A research team led by Professor Kevin Tsia at the University of Hong Kong has developed an innovative AI-driven imaging tool called CytoMAD, which significantly enhances the speed and precision of cancer diagnosis.

The development of CytoMAD involved collaboration with medical experts from HKU's Li Ka Shing Faculty of Medicine, including associate professor James Ho and cardiothoracic surgeon Michael Hsin, and the findings were published in the journal Advanced Science.

CytoMAD employs advanced microfluidic technology for 'label-free' imaging, allowing for the examination of individual tumor cells and assessment of metastasis risks without traditional staining techniques.

By utilizing generative AI, CytoMAD streamlines sample preparation and diagnostic workflows, reducing the number of steps required for analysis.

This label-free approach not only expedites the diagnosis process but also accelerates drug discovery efforts, making it a valuable tool in medical research.

The AI capabilities of CytoMAD enhance cell imaging by correcting inconsistencies and extracting previously undetectable cellular information, leading to more reliable data analysis.

With its ultrafast optical imaging technology, CytoMAD can capture tens of millions of cell images daily, positioning the system for advanced AI research and development.

The system effectively mitigates the 'batch effect'—variability from different imaging protocols—by not relying on predefined data constraints, thus allowing for unbiased analysis.

The research team plans to expand CytoMAD's applications into predictive healthcare, focusing on early detection of cancer and other diseases.

While the current focus is on lung cancer, CytoMAD's capabilities extend to other cancers, aiming to enhance drug screening processes and improve predictive diagnostics.

The research team has applied for funding to conduct clinical trials over the next three years, which will involve monitoring lung cancer patients' progress using this innovative technology.

Professor Tsia emphasized that the generative AI technology used in CytoMAD produces clearer images that provide critical treatment information, further enhancing its diagnostic potential.