2.6: Real World Applications and Future Work

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Arguably the most famous example of artificial intelligence is IBM Watson. Ever since competing in both high-stakes chess and the game show Jeopardy!, Watson has applied its skills to more than just strategy games. Currently Watson has taken to oncology and is helping doctors and researchers diagnose cancer. The motivation behind Watson’s involvement is that oncologists need to stay up to date n the latest cancer research and studies for the maximum benefit of their patients. However, there are thousands of medical journals that publish oncological studies daily, and no one person could possibly keep up with them all. Instead, Watson has been trained to maintain a database of sorts for relevant information regarding cancer research that can be used as a supercomputer for physicians to give their patients the best care possible. Doyle-Lindrud explains in “Watson Will See You Now: A Supercomputer to Help Clinicians Make Informed Treatment Decisions” that Watson has paired with big hospitals and healthcare companies around the country including Memorial Sloan Kettering Cancer Center, the University of Texas MD Anderson Cancer Center, and WellPoint, Inc. In all these locations, Watson has been used as a tool to help customize patient care with the best possible treatment options by analyzing and ranking medical literature to rank potential treatment options based on evidence. Along with oncology, Watson has participated in other experiments meant to benefit patients.

Chen et al (2) described various studies that Watson has been a part of, including a drug repurposing study where Watson looked for drugs approved for human use and then cross referenced those drugs with statements suggesting efficacy in treating malaria. After obtaining this final list of cross referenced drugs, Watson then looked at the company’s existing compounds and identified similarities to known malaria treatments in hopes of finding drugs that may not have been intended to treat malaria, but possibly could. Watson also participated in a study at Baylor College of Medicine aimed to enhance insight on cancer kinases. First, Watson read articles discussing known kinases, then with graph and text-based features, Watson found text similarity patterns between kinases. Those models were then applied to Medline abstracts through 2002 to determine whether Watson could identify kinases discovered in 2003 through 2013. Watson was able to identify nine potential kinases successfully, and of these, Baylor validated seven. Watson’s clinical knowledge is a good example of machine classification and information retrieval put to good and accurate use. Watson is a valuable tool for many physicians and its knowledge is expanding daily which will hopefully help save more lives.