Medical AI model speeds up blood analysis

CHONGQING — A Chinese medical research team has developed a patented model that uses artificial intelligence to speed up and automate blood analysis, allowing laboratories to provide faster and more accurate feedback to doctors.

Hospital laboratories evaluate millions of blood cells for diagnosis every day, a repetitive task usually performed manually by trained physicians who inspect blood samples through microscopes one after another.

The new AI model has been hailed as a groundbreaking development as it has the potential to revolutionize how laboratories analyze samples, streamlining the evaluation process and flagging potential abnormalities with exceptional efficiency.

A blood smear is a conventional examination used to detect abnormalities in blood cells. It is an important way to clinically diagnose blood and lymphatic system disorders.

However, the current analysis of blood smear images under a microscope is timeconsuming and relies on the skill and experience of the physician. Many Chinese clinics at the grassroots level lack properly trained professionals, resulting in a low rate of diagnosis.

Based on 2,500 microscopic blood smear images taken from patients at the Xinqiao Hospital at Army Medical University in Chongqing between 2018 and last year, researchers developed the AI-assisted model, which turned the results into algorithms.

The model has learned to differentiate between cells that are normal or abnormal with an accuracy of over 90 percent in a shorter period of time than humans, said Peng Xiangui, leader of the research team and chief examiner at the hospital’s hematology center.

“Physicians need half an hour or more to examine a blood sample and generate a report, while the AI model just needs a few minutes,” said Peng, who has more than 30 years of experience in the field of hematology.

He went on to explain that in order to train, validate and test the AI model, his team fed it data on 300,000 red blood cells collected over the past five years, resolving a challenging identification problem.

The results showed that the model is able to accurately identify 49 types of abnormal blood cells, covering most of the common diseases dealt with at the clinic.

In addition to cutting down the need for manual labor, Peng believes that the model will help train inexperienced physicians and boost their efficiency.

“A doctor can only examine a limited number of cases in their lifetime, whereas the AI database can accumulate unlimited information, making diagnosis more scientific and accurate,” Peng told Xinhua.

This is the latest example of Chinese researchers using AI technology to assist physicians in clinical diagnosis. From diagnostic screening to surgical robots, AI-assisted medical products are gaining momentum in hospitals across the country.

Zhang Xi, head of the hospital’s hematology center, said that the AI model was granted a Class II medical device license in September last year and has obtained 32 patents. Several domestic medical institutions have expressed their interest in collaborating with the research team.

“We will explore further potential applications of the AI system to assist more primary care hospitals and serve more patients,” Zhang added.