Predicting cancer patient survival rates is a crucial aspect of cancer treatment and management. Accurately forecasting a patient's prognosis helps medical professionals make informed decisions about the most appropriate course of action and can also aid in the development of personalized treatment plans. Researchers from the University of British Columbia and BC Cancer have created an AI model that predicts cancer patient survival with greater accuracy and using more readily accessible data compared to previous methods. The AI model utilizes natural language processing (NLP), a field of AI that comprehends human language, to examine oncologists' notes taken following a patient's initial consultation. This is the first step in a cancer patient's journey after diagnosis.

A team of researchers from the University of British Columbia and BC Cancer have developed an artificial intelligence (AI) model that predicts cancer patient survival more accurately and with more readily available data than previous tools. The model uses natural language processing (NLP)--a branch of AI that understands complex human language--to analyze oncologist notes following a patient's initial consultation visit--the first step in the cancer journey after diagnosis. By identifying characteristics unique to each patient, the model was shown to predict six-month, 36-month and 60-month survival with greater than 80 percent accuracy. The findings were published today in JAMA Network Open. "Predicting cancer survival is an important factor that can be used to improve cancer care," said lead author Dr. John-Jose Nunez, a psychiatrist and clinical research fellow with the UBC Mood Disorders Centre and BC Cancer.