CS Colloquium: Elad Yom-Tov (Microsoft Research)

Screening for cancer using a learning internet advertising system

Studies have shown that the traces people leave when browsing the internet may indicate the onset of diseases such as cancer. Specifically, queries to search engines were found to be indicative of future cancer diagnosis for several types of cancer.

In my talk I will discuss two studies showing that the adaptive engines of advertising systems working in conjunction with clinically verified questionnaires can identify people who are suspected of having one of three types of solid tumor cancers. First, a classifier trained to predict suspected cancer inferred from questionnaire response using past queries reached an Area Under the Curve of 0.64. Second, using a conversion optimization mechanism, both Bing and Google advertisement systems learned to identify people who were likely to have symptoms consistent with suspected cancer, such that after a training period of approximately 10 days, 11% of people it selected for showing of targeted campaign ads were found to have suspected cancer. People who received information that their symptoms were consistent with suspected cancer increased their searches for healthcare utilization and maintained it for longer than people whose symptoms were not associated with suspected cancer, indicating that the questionnaires provided useful information to people who completed them.

These results demonstrate the utility of using search engine queries to screen for possible cancer and the application of modern advertising systems to identify people who are likely suffering from serious medical conditions.

Bio: Elad Yom-Tov is a Principal Researcher at Microsoft Research. Before joining Microsoft he was with Yahoo Research, IBM Research, and Rafael. His primary research interests are in applying large-scale Machine Learning and Information Retrieval methods to medicine. Dr. Yom-Tov studied at Tel-Aviv University and the Technion, Israel. He has published four books, over 100 papers (of which 3 were awarded prizes), and was awarded more than 20 patents. His latest book is “Crowdsourced Health: How What You Do on the Internet Will Improve Medicine” (MIT Press, 2016).

Tuesday, March 12 at 2:00pm

St Mary's Hall 326

Event Type

Academic Events

Departments

Georgetown College, Computer Science

Website

https://cs.georgetown.edu/events

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