Medical Artificial Intelligence Technology and Application Development Forum was successfully held in Hangzhou

Release date: July 24, 2024 Views:

On July 19, the "2024 China Health Data and Digital Medicine Forum: Medical Artificial Intelligence Technology and Application Development" was successfully held in Hangzhou, hosted by the Health Data and Digital Medicine Branch of the China Medical Health International Exchange Promotion Association, undertaken by the Second Affiliated Hospital of Zhejiang University School of Medicine, and co-organized by Peking University Third Hospital. Professor Han Hongbin, Dean of the Institute of Medical Technology, Peking University Health Science Center, attended the seminar and delivered a welcome speech.

Professor Han Hongbin expressed his gratitude and warm welcome to all the experts, and pointed out that in the era of rapid development of artificial intelligence technologies such as big models, the leaders in the field of medical information are needed to discuss the development of artificial intelligence in clinical diagnosis, treatment, medical management, etc. in the new era, and flexibly apply new technologies of artificial intelligence, so as to make contributions in the future medical field and truly realize digital innovation to empower smart medical care. Professor Han wished the conference a complete success and pointed out that through this forum discussion, experts and scholars can further promote the development of digital and intelligent medical care in the future.

Professor Han Hongbin delivered a welcome speech

The seminar invited many well-known experts in the field of medical artificial intelligence to give keynote speeches. The meeting was hosted by Researcher Xie Zhaoheng from the Peking University School of Medicine and Deputy Director Li Pengfei from the Smart Healthcare Center of the Peking University Institute of Advanced Information Technology.

Professor Liu Huafeng of Zhejiang University shared the research progress titled "Artificial Intelligence Empowers PET Imaging". He gave a detailed introduction to the development history, research challenges, technological development and future exploration of positron emission tomography (PET) detector technology, and introduced the latest progress in PET detector technology from the aspects of software and hardware, including breakthroughs in image reconstruction algorithms and the close integration of deep learning, which improves PET detector technology in terms of time and spatial resolution and facilitates its application in clinical practice.

Professor Yang Meng from Peking Union Medical College Hospital gave a report on the theme of "Exploration of Artificial Intelligence Applications in Musculoskeletal Ultrasound", sharing a number of research results on the application of artificial intelligence in musculoskeletal ultrasound based on actual research results on rheumatoid arthritis (RA) and sarcopenia. She pointed out the current status and difficulties of accurate diagnosis and treatment of RA, and further proposed a deep learning scoring model for synovial membranes in static and dynamic ultrasound images, and the RATING system (deep learning combined with EOSS knowledge-guided RA multimodal ultrasound intelligent scoring system), which improves the reliability of the scoring and the interpretability of the scoring system through visualization of scoring results and auxiliary heat maps, truly realizing AI human-computer interaction, allowing ultrasound doctors to realize practical applications and improve clinical recognition accuracy.

Professor Tian Guihua from Beijing University of Chinese Medicine gave a report entitled "Establishment and Application of Intelligent TCM Diagnosis and Treatment System". Aiming at the bottleneck problems of redundant information and multi-modal and sparse data in TCM treatment, he proposed an intelligent diagnosis and treatment system for TCM prevention and treatment of chronic diseases. Director Tian mentioned that by establishing an evidence-based TCM methodology system for chronic pain and constructing an evidence-based TCM research paradigm of "production, differentiation, use and verification", medicine can be made warm. In addition, the original TCM pain "pulse-symptom-sign" feature information fusion algorithm was developed, and TCM palpation equipment was independently developed to overcome the technical difficulties of intelligent identification and precise collection of "pulse-symptom-sign" pain information. In addition, Professor Tian's team explained the analgesic mechanism of acupuncture and medicine combined with regulation of energy metabolism, enriched the connotation of TCM medication, and improved the level of clinical diagnosis and treatment.

Experts and scholars gave keynote speeches

Wang Mixia, an associate researcher from Cai Xinxia's team at the Institute of Space Information Innovation of the Chinese Academy of Sciences, shared a report titled "Precise Identification and Positioning of the Deep Brain and Intelligent Brain-Computer Interaction Technology". Guided by the major demand for precise identification and positioning, she introduced key technological breakthroughs in micro-nano electrode arrays and brain-computer interaction applications. Through the synchronous and joint rapid positioning of new algorithms for microscopic and macroscopic data, precise intelligent identification and positioning of the deep brain of rodents can be achieved. In the future, non-primate and clinical brain function positioning research is expected to be conducted, providing new means for the diagnosis and treatment of brain diseases. The team established a neural network learning and memory training program, realized neural network brain-computer interaction through neural stem cell culture and functional evaluation, and completed application evaluation, providing core components and instrument technology means for the detection of major brain diseases.

Professor Chen Yang from Southeast University shared a report titled "AI-enabled X-ray tomography algorithm research". The team first proposed the full-space constraint Deep Recon technology in the low-dose spiral CT research to optimize the overall performance. Faced with the challenges of photon counting CT imaging and clinical diagnosis scenarios, the detector counting system modeling is realized through deep learning, the signal-to-noise ratio is improved, the imaging rate is increased, and it is well applied in a variety of clinical scenarios. For intraoperative, radiotherapy and flexible application scenarios, a new dual-source cone beam CT (CBCT) device is developed to enable domestic low-cost mobile CBCT, which can effectively serve special scenarios such as remote areas and remote surgery.

Professor Li Yang from the Beijing University of Aeronautics and Astronautics shared a report on the theme of "Research Progress of Brain-Computer Interaction Technology for Major Brain Diseases", which summarized the four aspects of multi-dimensional collection and transmission of medical big data, medical big data supercomputing services and cloud platforms, medical cognitive computing and data intelligence, and intelligent applications combining medicine and engineering. Through the construction and positioning of individualized functional networks, the construction of multi-modal adaptive dynamic brain network models, and the proposal of multi-atlas multi-map cross-region perception fusion networks, the brain functional areas inside and around the tumor boundary are accurately divided in clinical verification, realizing the deep integration of structural phase, functional phase and clinical prior knowledge. For disease models that are difficult to treat with drugs, such as depression and autism, cross-modal fusion information recognition such as semantics and emotions is carried out, and a multi-modal brain-computer human emotion robot recognition system is designed, in order to achieve early detection, early intervention, and early treatment, providing a new way for early diagnosis and personalized treatment of brain diseases.

Professor Lu Jian from Peking University Third Hospital shared a report titled "Advances in AI-assisted diagnosis and treatment of prostate diseases", starting from the background of prostate cancer, which is highly prevalent worldwide, and introduced the wide application of AI in the field of prostate disease diagnosis and treatment. The diagnosis and treatment of prostate cancer uses AI technology in a variety of imaging data such as MRI, ultrasound CT, and pathology, including the introduction of natural language processing models, machine learning, and deep neural networks to assist clinical detection, risk classification, metastasis assessment, evidence synthesis, prediction of treatment response, palliative care, drug development, surgical navigation, etc., to achieve efficient diagnosis and precise treatment of prostate diseases.

Experts and scholars gave keynote speeches

After the special report, the experts at the meeting discussed in depth the topic of "Medical Artificial Intelligence Technology and Application Development". Clinical doctors and experts in the field of artificial intelligence discussed how to integrate the professional knowledge of the two fields of medicine and artificial intelligence in a high and deep way. The rapid development of medical artificial intelligence technology has brought unprecedented opportunities to the medical industry. With data-driven and knowledge-driven as the guide, academic exchanges and cooperation will be strengthened to better cope with future challenges and promote the continuous innovation and development of medical artificial intelligence technology.

Experts at the meeting had heated discussions

The successful holding of the "Medical Artificial Intelligence Technology and Application Development Forum" has laid a solid foundation for promoting technological progress and widespread application in this field. With the joint efforts of all experts, medical artificial intelligence technology will continue to break through innovation and help the medical and health industry continue to reach new heights. It is expected that in the future journey, medical artificial intelligence will be able to serve the society more deeply and protect the health of the people.

Group photo of experts attending the meeting