Jianrui Wu

Papers

Total Citations

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About

Jianrui Wu’s research lies at the intersection of medical imaging, deep learning, and intelligent diagnostic systems, with a particular focus on cancer diagnosis using convolutional neural networks (CNNs). His most-cited work, a comprehensive thesis on CNN-based cancer diagnosis systems, systematically surveys the integration of miniature diagnostic robots, CNN-SVM-FCN (CSF) architectures, and expert systems. In this study, Wu critically analyzes key technologies and recent advances in image processing methods for automated cancer detection, highlighting how these systems enhance diagnostic accuracy and efficiency. Although his citation count is modest, his work provides a valuable synthesis of emerging trends in miniature robotics and deep learning for medical applications, offering a roadmap for future research in non-invasive, AI-driven diagnostics. Wu’s contributions are particularly notable for bridging the gap between robotic hardware and algorithmic innovation, demonstrating how compact diagnostic platforms can leverage sophisticated neural networks for real-time cancer screening. His survey remains a useful reference for researchers exploring the convergence of robotics, computer vision, and clinical decision support systems.