LAHORE – A new chapter in Punjab’s healthcare system is taking shape as AI moves into the screening room. A proposed AI scanner could help doctors detect cancer, fatty liver, and other serious diseases in just minutes, giving early diagnosis a strong technological boost.
The provincial authorities are taking a major leap into AI-powered healthcare as Chief Minister Maryam Nawaz Sharif gives green light in principle to a cutting-edge scanner capable of screening for up to 10 diseases in around two minutes.
The technology, demonstrated by senior executives of Chinese tech giant Alibaba, uses non-contrast CT scans to rapidly analyze patients and flag potential signs of serious illnesses.
The proposed system could assist doctors in detecting some of the most dangerous cancers, including pancreatic, liver, gastric, esophageal and colorectal cancers.
Its capabilities extend beyond cancer screening. The AI tool can also assess cardiovascular risks, acute aortic syndrome, fatty liver disease and osteoporosis, while providing evaluations of bone and muscle health.
CM Maryam Nawaz directed Punjab’s health authorities to move ahead with preparations for a pilot project, marking a potential new phase in the province’s use of artificial intelligence for medical screening and early detection. Officials stressed that the technology would work alongside doctors and existing diagnostic procedures, providing additional screening support rather than replacing medical professionals.
Punjab government has yet to announce where the pilot will be launched or when the AI scanner will become operational.
AI is transforming radiology by helping doctors analyze CT scans, X-rays and MRIs, flagging possible cancers, cardiovascular problems, fatty liver and bone-related conditions. While these systems can speed up screening and prioritize suspicious cases, they support rather than replace doctors, with accuracy varying by disease, scan quality and patient population.
Punjab’s planned AI scanner pilot will test whether it can effectively screen for up to 10 diseases in about two minutes in real-world healthcare settings.
