AI could potentially become a valuable tool for neurologists, particularly when it comes to pinpointing the location of a stroke within the brain.
A cutting-edge study on canine cancer is using artificial intelligence to develop a novel strategy for early detection and prevention of diffuse large B-cell lymphoma in dogs.
A new generative artificial intelligence model developed by researchers at Stanford and McMaster Universities can create billions of new antibiotic molecules that are simple and affordable to produce in the lab.
A Linköping University study tested the app in primary care settings, demonstrating its ability to analyze images of skin lesions and detect melanoma with high precision.
An artificial intelligence (AI) tool created by a group of international researchers can identify breast cancer patients who may be more susceptible to side effects following surgery and radiation treatment.
AI-powered medical image analysis has advanced quickly in recent years. Currently, one of the biggest studies to date on lymphoma, or cancer of the lymphatic system, has been conducted with the use of AI-assisted image analysis. Scientists at Chalmers University of Technology in Sweden have created a computer model that, in 90% of cases, can accurately identify lymph node cancer symptoms.
Researchers from ETH Zurich and KUNO Klinik St. Hedwig in Regensburg have created an algorithm that offers a reliable and automatic method for identifying a specific kind of heart defect in newborn babies.
A novel AI language model is capable of identifying clinical symptoms in medical summaries and correlating them with brain tissue data from donors of the Netherlands Brain Bank.
When treating patients with early-stage lung cancer, physicians must decide whether to proceed with potentially beneficial but toxic therapies like chemotherapy, radiation, or immunotherapy to remove cancer and reduce the likelihood that it will spread to the brain, or whether to wait and see if lung surgery alone is adequate.
A ground-breaking research study has used AI to understand the genetic underpinning of the heart’s left ventricle, using three-dimensional images of the organ.
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