Cancer research involving AI long on predictions, short on outcomes

Worldwide, research is booming around AI applications for predicting and treating cancer with ever more precise and personalized approaches. However, a new literature review has found a shortfall of AI-inclusive studies looking at cancer outcomes and survivorship.

The study was published online Oct. 1 in JMIR Medical Informatics.

Reviewing cancer studies published through 2018 and dating back to 1991, researchers in the U.S., Vietnam and Singapore counted more than 3,500 abstracts mentioning AI along with cancer therapeutics, capacities and factors associated with outcomes.

They found the most commonly explored topics involved machine learning, AI-based disease prediction and the comparative effectiveness evaluation of AI-assisted medical therapies.

The bibliometrics further showed the increasing interest in these topics evidenced by research activity around the world owes largely to the growth of clinical possibilities for AI in its various iterations.

“The research topics and landscapes constructed show that the development of AI in cancer care is focused on improving prediction in cancer screening and AI-assisted therapeutics and corresponding areas of precision and personalized medicine,” the authors comment in their discussion. “Our findings show the rapid growth in these areas over the past decade.”

At the same time, a boomlet the authors observed in research looking into indirect outcomes indicators—things like physical functioning and quality of life measures—makes all the more noticeable “the relative paucity of research focusing on cancer outcomes and survivorship.”

The latter finding is noteworthy and deserving of attention, the authors note, especially in light of the snowballing proliferation of cancer survivors.

Lead author of the study is Bach Xuan Tran, PhD, of Johns Hopkins and Hanoi Medical University.

The report is available in full for free.