Cognitive Computing: Penetrating Complexity & Clarifying Choices
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When IBM’s Watson won Jeopardy! in 2011, the victory set off a stampede of interest in the technology behind the computing coup. Today, what is known as “cognitive computing” is being pursued by some of the world’s leading technology companies. Along with IBM, whose Watson effort remains the most sophisticated and best-known cognitive computing platform1, Dell, Facebook, Google, HP, Microsoft and SAS are pursuing forms of artificial intelligence” (AI). The result has been a “steady and impressive improvement”2 in the technology’s capabilities. At its core, cognitive computing represents a set of powerful tools for penetrating complexity and clarifying choices. Not surprisingly, the healthcare field has become a prime focus, positioned, in one expert’s judgment, to “lead the [national] acceleration of cognitive computing.”3 “We’re all overwhelmed with data, but we don’t know how to turn data into knowledge,” says Dr. Robert Miller, vice president for quality and guidelines of the American Society of Clinical Oncology (ASCO). “Doctors need to know about this.”4 An important first step is ensuring that those at the front lines of medicine have a clearer understanding of the technology. 2
“We’re all overwhelmed with data, but we don’t know how to turn data into knowledge. Doctors need to know about this.” Dr. Robert Miller, vice president for quality and guidelines of the American Society of Clinical Oncology (ASCO)
The Limits of Traditional Computing “Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.” John McCarthy, Stanford University professor of computer science
1. Rodriguez, J. The Era of Cognitive Mobile and IoT is Upon Us. CIO. Jan. 15, 2016. Accessed at: http://bit.ly/1TxUiSK 2. Reynolds, H. Cognitive Computing. Beyond the Hype: Cognitive Computing and Your Business, Your Job, Your Life. KM World. 25(5); May, 2016. Accessed at: http://bit.ly/1U2us84 3. Saxena, M. Big Data: Where are the Opportunities for Cognitive Computing Startups? SandHill Group, Feb. 23, 2015. Accessed at: http://bit.ly/1W59LMb 4. Interview, Dr. Robert Miller, American Society of Clinical Oncology, May 16, 2016 5. Myers, A. Stanford’s John McCarthy, seminal figure of artificial intelligence, dies at 84. Stanford Report. Oct. 25, 2011. Accessed at: http://stanford.io/1U4B9DU 6. Stephens, Z. D., Lee, S. Y., Faghri, F., Campbell, R. H., Zhai, C., Efron, M. J., . Robinson, G. E. (2015). Big data: astronomical or genomical? PLoS Biol, 13(7), e1002195
The first programmable computer to use the on-off (1/0) pulses of the digital age, ENIAC (Electronic Numerical Integrator And Calculator), was completed in 1946. Within a decade the term artificial intelligence was coined to describe this computational advancement: “Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.”5 For medicine, and for oncology in particular, an additional Big Data challenge comes from the sequencing of the human genome. Within 10 years, the tasks of genomic data acquisition, storage, distribution and analysis are expected to create a “four-headed beast” with unprecedented computational demands.6 Enter cognitive computing.
Cognitive Computing: Penetrating Complexity & Clarifying Choices
How Cognitive Computing Works There are many definitions of cognitive computing. However, it ultimately depicts systems that learn from interactions with data how to solve problems on their own. Traditional computers merely calculate rapidly, but smart machines learn from texts, extract insights from data and have the potential to recognize images.7
“Training Watson to improve cancer treatment is a much more ambitious effort than winning a game of Jeopardy!� Dr. Andrew Seidman, a member of the team training Watson at New York’s Memorial Sloan Kettering Cancer Center
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Similar to humans, a cognitive computing platform gains expertise with experience. The more examples on which the computer is trained, the deeper and more accurate the insights and predictions, as it employs parallel processing to analyze massive data sets for patterns and correlations. Making all this possible are sophisticated algorithms related to activities such as natural language processing, keyword extraction, concept tagging, taxonomy, sentiment analysis and relationship extraction.8 Of the companies involved in AI in healthcare, IBM has the greatest focus on oncology. In the last few years, IBM and leading oncologists have fed Watson millions of pages of medical journal articles, data from electronic medical records, and case studies to help facilitate collaboration across various teams. The intent is to improve communication between care teams; enable physicians to personalize therapeutic recommendations; and help match more patients to clinical trials.
In interviews, several physicians cited both specific accomplishments and the need to distinguish between present reality and future hopes. “Training Watson to improve cancer treatment is a much more ambitious effort than winning a game of Jeopardy!,” says Dr. Andrew Seidman, a member of the team training Watson at New York’s Memorial Sloan Kettering Cancer Center.9 Nonetheless, Seidman adds, the technology is beginning to prove its usefulness by providing treatment options informed with a previously unachievable level of detail, matching individual patient characteristics to the medical literature. By doing so, it “fills in holes” left by more generalized expert guidelines. Still, the technology’s role remains a supporting one. Watson’s response to an oncologist’s query is not a single answer, but a list of color-coded options that are “recommended” or “for consideration.” Literature references and the logic trail are all transparent.
Although the routine oncological use of cognitive technology is only now starting to spread, some analysts expect to see a rapid adoption for the clinical situations where it provides high value. By 2018 cognitive technology will be used to identify the most effective treatment for half of all complex cancer patients, predicts market research firm IDC.10 “Computer science is going to evolve rapidly, and medicine will evolve with it,” says Dr. Larry Norton, Memorial Sloan Kettering’s deputy physician-in-chief for breast cancer programs. “This is co-evolution. We will help each other.”11 7. Davenport, TH. “CIO Journal: The Confusing Landscape of ‘Cognitive” Computing.” Wall Street Journal. Accessed at: http://on.wsj.com/1PtxNcr 8. Taft, DK. “Machine Learning Shaping the New World of Cognitive Computing.” eWeek. Nov. 30, 2015. Accessed at: http://bit.ly/1WHXI7v 9. Interview, Dr. Andrew Seidman, Memorial Sloan Kettering Medical Center, May 19, 2016 10. IDC FutureScape: Worldwide Healthcare 2016 Predictions. November, 2015. Accessed at: http://bit.ly/257YkFj 11. Kelly III, J., & Hamm, S. (2013). Smart Machines: IBM’s Watson and the Era of Cognitive Computing: Columbia University Press
Cognitive Computing: Penetrating Complexity & Clarifying Choices
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