A new system combining artificial intelligence with human knowledge promises faster and more accurate cancer diagnosis.
By adding infrared capability to the ubiquitous, standard optical microscope, researchers hope to bring cancer diagnosis into the digital era.
Researchers from Thomas Jefferson University use machine learning on ultrasound images of thyroid nodules to predict risk of malignancy.
An AI tool identified breast cancer with approximately 90 percent accuracy when combined with analysis by radiologists.
Researchers are pairing a nanoscale imaging technique with virtual reality technology to create a method that allows researchers to “step inside” their biological data.
Medical software that overlays tumour information from MRI scans onto ultrasound images can help guide surgeons conducting biopsies and improve prostate cancer detection.
The Murab project is developing technology that will make it possible to take more accurate biopsies and diagnose cancer and other illnesses faster.