Healthcare AI: prepared for the real-world?

  • The role faced by many organisations today is how to resolve the challenges presented by human-machine mediation, as AI and ML are increasingly used in healthcare to solve problems.

  • Experts in different fields agree that AI can be leveraged to save lives by constructive practises and patience in process improvement,**

Artificial intelligence ( AI) has a tremendous opportunity to advance healthcare as more and more data becomes available, from reducing the burden of back-office admin to providing life-saving potential in diagnosis and treatment recommendations.

A global demand estimated to be worth US$ 19.25 billion by 2026 provides this new frontier. But it is approached with a strong dose of caution as well. As organisations aim to harness the potentially enormous healthcare benefits of AI, the risk of underestimating how to safely and efficiently incorporate these instruments alongside human medical professionals remains a key challenge in tapping its full potential.

AI in healthcare: ready for the real-world?

Professor Samuel Kaski is a computer science expert at Finland’s Aalto University “Far from resembling futuristic artificial intelligence myths, Prof Kaski told TechHQ,” they can be very down-to - earth mathematical methods of computation, implemented at best in a way that can be more easily generalised to new problems. “And he said, many medical research activities now involve machine learning as a” almost normal ingredient. But there is still a gap in human-machine mediation and effective application in the integration of technology in the heat of ‘real-world’ healthcare environments, despite many models that can still perform, if not better, than medical professionals. Read More From Source

When it comes to our health, especially in matters of life and death, the promise of artificial intelligence (AI) to improve outcomes is very intriguing. While there is still much to overcome to achieve AI-dependent health care, most notably data privacy concerns and fears of mismanaged care due to machine error and lack of human oversight, there is sufficient potential that governments, tech companies, and healthcare providers are willing to invest and test out AI-powered tools and solutions.

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