Zhiqi Wu

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About

Zhiqi Wu is a researcher whose work sits at the intersection of medical imaging, artificial intelligence, and robotics. Their key research areas include convolutional neural network (CNN)-based diagnostic systems, miniature diagnostic robots, and expert systems for medical applications. Wu’s major contribution is a comprehensive survey that systematically integrates CNN, SVM, and FCN architectures with miniature robotic platforms, providing a foundational framework for automated cancer diagnosis. This work, cited 3 times, analyzes the structure and image processing methods of miniature robots, highlighting key technologies and recent advances in the field. By bridging the gap between deep learning and robotic-assisted diagnosis, Wu has helped chart a path for more precise, minimally invasive medical interventions. Their research is particularly valuable for students and engineers seeking a consolidated view of how CNN-based systems can be deployed in real-world clinical settings. Wu’s synthesis of technical approaches offers a clear roadmap for future innovation in intelligent diagnostic systems.