AI in healthcare: high-quality clinical data essential for progress

Constructing high-quality, integrated clinical datasets is crucial for advancing the long-term deployment of artificial intelligence in healthcare, a medical expert said recently.

Xu Zhonghuang, president of Beijing Arion Cancer Hospital and a cancer specialist, said an ideal clinical data system should synthesize regular health examinations, lifestyle changes, and recent major illnesses while being able to analyze potential health risks.

Since its founding in 2021, the hospital has been developing its own information system to ensure that the data collected remains high-quality, continuous, and well-structured, Xu said.

In July, Beijing health authoritiesreleased an action plan to accelerate the development of AI-enabled healthcare.

The plan highlights the application of AI in medical services, including the creation of digital tools to assist with clinical diagnosis and treatment planning, improve quality control in medical imaging, and automate medical record generation.

To date, the hospital has introduced a suite of AI-assisted tools designed to support tasks such as intelligent pre-consultation, automated generation of electronic medical records, and screening cases suitable for clinical research.

“These intelligent tools are primarily aimed at relieving medical staff from repetitive and time-consuming tasks and improving overall diagnostic and treatment efficiency,” Xu said.

He added that AI currently plays a supportive role in clinical environments, with all AI-generated outputs still requiring human verification to ensure safety and reliability.

Wang Nasi contributed to the story.