Abstract: Brain tumor detection is a vital and challenging task in medical diagnosis, requiring highly precise and efficient methods to improve patient treatment outcomes. Traditional approaches rely ...

As the state investigates a possible cancer cluster at a high school, many Herald readers have asked whatever happened with the potential tumor cluster at a local hospital. Seven current and former ...

A major clinical trial involving 50 hospital intensive care units (ICUs) throughout New Zealand and Australia will test if artificial intelligence (AI) can help doctors save more patients’ lives who ...

At least 12 of my colleagues boarded planes to the American Society of Clinical Oncology conference in Chicago last week to hear Charles Swanton of the Francis Crick Institute in London share results ...

A brain tumor can strike anyone at any age, impacting a person’s very essence — everything from cognition and personality to movement and speech — if it’s fast-growing and aggressive. It can be the ...

A new McGill-led study reveals that digital brain exercises can rejuvenate aging brain systems responsible for learning and memory. Older adults using BrainHQ for 10 weeks showed restored cholinergic ...

Brain cancer is one of the deadliest diseases — and early detection is crucial for better outcomes. There are obvious symptoms like sudden, severe headaches and dizziness, while subtle signs such as ...

Each May, Brain Cancer Awareness Month offers an opportunity to spotlight one of oncology’s most complex and underserved areas: brain and other central nervous system (CNS) cancers. While progress has ...

Machine learning often feels difficult at the beginning, especially when everything stays theoretical. That changes once you start working on real projects and see how models are actually used. The ...

Abstract: Medical imaging is very important for diagnosing and treating patients in healthcare. Oncologists examine images to identify the distinct features of malignant diseases, formulate treatment ...

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), the most common ...