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Artificial intelligence-enabled medical diagnostic tools are ensuring greater accuracy in cancer screening and detection, helping doctors arrive at more precise diagnoses and enhancing treatment quality.

Zhejiang University recently introduced an AI-powered universal pathology assistant called OmniPT, which integrates vision and language models for human-computer interaction. 

The model is being used at the First Affiliated Hospital of Zhejiang University School of Medicine's department of pathology, focusing on high-incidence cancers such as gastric, colorectal and cervical. The hospital in Hangzhou, the capital of Zhejiang province, is the first clinical institution in China to use an AI-powered pathology assistant.

OmniPT has achieved a number of breakthroughs in laboratory tests, including in cancer classification, grading, vascular and neural invasion identification and the discovery of markers that indicate the future course of the disease, the hospital said. Analyses and predictions by OmniPT have been 80 to 90 percent accurate across cancer types.

Most patients and their families are unfamiliar with the details of pathology examinations — work performed on tissue samples or cells in a lab, and pathologists generally do not interact directly with patients.

When biological samples from a patient are sent to a lab, experts go through an intense process to understand the pathological changes and the nature of the disease in the specimen at hand.

The role of the pathologist is to help reach an accurate diagnosis through the application of rigorous empirical standards. China, however, faces a severe shortage of pathology professionals.

"Many people may know that pediatricians are in short supply, but pathologists are even more rare. Currently, our country needs 150,000 to 200,000 pathologists, but there are only about 30,000 officially registered," said Zhang Jing, chair of the pathology department and vice-president of the Yuhang branch of the hospital.

Apart from this massive gap, there are also regional imbalances. While cities like Beijing, Shanghai and Hangzhou may be facing less severe shortages, the situation is dire in remote areas, he added.

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