Each year, one out of every five patients admitted to a hospital in the United States for serious care develops acute kidney injury.

For a variety of reasons, these patients’ kidneys suddenly stop functioning normally and become unable to properly remove toxins from the bloodstream. The condition can permanently damage the kidneys, cause other illnesses or even lead to death. Acute kidney disease, or A.K.I., contributes to nearly 300,000 deaths in the United States each year, according to a 2016 study.

But if the condition is identified in its early stages and properly treated, it can be stopped or reversed.

In a paper published on Wednesday in the science journal Nature, researchers from DeepMind, a London artificial intelligence lab owned by Google’s parent company, detail a system that can analyze a patient’s health records, including blood tests, vital signs and past medical history, and predict A.K.I. up to 48 hours before onset.

The paper is part of widespread efforts to build technology that can automatically diagnose or predict illness and disease, from diabetic blindness to meningitis to cancer. In academia and industry, particularly at companies like Google and DeepMind, researchers are rapidly improving this new type of automated health care.

But there are many questions regarding the research, especially when it involves big corporate labs. To build and improve their automated systems, such labs must acquire vast amounts of patient data from hospitals and other medical institutions. That has repeatedly raised concerns over patient privacy.