Glioblastoma, the most aggressive malignant brain tumor in adults, is not an isolated lesion, but a disease that destabilizes ...

Efforts to improve cancer imaging technologies are crucial for diagnosing and treating the disease effectively. This transition from experimental to clinical use requires bridging the gap between ...

Discover how a new nanophotonic chip uses genetic markers and AI to detect diseases in minutes, potentially revolutionising ...

Researchers have developed a new AI system that improves lung cancer detection by analysing CT scans at both microscopic and ...

Lung cancer remains the leading cause of cancer-related deaths worldwide, accounting for nearly one in five cancer deaths – ...

Brain tumors pose a major challenge in neuro-oncology due to their high mortality rates and complex diagnosis. This review summarizes recent advances in using artificial intelligence (AI), ...

Abstract: Brain tumor poses significant challenges in diagnosis and treatment, necessitating accurate and timely detection methods. This study presents a deep learning approach for the detection of ...

Explore the advancements in minimal residual disease (MRD) assays, comparing tumor-informed and tumor-agnostic methods for enhanced cancer detection and treatment strategies. Minimal residual disease ...

Abstract: In the domain of modern healthcare research, decentralized learning based computer-aided diagnosis (CAD) is transformative for health monitoring and disease detection, particularly in ...

This important study describes a deep learning framework that analyzes single-cell RNA data to identify a tumor-agnostic gene signature associated with brain metastases. The identified signature ...