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Chongqing - A tiny slice of tissue can hold the key to detecting disease — but reading it accurately often requires highly trained specialists.
As China works to expand precision healthcare, a shortage of pathology experts has become a challenge. Chongqing’s Jinfeng Laboratory is turning to AI to develop next-generation diagnostic tools that could make medical expertise more accessible.
Jinfeng Laboratory is located in Western (Chongqing) Science City, a major innovation hub in southwest China. (Photo/Lei Jian)
In a quiet pathology lab, a doctor places a fingernail-sized glass slide under a microscope, searching for microscopic signs that can reveal what is happening inside a patient’s body.
“This is a biopsy slide taken after brain tumor surgery,” said Yao Rui, an attending pathologist at Hygeia Hospital. “Under an optical microscope, the differences between normal and tumor cells are measured in micrometers—just a fraction of the diameter of a human hair.”
Pathologists must identify these subtle differences under a microscope to support accurate diagnoses, a process that requires extensive expertise and careful analysis. At Hygeia Hospital, the pathology department receives slides covering more than 100 types of diseases every day.
For complex cases, patients may also need additional molecular testing, with results often taking more than 10 days, further increasing the time and workload involved in diagnosis.
With an industry benchmark of one to two pathologists per 100 hospital beds, China faces a shortage of more than 100,000 pathology specialists, especially in primary-level medical institutions. AI-assisted pathology offers a new way to boost diagnostic efficiency and help bridge regional gaps in healthcare services.
Jinfeng Laboratory aims to become an international center for pathology research, with next-generation diagnostics for major diseases as a core mission. The laboratory is a key strategic research platform under Chongqing’s “416” science and technology innovation framework and its efforts to build a nationally influential innovation center.
Pathologists conduct a remote consultation at the Intelligent Pathology Center of Jinfeng Laboratory. (Photo/Lei Jian)
Compared with conventional pathology, AI-assisted diagnosis can rapidly analyze digital slides and related clinical data, supporting doctors in diagnosis and treatment.
“We receive pathology data from primary-level hospitals in real time,” said Yan Xiaochu, Chief Scientist at the Intelligent Pathology Center of Jinfeng Laboratory. Yan said AI models can provide diagnostic results, predict disease outcomes, and offer treatment recommendations, allowing primary-level hospitals to access more consistent, high-quality pathology services.
Accurate AI diagnosis depends on large volumes of high-quality pathology data. Drawing on its growing data resources, Jinfeng Laboratory is building a pathology data network covering medical institutions across different regions and levels.
Li Sen, Project Director of the Intelligent Pathology Center of Jinfeng Laboratory, said Jinfeng Laboratory has partnered with 49 medical institutions across 21 provincial-level regions. It has also been approved to establish a national pathology phenotype data sub-center.
According to Li, it is the only institution in China capable of collecting and standardizing pathology data across provinces, medical centers and institutional levels.
Supported by this data network, Jinfeng Laboratory has connected 43 medical institutions across 35 districts and counties in Chongqing. Its system integrates six intelligent diagnostic modules, reducing the time needed to annotate a pathology slide from five minutes to 50 seconds, with an accuracy rate of 87%. It has also completed remote diagnoses for more than 400 complex cases.
Researchers conduct pathology testing at the Intelligent Pathology Center of Jinfeng Laboratory. (Photo/Lei Jian)
Building on these advances, Jinfeng Laboratory released China’s first standardized brain tumor pathology dataset certified by the National Institutes for Food and Drug Control in April.
Yang Yi, a researcher at the Intelligent Pathology Center, said the dataset covers 474 clinical cases and centers on 3,420 whole-slide digital images, forming a multimodal data matrix.
Building a “common language” for AI pathology
Companies and research teams developing AI-assisted brain tumor diagnostic tools in China must submit their products to the National Institutes for Food and Drug Control for review before receiving market approval.
Their models are then evaluated through standardized blind testing using this dataset, allowing diagnostic accuracy and stability to be compared under the same benchmark.
The key value of a standardized dataset lies in setting common rules for the industry. Yan said the dataset provides a unified performance benchmark for AI research and development. Once established, the standard is expected to attract medical institutions, research teams and companies from across the country, helping Chongqing become a national hub for pathology data resources.
The creation of a national-level standard reflects Jinfeng Laboratory’s step-by-step innovation strategy. Its role as a strategic research platform gives it a mandate to fill gaps in the industry, while its talent pool supports technological development and commercialization.
Jinfeng Laboratory has assembled 738 researchers, 86% of whom work there full time. Researchers with master’s or doctoral degrees account for 72% of the workforce. It has also recruited five teams led by academicians and 41 national-level experts.