Lung cancer， with persistently high incidence and mortality rates， remains a significant global health challenge. By taking the study on the experience in diagnosis and treatment of lung cancer with phlegm-dampness and blood stasis syndrome by distinguished traditional Chinese medicine physicians of the Sichuan School as an example， the diagnosis and treatment system for lung cancer with phlegm-dampness and blood stasis syndrome， which was formed in response to the humid and foggy environment of the Sichuan Basin， possesses unique value. However， traditional inheritance modes face challenges such as fragmentation， lack of standardization， and insufficient quantification， which hinder the promotion and application of this experience. This research focused on how to leverage multimodal data and artificial intelligence-generated content （AIGC） to achieve precise analysis， intelligent inheritance， and clinical innovation of the experience in diagnosis and treatment of lung cancer with phlegm-dampness and blood stasis syndrome by distinguished traditional Chinese medicine physicians of the Sichuan School. By integrating multimodal data （encompassing four diagnostic methods of traditional Chinese medicine， modern medical imaging， clinical laboratory tests， molecular biology， and regional environmental information）， a precise diagnosis and treatment system integrating macro and micro perspectives for the "disease， syndrome， and pathogenesis" was constructed. The research yielded the following results： （1） In precise syndrome differentiation， the objective quantification of the phlegm-dampness and blood stasis syndrome was achieved. By constructing a "four diagnostic methods， imaging， and molecule" correlation model， the study revealed intrinsic links between tongue and pulse parameters and the tumor microenvironment， as well as between regional climatic factors and syndrome characteristics， enabling real-time dynamic monitoring of efficacy. （2） In elucidating patterns， the study systematically explored the syndrome differentiation thoughts of Sichuan School physicians， such as the timing of purgation and tonification. A "pathogenesis， syndrome complex， and prescriptions and herb" network model was constructed， which accurately elucidated the synergistic action mechanisms of core herb pairs and quantified the dynamic compatibility patterns of reinforcing healthy Qi and eliminating pathogenic factors. （3） In intelligent empowerment， an auxiliary system integrating intelligent syndrome differentiation， treatment plan generation， and efficacy evaluation was built. This system can fuse regional characteristics with individual data， dynamically generate and optimize personalized prescriptions aligned with the experience of Sichuan School， and predict efficacy trends and potential adverse reactions. The integration of multimodal data and AIGC can effectively facilitate the structured inheritance and clinical translation of distinguished physicians' experience. The established intelligent diagnosis and treatment model integrating traditional Chinese medicine and Western medicine demonstrates clear potential in prolonging patients' progression-free survival， alleviating symptoms， and reducing adverse reactions to treatment. This study provides a referential methodological framework for the traditional Chinese medicine experience in diagnosis and treatment of lung cancer， especially the empirical inheritance and modernized development of regional academic schools. It contributes to advancing clinical diagnosis and treatment toward greater precision and personalization.

The integration of large language model （LLM） and traditional Chinese medicine （TCM） promotes the informatization of TCM，and also provides a new direction for the inheritance and innovation of TCM in the new era. Based on the research background of LLM，the development process of LLM based on the Transformer architecture is summarized，and the research progress of LLM in TCM is reviewed. The main process of constructing TCM LLMs and the key techniques used by researchers during model development are summarized. Based on the related literature， the main application scenarios of TCM LLMs and the research explorations conducted by TCM researchers using LLMs are outlined. Meanwhile，the current challenges faced in the development of TCM LLMs are analyzed. Further improvements are urgently needed in the construction of high-quality data，the evaluation methodology of TCM LLMs，the interpretability of the model， multimodal fusion of TCM LLMs， and the development of TCM prescription recommendation models. Looking forward to the future development of LLM in TCM，it is expected to provide a reference for the deeper integration of LLMs and TCM，and facilitate the modernization of TCM.

As traditional Chinese medicine （TCM） culture evolves， the academic thoughts of these practitioners， being a core component of TCM inheritance， are gradually shifting from traditional models to digital and intelligent approaches. However， this process faces challenges， including insufficient standardization of data collection and processing， low inheritance efficiency， and the risk of inheritance alienation. To address these issues， this paper proposed the construction of an intelligent platform following the "intelligence-transmission-modeling-linkage" path. "Intelligence" involves using smart perception technologies to accurately collect and classify diagnostic and therapeutic information from famous TCM practitioners， laying the foundation for digital inheritance； "transmission" focuses on leveraging artificial intelligence to mine and inherit the clinical experience of famous TCM practitioners， thereby establishing a "regional academic schools+group commonality" dynamic inheritance system； "modeling" integrates the academic thoughts and advantageous diseases of multiple schools to develop intelligent diagnostic and therapeutic models of famous TCM practitioners， resulting in personalized treatment plans； "linkage" involves constructing a clinical decision support system of famous TCM practitioners by integrating blockchain and generative intelligence， creating an AI digital avatar of TCM diagnostic and therapeutic knowledge. The "intelligence-transmission-modeling-linkage" intelligent inheritance model not only provides new ideas for the digital inheritance of TCM academic schools， but also offers strong support for the modernization and internationalization of TCM.

Yin-yang, visceral manifestation, and ti-yong theories are the core theories of traditional Chinese medicine (TCM) and play a crucial role in its formation and development. With the continuous evolution of Chinese philosophy, TCM philosophy and theories have undergone significant influence, resulting in differing interpretations of the visceral manifestation of liver and mingmen across various historical periods by different medical practitioners. This paper focuses on the different understandings of the position of liver and mingmen, combining relevant philosophical images and TCM anatomical illustrations to deeply explore ancient medical theorists′ concepts regarding the four spatial directions of left, right, up, and down. The research reveals that ancient medical theorists′ conceptualization of spatial theory transitioned from an initial circular motion to a vertical movement, with the focus shifting from the upper part to the lower part. The primary reasons for these differences and changes could be explained by the varying emphasis on the ti-yong theory and differing focal points within the yin-yang theory. This study systematically examines the evolution of visceral manifestation theories related to liver and mingmen, highlights the shifts in physicians′ perspectives on spatial theory, and analyzes the influence of the ti-yong theory and yin-yang theory on these changes. The findings aim to provide a theoretical guide for advancing research and clinical application of spatial theory in TCM, thereby fostering the integration of TCM philosophy with medical theory.