ABOVE: MODIFIED FROM
© ISTOCK.COM, Aleksei_Derin

Scientists have been using two main forms of clinical data to predict cancer outcomes: images (either photographs, as in the case of skin cancer, or pathology slides) and -omes of various sorts. Applying ever-more sophisticated machine learning approaches to these datasets can yield accurate diagnoses and prognoses, and even infer how tumors evolve (yellow arrows). Now, scientists are finding that images can predict -omics (blue arrows). Combining the two data sources gives researchers even better predictions of how long a cancer patient will live (thick purple arrows). The ultimate goal of these algorithms, currently under development in basic biology labs, is to help doctors select treatments and forecast survival.

the scientist staff; © ISTOCK.COM, dzika_mrowka, from2015

Read the full story.

Interested in reading more?

May 2019 The Scientist Issue

Become a Member of

Receive full access to digital editions of The Scientist, as well as TS Digest, feature stories, more than 35 years of archives, and much more!
Already a member?