AI systems already work their magic in many areas of biomedical science, helping to solve protein structure, discover hidden patterns in the genome and process massive amounts of biological data. Now, an AI-assisted technology developed at the Weizmann Institute of Science and published in Nature Biotechnology may grant researchers and physicians an unprecedented means of peering deep into the body’s tissues by making it possible to simultaneously view more proteins than ever before, in a tissue sample.

“To understand how any particular tissue works, it’s crucial to measure lots of its proteins at the same time,” says Dr. Leeat Keren of Weizmann’s Molecular Cell Biology Department, who headed the research team. “This gives us an idea of which cells are present in the tissue and how they communicate and interact with one another.”

Keren explains that this knowledge is vital to the study of disease processes. Cancerous growths, for example, contain, in addition to tumor cells, various other cell types, including healthy cells of the tissue the tumor is growing on and of the immune system. The cellular makeup of the tumor and how those cell types interact with one another can determine the effectiveness of therapies or be used to predict which patients have a better prognosis and which are likely to develop metastases. Such findings, in turn, can lead to improved personalized treatments.

Patients with narrowing of at least 50% in three major coronary arteries did equally well when treated with a minimally invasive stent placement guided either by ultrasound-based imaging or by a novel, artificial-intelligence-powered (AI), non-invasive imaging technique derived from angiography, researchers reported at the American College of Cardiology’s Annual Scientific Session (ACC.25) on March 30 in Chicago. The work was simultaneously published in The Lancet.

“This is the first such study to be conducted in patients with angiographically significant lesions,” said Jian’an Wang, MD, a professor in the Heart Center at The Second Affiliated Hospital of Zhejiang University School of Medicine in Hangzhou, China, and the study’s senior author. “Patients whose evaluation was non-invasively guided by the novel, AI-powered technique underwent approximately 10% fewer procedures, and their outcomes were comparable with those for patients whose evaluation was guided by a commonly used ultrasound-based imaging technique.”

The study, known as FLAVOUR II, met its primary endpoint, a composite of death, a heart attack or need for a repeat procedure at one year, Wang said.