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MarketsandMarkets estimates that Artificial intelligence spending in healthcare will reach $36.1 billion by 2025.
FREMONT, CA: Industry leaders are hurrying to build healthcare-specific artificial intelligence (AI) solutions in response to the COVID-19 pandemic, the mental health crisis, rising healthcare expenditures, and aging populations. A hint comes from the venture capital sector, where more than 40 businesses have raised $20M or more to develop AI solutions for the industry. But how is AI being implemented in healthcare?
More than 300 respondents worldwide were queried for the "2022 AI in Healthcare Survey" to better understand the problems and successes and use cases that define AI in healthcare. The results did not alter dramatically in its second year, but they indicate some intriguing trends that foretell how the pendulum may swing in the years. While some aspects of this transition are favorable (the democratization of AI), others are less exciting (a much larger attack surface). Here are some trends that businesses must be aware of:
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DEMOCRATIZATION OF AI WITH NO-CODE TOOLS
Gartner forecasts that by 2025, 70 percent of newly built enterprise applications will include no-code or low-code technologies, up from less than 25 percent in 2020. While low-code can ease programmers' workloads, no-code solutions, which do not require data science intervention, will significantly impact the enterprise and beyond. It is, therefore, interesting to observe a definite transition in the use of AI from technical terms to domain specialists themselves.
For healthcare, this indicates that more than half (61 percent) of AI in Healthcare Survey respondents chose clinicians as their target users, followed by healthcare payers (45 percent) and health IT businesses (38 percent). This, coupled with substantial advancements and investments in healthcare-specific AI applications and the availability of open-source technologies, is indicative of broader industry adoption.
Putting code in the hands of healthcare personnel in the same manner as typical office applications such as Excel or Photoshop can improve artificial intelligence. Also, to make the technology more accessible, it enables more accurate and dependable findings, as a medical professional—rather than a software expert—is now in control. These improvements are not instantaneous, but increasing domain experts as primary AI users is a significant step forward.
THE INCREASING SOPHISTICATION OF TECHNOLOGIES AND THE EXPANDING VALUE OF TEXT
Users also wanted to explore particular models in greater depth, indicating advances in AI tools. Technical executives' top technology priorities for 2022 include data integration (46 percent), business intelligence (44 percent), natural language processing (43 percent), and data annotation (43 percent). (38 percent). Text is currently the most prevalent type of data used in AI applications, and the emphasis on Natural Language Processing (NLP) and data annotation indicates an increase in the sophistication of AI technology.
These instruments facilitate vital operations such as clinical decision support, medication research, and medical policy evaluation. Having lived through the pandemic for two years, it is evident how essential advancements for these areas are as researchers develop vaccines and determine how to better support healthcare system demands. Additionally, it is clear from these examples that AI's application in healthcare differs significantly from that in other industries, so different methodologies are needed.
It should not be amazement that both technical leaders and respondents from mature enterprises rated the availability of healthcare-specific models and algorithms as essential for evaluating locally installed software libraries or SaaS solutions. As evidenced by the venture capital landscape, the market's current libraries, and the need for AI users, healthcare-specific models will continue to expand in the future.
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