A new World Economic Forum report released yesterday brings to attention the transformative potential of artificial intelligence (AI) in healthcare and the key role public-private collaboration plays in ensuring its global adoption.
The report, Scaling Smart Solutions with AI in Health: Unlocking Impact on High-Potential Use Cases, aims to jumpstart public-private collaboration to speed up the responsible application of AI in healthcare.
It compiled analysis by more than 400 existing AI use cases as well as direct conversations with 50 global leaders across technology, healthcare delivery, biopharma, government, academia and more.
The report came in response to universal challenges incumbent on health systems worldwide and suggests a global taxonomy for healthcare AI uses, pointing to ways global healthcare systems could unlock the full potential of these new technologies to transform patient care, reduce costs and enable people to live healthier, longer lives.
“We are at a critical juncture in global health and healthcare, as mounting headwinds threaten collective wellness as well as employers, economies, budgets and societal resilience,” said Shyam Bishen, Head of the Centre for Health and Healthcare and Member of the Executive Committee at World Economic Forum.
“Closely governed advancements in AI are critical to supporting a broader digital and data-driven transition to intelligent healthcare systems, which can meet populations’ needs and transform healthcare outcomes, access, and efficiency.”
“The question is no longer whether the technology exists for AI to transform healthcare. It does,” added ZS Chief Executive Officer Pratap Khedkar. “The question is whether or not stakeholders can pull together to set the conditions for its widespread use and adoption. If adopted broadly and responsibly, AI holds the potential to radically transform healthcare systems and improve health outcomes for all.”
According to the report findings, AI potentially provides a diagnosis of a range of diseases at scale, helping to intervene at an early stage for individuals at greater risk, as well as deal with infectious diseases through AI-powered systems that can predict future outbreaks, while identifying their spread and deliver customized mitigation strategies to reduce their impact.
The report identified some barriers to AI adoption including insufficient high-quality data, low trust in AI solutions, and inadequate technological infrastructure.
These obstacles can be overcome when Public-private support for creating a strong data foundation and improved privacy laws are put in place to adopt these technologies at scale.
Personalized AI treatment
Mihaela van der Schaar, the John Humphrey Plummer professor for machine learning, AI and medicine, and director of the Cambridge Centre for AI in Medicine at the University of Cambridge believes that using AI-powered personalized medicine could allow for more effective treatment of common conditions such as heart disease and cancer, or rare diseases such as cystic fibrosis.
“It could allow clinicians to optimize the timing and dosage of medication for individual patients, or screen patients using their individual health profiles, rather than the current blanket criteria of age and sex. This personalized approach could lead to earlier diagnosis, prevention, and better treatment, saving lives and making better use of resources,” Schaar told British media.
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