Whether it’s OpenAI’s ChatGPT or Google’s Bard AI, 2023 is the year that artificial intelligence has dominated the virtual water cooler.
In medicine, AI is already assisting in myriad ways. To name a few, AI can enhance diagnostics through analysis of big data and aid radiologists in interpreting images. It’s even helping to personalize medical treatment and in the diagnosis of disease.
Pancreatic Cancer Screening Status
Screening for common cancers like breast, cervix, and prostate cancer relies on relatively simple and highly effective techniques, such as mammograms, Pap smears, and blood tests. These methods have revolutionized outcomes for those cancers by enabling early detection and intervention during the most treatable stages.
For pancreatic cancer, the picture is very different because there is no easy screening test. The disease is very often diagnosed in later stages, due to the location of the pancreas deep in the abdomen and the often-vague early symptoms. The late diagnosis contributes significantly to the low survival rate for pancreatic cancer.
People at high risk for developing pancreatic cancer—those with certain genetic mutations, a family history of the disease, or an identified pancreatic cyst—are urged to undergo regular screening. But pancreatic cancer screening is more challenging than a mammogram. It generally involves blood tests, endoscopic ultrasounds and MRIs given at specific intervals. Although research shows high-risk screening is beneficial to patients, it can be difficult to access if patients live far from academic medical centers, where most of the research takes place. It can also be costly.
Predicting Pancreatic Cancer Three Years Before Diagnosis
Research published in May 2023 in Nature Medicine suggests that AI screening of large groups of patients beginning with their medical records could make earlier diagnosis of pancreatic cancer possible. That, in turn, could lead to earlier and more effective treatment of the disease.
“It’s a remarkable study and we’re all very excited about it,” says study co-author Michael H. Rosenthal, M.D., Ph.D., Assistant Director of Radiology, Pancreas and Biliary Tumor Center of Dana-Farber Brigham Cancer Center (Boston, Massachusetts). “This is a great example of the cool and wonderful things that AI can do. Finding the subtle sense of cancer among diagnostic codes around the world really gave us the sense that we are on the right track.”
