Microsoft claims that it has developed an AI device, which recently diagnosed patients with four times more accuracy than human doctors.

The technology called Mai Diagnostic Orchestrator (MAI-DXO) works by adding several advanced AI models, including Chatgpt, Google’s Gemini, Ethropic’s claude, Meta’s Lalama, and Xai’s Grok. The system mimics a team of doctors working simultaneously, shares opinions and debate symptoms before reaching a diagnosis.

To test the system, researchers used 304 real -life case studies published in the New England Journal of Medicine. These were converted into a series of patient scenarios, where AI had to detect the disease, such as a doctor analyzing symptoms, ordering tests and step-by-step to reduce the possibilities.

The results were surprising: the AI ​​system correctly diagnosed 80% of cases compared to just 20% by a group of human doctors. And it was not just about accuracy. AI also managed to reduce the cost of diagnosis by about 20%by selecting more affordable tests and avoiding unnecessary procedures.

Microsoft AI CEO Mustafa Suleman said, “This is a real step towards medical superintendent, which Microsoft AI CEO Mustafa Suleman said, which highlights the capacity of the equipment to change the healthcare decision.

According to the company, as the demand for healthcare is increasing, the cost is growing at a constant pace, and billions people face many obstacles for better health, including incorrect and delayed diagnosis.

While AI has already been used to help doctors explain medical scans, this latest development suggests that it can take on broad clinical roles, possibly becoming the first point of contact for patients in future.

Experts involved in the project say that this can help reduce the cost of healthcare and speed up access to care. Dominic King, a vice president of Microsoft, said, “Our model performs incredibly well-for lid and so cost effectively.”

However, like all AI systems, these devices should be carefully monitored. There are concerns about whether they work equally well in different populations, as most of the data of training can be slanting towards some groups.

“This research is just the first step on a long, exciting journey. We are excited to test and learn with our healthcare partners in search of better, more accessible care for people,” said Suleman.