As cancer cases have increased worldwide, the disease has become more complex, presenting challenges to scientific advances in diagnosis and treatment. In this context, artificial intelligence (AI) has emerged as a valuable tool for predicting and detecting cases.
Recently, researchers from Prof. Eran Segal’s laboratory at the Weizmann Institute of Science have harnessed artificial intelligence to create a personalized “digital twin” that allows them to detect a risk of developing diseases, initiate preventive treatment and even run simulations to predict which treatment will be most effective.
“Precision medicine” has become increasingly popular in the last decade as an avenue for cancer therapy, where treatment strategies are tailored to a specific patient based on the unique characteristics of their disease and their personal background.
Innovative software platform leverages artificial intelligence to personalize therapy decisions and improve clinical outcomes for prostate cancer patients.
AI-Powered 3D Surgical Planning Tool Advances Precision Breast Cancer Surgery with Latest Regulatory Milestone
An artificial intelligence (AI) model developed by Mayo Clinic and Ultromics, Ltd., an AI echocardiography company based in Oxford, England, is highly accurate in screening for cardiac amyloidosis, a rare and progressive type of heart failure, according to a new study. The model is the first and only AI tool of its kind.
A new study by researchers at the Icahn School of Medicine at Mount Sinai, Memorial Sloan Kettering Cancer Center, and collaborators, suggests that artificial intelligence (AI) could significantly improve how doctors determine the best treatment for cancer patients—by enhancing how tumor samples are analyzed in the lab.
Researchers from DZNE, Ludwig-Maximilians-Universität München (LMU), and Technical University of Munich (TUM) have found that the enzyme “gamma-secretase”—implicated in Alzheimer’s disease and cancer—selects its reaction partners according to a complex scheme of molecular features.
It can take as long as 18 months for children with suspected autism spectrum or attention-deficit-hyperactivity disorders to get a diagnostic appointment with a psychiatrist in Indiana. But an interdisciplinary team led by an Indiana University researcher has developed a new diagnostic approach using artificial intelligence that could speed up and improve the detection of neurodivergent disorders.
A combination of high-resolution imaging and machine learning, also known as artificial intelligence (AI), can track cells damaged from injury, aging, or disease, and that no longer grow and reproduce normally, a new study shows.