New AI solves math and science problems faster than supercomputers

This new AI framework DIMON stands for Diffeomorphic Mapping Operator Learning. 

Engineers design safer cars, more resilient spacecraft, and stronger bridges using complex math problems that drive the underlying processes. Similarly, doctors use mathematical models to predict heart problems with greater accuracy.

These problems, called partial differential equations, are the backbone of engineering and science. But solving them can take days, even weeks, especially for complex shapes.

Now, Johns Hopkins University researchers have created a new AI model called DIMON. It can solve these complex equations thousands of times faster, right on your personal computer.

“While the motivation to develop it came from our own work, this is a solution that we think will have generally a massive impact on various fields of engineering because it’s very generic and scalable,” said Natalia Trayanova, biomedical engineering and medicine professor from the Johns Hopkins University. 

Tested on heart digital twins

Partial differential equations are common mathematical problems. These equations help convert real-world scenarios into mathematical models to predict future changes in objects or environments.

However, solving these big math problems is typically a job for supercomputers. Things are becoming easy with the arrival of artificial intelligence. 

This new AI framework DIMON stands for Diffeomorphic Mapping Operator Learning. 

The team tested DIMON on over 1,000 digital computer heart models of real patients. 

Interestingly, the model accurately predicted electrical signal pathways in diverse heart structures.

In this demonstration, the researchers used partial differential equations to investigate cardiac arrhythmia. This happens when the human heart beats irregularly because of messed-up electrical signals.

Using heart digital twin models, researchers can predict the risk of this life-threatening condition and suggest appropriate treatments.

“We’re bringing novel technology into the clinic, but a lot of our solutions are so slow it takes us about a week from when we scan a patient’s heart and solve the partial differential equations to predict if the patient is at high risk for sudden cardiac death and what is the best treatment plan,” explained Trayanova, who directs the Johns Hopkins Alliance for Cardiovascular Diagnostic and Treatment Innovation. 

The new AI significantly speeds up heart disease predictions, reducing calculation time from hours to 30 seconds. It can be done using a simple computer, making it more practical for everyday clinical use.

However, don't expect your cardiologist to use this now. It is in early theoretical development.  

DIMON is not for the weak of heart or mind. “For each problem, DIMON first solves the partial differential equations on a single shape and then maps the solution to multiple new shapes. This shape-shifting ability highlights its tremendous versatility,” said Minglang Yin, a Johns Hopkins Biomedical Engineering Postdoctoral Fellow who developed the platform.

Gary M. Levin M.D.

New AI solves math and science problems faster than supercomputers