Chilmark Advisory Service Analytics Domain Monitor (December 2017)
By Ken Kleinberg and Brian Edwards
Artificial intelligence (AI), especially the sub-area of machine learning (ML), offers the healthcare industry the potential to increase the productivity of clinicians and support staff. Big Data, rapidly decreasing costs for distributed computing infrastructure, and more powerful algorithms all drive this rapid rise in the use of AI – but success requires matching technologies to appropriate use cases.
- AI and ML, in development over decades and now at an inflection point, have gained traction and visibility in industries such as transportation, finance, and retail.
- Three converging advances are AI adoption: New types of hardware, the accumulation of massive datasets, and the validation of advanced analytical algorithms.
- Major initiatives from IBM and Google, an influx of VC investment, and progress by large EHR vendors have triggered healthcare’s interest in AI/ML.
- Chilmark sees five emerging areas of AI investment and impact: NLP (now), predictive analytics (now), image recognition (1-3 years), virtual assistants (2-4 years), and decision/diagnosis support (3-5 years).
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