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Healthcare Startups Leading the Way in Medical Artificial Intelligence

Feb. 1, 2019
Kolabtree, the online platform for freelance scientists, has released an infographic highlighting startups that have developed innovative AI-assisted products that are advancing healthcare.

A recent report by CB Insights shows that healthcare artificial intelligence (AI) startups have raised $4.3 billion since 2013, topping all other industries. Kolabtree, the online platform for freelance scientists, has released an infographic highlighting startups that have developed innovative AI-assisted products that are advancing healthcare.

According to new research from ReportLinker. the AI in healthcare market expected to grow from $2.1 billion to $36.1 billion by 2025. This increase in value will be driven largely by North American investment, with the United States at the forefront of innovation and spending. 

Machine learning’s ability to collect and handle big data is fueling the growth of AI. Hospitals, research centers, pharmaceutical companies, and other healthcare institutions are increasing the adoption of artificial intelligence to improve patient health. The growing adoption of natural language processing in applications such as patient-data and risk analysis, lifestyle management and monitoring, and mental health is propelling the growth of this technology in the market.

The hospitals and providers segment is expected to hold the largest size of AI in healthcare market in terms of end-users. A few major factors are the large number of applications of AI solutions across provider settings; the ability of AI systems to improve care delivery, patient experience, and bring down costs; and growing adoption of electronic health records by healthcare organizations. AI-based tools, such as voice recognition software and clinical decision support systems, help streamline workflow processes in hospitals, lower cost, improve care delivery, and enhance patient experience.

The startups listed in the infographic are some of the companies leading the way in artificial intelligence for the medical industry. (Credit: Kolabtree)

Many of the AI-assisted healthcare products developed by startups are now being used in homes, hospitals, and clinics to improve people’s lives. Kolabtree has illustrated how these products use AI to improve healthcare, from drug discovery and diagnosis to treatment and service provision.

“We hear a lot about the work of big pharma companies, but the important contributions that startups make to the healthcare industry often go under the radar,” commented Ashmita Das, CEO of Kolabtree. “The big corporations often lack the research capabilities to develop AI-assisted products in-house, which is why many have partnered with startups in this sector.

“For example, pharmaceutical giant Merck works with Atomwise, a startup in the U.S. that uses deep learning to shorten the drug discovery process,” Das continued. “Also, GSK has entered into a partnership with a startup called Insilico Medicine, which uses AI to discover new biologic drugs.”

Consulting firm Frost & Sullivan has predicted a compound annual growth rate in the healthcare AI market of 40% through 2021, largely because AI has the potential to improve healthcare outcomes by 30 to 40% while halving treatment costs. Global Market Insights predicted an increase in the healthcare AI market value from $760 million in 2016 to $10 billion in 2024. Startups around the world will be pivotal in bringing these predictions to reality.

Kolabtree is an online platform that puts small businesses and research organizations in touch with freelance scientists. Users can post a project on the platform for free, receive bids from freelancers, interact with candidates, and hire a freelancer with the specific skills and experience required for the project.

More than 6,500 freelance scientists are registered with Kolabtree—many with PhDs and extensive experience in healthcare and medical research. They specialize in services such as data analytics, scientific consulting, medical writing, and experimental design.

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