New advances in artificial intelligence (AI) could streamline the process of diagnosing breast cancer. Traditional methods of mitotic counting, which assess cellular division, can be inefficient and prone to errors. With AI, this process can be standardized, reducing variability and inconsistency. However, effective implementation of these AI tools requires high-quality, diverse training data, ongoing validation, and direct feedback from pathologists. Despite the challenges, AI integration presents a promising future for breast cancer diagnostics and the broader spectrum of medical diagnostics.
New Malware Loaders Use Call Stack Spoofing, GitHub C2, and .NET Reactor for Stealth
An updated version of a malware loader, known as Hijack Loader, has been discovered with new features aimed at evading detection and maintaining persistence. The
