In April 2024, the Experimental Diagnosis Group of the Hematology Branch of the Chinese Medical Association organized relevant experts to standardize and optimize the clinical application of artificial intelligence technology in blood cell morphology examination based on the urgent need for precise clinical diagnosis. By integrating the latest research achievements at home and abroad, Jointly published the "Chinese Expert Consensus on Technical Requirements and Clinical Application of Artificial Intelligence-Assisted Blood Cell Morphology Examination (2024 Edition)" (hereinafter referred to as the "Consensus").

Liu Zhi, the CTO of Chongqing Defang Information Co., LTD., was honored to be invited to participate in the formulation and discussion of this "Consensus" because the peripheral blood image analysis system he led in developing meets the clinical application requirements of blood cell morphology examination and highly complies with the technical process norms of this "Consensus".

This "Consensus" not only standardizes the application rules of artificial intelligence in blood cell morphology, including blood smear production and staining, image acquisition, cell image recognition and classification, etc., but also emphasizes the requirements for establishing quality control standards, standardizing the content and form of diagnostic reports, as well as data security and efficient management of digital image storage for cell pathology. The release of the "Consensus" holds significant milestone significance for peripheral blood morphology examination, effectively promoting the application of artificial intelligence in the standardized diagnosis and treatment as well as the testing level of peripheral blood morphology, and also clarifying the overall development direction of the automation of blood cell morphology examination.

Under the leadership of General Manager Liu Zhi, the R&D team of Chongqing Defang spent five years in collaboration with the blood centers of the entire military and authoritative experts in laboratory medicine, applying artificial intelligence technology to develop the latest generation of artificial intelligence peripheral blood image analysis system. The system can identify 47 types of abnormal cells and directly provide auxiliary diagnostic basis for clinical practice. It has been shortlisted for the "Challenge and Response List" of the 2022 Ministry of Industry and Information Technology of China's Artificial Intelligence Medical Device Innovation tasks. The system not only meets the requirements of this "Consensus", but has also been widely applied in the clinical diagnosis of blood cell morphology, effectively solving the problems of difficult and inaccurate identification in clinical morphology tests, and improving the efficiency and quality of grassroots tests.

Technological innovation is transforming the medical industry at an unprecedented speed. The integration of artificial intelligence technology and medical diagnosis has become a future development trend, and morphological-assisted diagnostic products have also reached a crossroads of technological innovation. Based on artificial intelligence technology, focusing on morphological examination has always been the development direction that Chongqing Defang strives for. This time, General Manager Liu Zhi's participation in the formulation of the "Consensus" not only provided theoretical support for Chongqing Defang in the development direction of blood cell morphology, but also offered guiding value for the clinical application in more fields of cell morphology examination and diagnosis.

Chongqing Defang has always been a leader in the field of peripheral blood morphology examination. It will continue to strive in the future, leverage the potential of artificial intelligence, further enhance the practicality and functionality of artificial intelligence technology in the diagnosis and treatment application process, and thereby continuously meet various medical clinical needs. At the same time, we will continuously enhance technological iteration, accelerate the integration of morphology with big data and intelligent technology, reach strategic cooperation with major hospitals and medical institutions, and promote the research and development of more products for clinical application of morphology.