Not all cancer patients benefit from chemotherapy or immunotherapy. Having a way to predict patient responses to various cancer treatment options may help improve outcomes. A new study published in Nature Communications shows how a combination of artificial intelligence (AI) machine learning with genomic sequencing may predict survival and responses to cancer treatments for stomach cancer. "There are currently few predictive biomarkers to guide treatment choices for gastric cancer patients," wrote the researchers affiliated with the Mayo Clinic, the Cleveland Clinic, Yonsei University College of Medicine, Seoul St. Mary's Hospital, and the University of Texas Southwestern Medical Center. Stomach cancer, also known as gastric cancer, is the fourth leading cause of cancer deaths globally and the fifth most common according to 2020 statistics from Global Cancer Statistics (GLOBOCAN).

Two Japanese national research institutes have succeeded in using artificial intelligence to identify early stage stomach cancer with a high accuracy rate. The breakthrough may help extend the lives of patients in Japan, where stomach cancer is one of the leading causes of death. According to the National Cancer Center, 45,531 people died of stomach cancer in 2016. According to Riken and the National Cancer Center, it took AI only 0.004 seconds to judge whether an endoscopic image showed early stage cancer or normal stomach tissue. AI correctly detected cancer in 80 percent of cancer images, while the accuracy rate was 95 percent for normal tissue.