EXCLUSIVE

From data to diagnosis: How AI is helping doctors detect disease

AI can scan large amounts of imaging data and highlight areas that may need closer review

Last updated:
Ali Al Hammadi, Reporter
One of the main challenges in healthcare AI is making sure the technology is easy to use for doctors.
One of the main challenges in healthcare AI is making sure the technology is easy to use for doctors.
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From spotting early signs of illness to helping doctors review scans faster, artificial intelligence is starting to play a bigger role in healthcare and researchers in the UAE are part of this shift.

At Mohamed bin Zayed University of Artificial Intelligence, researcher Chao Qin is working on AI tools designed to support doctors in real clinical settings. Qin, who will graduate in 2026 with a PhD in computer vision, has focused his research on how AI can be used in medical imaging.

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He said his time at MBZUAI helped him move from purely technical work to thinking about real healthcare use.

“My journey at MBZUAI has been both academically and personally meaningful,” he said. “It helped me focus on building AI systems that are useful for doctors in real situations.”

Supporting doctors, not replacing them

Qin’s work looks at how AI can analyse medical images such as ultrasound, CT scans, MRI and X-rays. These systems are trained to recognise patterns that may point to disease.

In simple terms, AI can scan large amounts of imaging data and highlight areas that may need closer review. This can help doctors work faster and make better decisions, especially in conditions like cancer where early detection is important.

His research includes work on breast cancer detection using ultrasound videos, as well as improving how AI models understand different types of medical data.

Global recognition

During his studies, Qin was named a Best Paper Finalist and Young Scientist Award Finalist at MICCAI 2024, one of the leading global conferences in medical imaging.

He said presenting his work to an international audience of researchers and clinicians was a key moment in his journey.

“It gave me confidence that our research can make a real impact,” he said.

Why data matters

A big part of his research focuses on building large medical datasets. Qin contributed to an open-source ultrasound dataset with more than 470,000 images.

He explained that having more data helps AI systems become more reliable, especially since medical images can vary between hospitals, machines and patients.

“Diversity in data is very important,” he said. “It helps make sure the system works well in different situations.”

Making AI practical

One of the main challenges in healthcare AI is making sure the technology is easy to use for doctors.

Qin’s work includes developing systems that allow doctors to interact with AI results, rather than simply accept them. This helps improve accuracy and keeps doctors involved in decision-making.

The idea, he said, is to make AI a support tool, not a replacement.

Supporting UAE healthcare goals

With the UAE investing in AI and healthcare, Qin believes his work can support local priorities.

MBZUAI is already working with partners such as Department of Health – Abu Dhabi and Cleveland Clinic Abu Dhabi to explore how AI can improve diagnosis and patient care.

He said the UAE offers a strong environment for this kind of research, with good infrastructure and support for innovation.

Looking ahead

Qin expects AI to play a bigger role in healthcare in the coming years, especially in helping doctors analyse different types of medical data together.

He is now exploring postdoctoral opportunities, with a focus on building more accurate AI systems that combine medical images with patient data.

His goal is simple, to help make diagnosis faster and more consistent, while keeping doctors at the centre of care.

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