
Breast cancer-on-a-chip tests immunotherapy drugs
Researchers have successfully designed and tested a system for rapid testing of large numbers of potential immunotherapy drugs.
Researchers have successfully designed and tested a system for rapid testing of large numbers of potential immunotherapy drugs.
Research has shown how microbubbles carrying powerful cancer drugs can be guided to the site of a tumour using antibodies.
Researchers are developing solutions designed to enable the analysis of breath gas to assist with the diagnosis of disease.
A dual-organ system enables the measurement of cardiac toxicity arising from breast cancer chemotherapy.
Researchers have developed an robotic system to enhance the safety and efficacy of endoscopic submucosal dissection (ESD) for the treatment of gastrointestinal cancer.
The new 3D hydrogels provide high rates of cell proliferation, as they mimic lymph nodes, where T-cells reproduce in vivo.
Scientists have paired 3D-printed, living human brain vasculature with advanced computational flow simulations to better understand tumor cell attachment to blood vessels.
Robotic surgery for patients with early stage, oropharyngeal squamous cell cancer is associated with improved health outcomes, including better long-term survival.
Researchers report innovative use of machine learning to help understand the interplay of genetic and other breast cancer risk factors.
Myriad Genetics, Inc. announced a new collaboration with OptraHEALTH to implement a cognitive chatbot named Gene to provide genetic and financial assistance information to prospective patients.
Researchers have developed a machine learning model that can predict chemotherapy-associated nephrotoxicity.
Nanoengineers plan to develop an immunotherapy for ovarian cancer using 3D-bioprinted plant virus nanoparticles.
Scientists at Purdue University have developed a skin patch that can deliver chemotherapy into melanoma tumors in an effective and painless way.
Improving the prediction of survival indicators in patients with breast cancer using tools from artificial intelligence and probabilistic modelling is the aim of ModGraProDep.
A new AI approach classifies a common type of brain tumour into low or high grades with almost 98% accuracy, researchers report.
Computer scientists working with pathologists have trained an AI tool to determine which patients with lung cancer have a higher risk of their disease coming back after treatment.
An AI model for automated classification of colorectal polyps could benefit cancer screening programs by improving efficiency, reproducibility, and accuracy.
Commercially available app-based technology now makes early detection of lymphedema easier, allowing for proactive treatment.
Using a robot to treat brain aneurysms is feasible and could allow for improved precision when placing stents, coils and other devices.
Researcher have developed a computer method that uses MRI and machine learning to rapidly forecast genetic mutations in glioma tumors,
A novel method of combining advanced optical imaging with an artificial intelligence algorithm produces accurate, real-time intraoperative diagnosis of brain tumors.
Using a computer algorithm, scientists at Uppsala University have identified a promising new treatment for neuroblastoma.
A computer algorithm has been shown to be as effective as human radiologists in spotting breast cancer from x-ray images.
Artificial intelligence can detect one of the most common forms of blood cancer—acute myeloid leukemia (AML)—with high reliability.
An AI has successfully found features in pathology images from human cancer patients, without annotation, that could be understood by human doctors.
Researchers have developed a new algorithm that enables automated detection of metastases at the level of single disseminated cancer cells in whole mice.
A software tool uses artificial intelligence to recognize cancer cells from digital pathology images — giving clinicians a powerful way of predicting patient outcomes.
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.
An AI platform can analyze genomic data extremely quickly, picking out key patterns to classify different types of colorectal tumors and improve the drug discovery process.