2025交叉学科研究生学术论坛“AI+围术期医学”

1.Opening Ceremony

On the morning of November 22, Yang Dawei, Executive Deputy Director of the Degree Evaluation Committee Office at Shanghai Jiao Tong University, delivered an opening address at the Shanghai Jiao Tong University 2025 Interdisciplinary Graduate Academic Forum. He emphasized that this forum is dedicated to fostering new momentum for interdisciplinary development and pioneering new pathways for cross-disciplinary talent cultivation. He encouraged participating graduate students to fully leverage this platform to actively showcase research achievements, broadly draw cross-disciplinary insights, spark scientific inspiration, forge genuine friendships, and clarify future development directions.

Professor Yu Weifeng, Chair of the Chinese Medical Association's Anesthesiology Branch, and Professor Zhang Shaoting, CEO of SenseTime Healthcare and Dean of Shanghai Jiao Tong University's Qing Yuan Research Institute, delivered opening remarks as representatives of the Medical-Engineering Cross-Disciplinary Forum. This segment was chaired by Lu Jialiang, Vice Dean of SPEIT.

Zhang Shaoting delivered a presentation titled “Multimodal Integration Paradigm in Healthcare: Full-Scene Diagnostic Innovation Driven by Foundation Models,” systematically introducing innovative achievements in clinical application-oriented multimodal medical image foundation models. By establishing China's largest medical big data training facility, the presentation demonstrated how data standardization and service openness drive the extensive application of the SenseCare Smart Diagnosis Platform across multiple surgical departments including hepatology, pulmonology, and pancreatology. Furthermore, the AI-powered diagnostic model reduced pathology workflow time from five days to one to two days, comprehensively advancing the digitization, intelligence, and standardization of diagnosis and treatment, making AI-driven healthcare accessible to all.

Additionally, Professor Wan Yi, Professor Yang Chaoyong and Professor Liu Haoyang delivered speeches on interdisciplinary research in environmental monitoring and embodied intelligence, respectively.

肖立教授

Professor Xiao Li presented three groundbreaking advancements by his team in AI-driven medical research in his report “AI-Driven Medical Innovation Research”: DeepOrganelle technology enables subcellular-scale quantification and digital reconstruction of organelles, establishing a new paradigm for electron microscopy image analysis. It has supported multiple research groups in publishing findings in journals such as "Cell Metabolism“ and ”Cell Proliferation“. The UniDCF deep learning framework integrates over 6,600 patients and 54,000 samples, constructing the largest and most clinically representative multimodal craniofacial dataset to date, surpassing existing state-of-the-art methods in geometric precision, structural integrity, and spatial accuracy; Concurrently, the team is actively pursuing reinforcement learning-based anesthesia strategy research, exploring pathways for optimizing anesthesia protocols. It highlights current model limitations in data quality and annotation standards, advocating for accelerated clinical translation through multi-center collaboration to chart the frontier direction for establishing a new paradigm of peri operation period intelligent decision-making.

李洪教授

Li Hong pointed out in his report “Artificial Intelligence and the Development of Anesthesiology” that as artificial intelligence approaches human-level cognition, it is driving a comprehensive transformation of anesthesiology toward precision and intelligence: its models have surpassed the Turing test, demonstrating behavioral prediction and human-like comprehension capabilities. Leveraging intelligent monitoring and imaging algorithms, AI is advancing the visualization and individualized management of clinical anesthesia. Simultaneously, AI is profoundly reshaping fundamental research and educational paradigms through virtual scientists, robotic experiments, and VR instruction. Facing this transformation, he emphasized that human-machine collaboration represents the optimal future trajectory. Physicians must transition from operational roles to cognitive decision-making roles. Those adept at leveraging AI will gain a competitive edge, while others risk obsolescence.

Xu Tao emphasized that establishing a broad collaborative alliance encompassing anesthesiology departments and external experts is crucial. It is necessary to foster regular exchanges and cooperation among all parties through stable collaborative mechanisms, thereby advancing interdisciplinary medical-engineering research to greater depths.

Zhang Hui stated that this forum serves as a concrete manifestation of actively responding to and implementing national policies, while also showcasing the trend of deep collaboration between universities and medical institutions in interdisciplinary fields.