAIL colleagues have developed ReMix, which uses lo power wireless signals to pinponit the location of implants in the body. The tiny implants could be used as tracking devices on shifting tumors...
Pratik Shah, Gregory Yauney, and MIT Media Lab researchers have developed an AI model that could make glioblastoma chemotherapy regimens less toxic but still effective. It analyzes current regimens and iteratively adjusts doses to...
MIT’s Hadley Sikes has developed a sensor that determines whether cancer cells respond to a particular type of chemotherapy by detecting hydrogen peroxide inside human cells. The technology could help identify new cancer drugs that...