DeepMind’s new research is based on what is called a neural network, a complex mathematical system that can learn tasks by analyzing vast amounts of data. By analyzing thousands of dog photos, for instance, a neural network can learn to recognize a dog.

Tech giants like Google already use such technology to recognize faces in photos, identify spoken words and translate languages on popular internet services and consumer devices. Now, researchers are applying the idea to health care.

In the new paper, DeepMind researchers describe a system that learns to predict acute kidney injury by identifying patterns in over 700,000 patient records from the Department of Veterans Affairs. The system was reasonably accurate with its predictions, but it still missed almost half of the cases of A.K.I.

“This perhaps points at the need to look into other data sources that may paint a more complete picture of the patient’s clinical reality,” said Dr. L. Nelson Sanchez-Pinto, a researcher at Northwestern University who was not involved in the DeepMind paper but is exploring similar technology.

Because the system learns from the medical history of mostly male patients admitted to V.A. hospitals, it is also unclear how well the technology would work when used with patients outside that particular population.

As Dr. Sanchez-Pinto indicated, the system could be improved with more, and more varied, data. But that is where DeepMind and Google are running into problems.