
AI taps human wisdom for better cancer diagnosis
A new system combining artificial intelligence with human knowledge promises faster and more accurate cancer diagnosis.
A new system combining artificial intelligence with human knowledge promises faster and more accurate cancer diagnosis.
Researchers develop an AI system that effectively evaluates endoscopic mucosal findings from patients with ulcerative colitis without the need for biopsy collection.
By adding infrared capability to the ubiquitous, standard optical microscope, researchers hope to bring cancer diagnosis into the digital era.
Various prototypes of 3D-printed biopsy robots could alleviate the suffering of patients and make breast cancer testing more accurate and efficient.
Researchers have developed a method based on artificial intelligence for histopathological diagnosis and grading of prostate cancer.
Researchers have used a chip-based sensor with an integrated laser to detect very low levels of a cancer protein biomarker in a urine sample.
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.
A student is aiming to 3D print life-sized breast cancer tumours, with her research targeting faster, more effective treatment for women with the disease.