Latest AI and machine learning research in colon cancer for healthcare professionals.
Accurate polyp segmentation from colonoscopy images is critical for colorectal cancer prevention, ye...
Medical image analysis relies on accurate segmentation, and benefits from controllable synthesis (of...
Source Free Unsupervised Domain Adaptation (SFUDA) is critical for deploying deep learning models ac...
Accurate polyp segmentation is essential for early colorectal cancer detection, yet achieving reliab...
Colonic polyps are well-recognized precursors to colorectal cancer (CRC), typically detected during ...
Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy characterized by profound molecu...
Differences in microbiome composition profoundly influence drug response, yet methods to model the m...
Video polyp segmentation (VPS) is an important task in computer-aided colonoscopy, as it helps docto...
Colonoscopy video generation delivers dynamic, information-rich data critical for diagnosing intesti...
Monocular depth estimation (MDE) for colonoscopy is hampered by the domain gap between simulated and...
Cancer driver mutations shape the tumor microenvironment (TME), yet whether TME composition alone ca...
We introduce a workflow that integrates BioEmu-generated conformational ensemble with physics-based ...
Monocular depth and pose estimation play an important role in the development of colonoscopy-assiste...
Accurate grasping point prediction is a key challenge for autonomous tissue manipulation in minimall...
Background: Pancreatic ductal adenocarcinoma is one of the most aggressive and lethal malignancies o...
Pancreatic ductal adenocarcinoma remains one of the most lethal malignancies, largely due to the abs...
Colorectal cancer (CRC) remains a significant cause of cancer-related mortality, despite the widespr...
Deep learning has the potential to improve colonoscopy by enabling 3D reconstruction of the colon, p...
Abstract Background: Colorectal cancer (CRC) is a leading cause of cancer mortality. While early det...
This study investigates the efficacy of transformer-based deep learning architectures-specifically, ...
Digitizing large histopathology archives requires processing millions of scanned whole slide images ...