AI could revolutionize medical research, but requires careful approach



PRI ESPL INT .MELBOURNE TGA1 AI-MEDICAL RESEARCH AI promises to revolutionize medical research, but requires a cautious approach Reece Hooker, Assistant Producer, Asia Pacific, 360info Melbourne, August 1 (360info) Social media users of the week are generating and using AI shares interesting images, and next we hear that AI can predict the structure of over 200 million proteins. Artificial intelligence is particularly well suited to revolutionize medical research. The technology helps in two important ways: it optimizes research, and it can make discoveries that humans don’t. AI is not limited by human researchers: it can search deep datasets at exponential speed, never needing to rest, and never succumbing to illness or fatigue. Taiwanese computer scientist, businessman and author Kai-Fu Lee recently spoke about his optimism about the future of artificial intelligence. We were amazed at the effect of machine learning algorithms. It allows us to focus on what AI cannot, and it may lead to a deeper understanding of the mysteries of the human way of thinking, or it may lead to more breakthroughs leading to superintelligence. It took 40 years, but I think we’re basically there. That doesn’t mean the rise of machines is imminent. Despite the progress, AI is still hampered by technological limitations. Artificial intelligence pioneer Yosua Bengio said in 2021 that deep learning today is nowhere near the intelligence level of a two-year-old. A study by Pugliese et al. (2021) found that more and more medical research refers to “machine learning”. But maybe we have the equivalent of lower animal algorithms for perception. “We’re climbing the ladder in terms of tools that allow entities to explore their environment,” he said. More work needs to be done to perfect the technology, and there is no foreseeable date when humans will become redundant in medical research. There are also ethical issues in AI, and lawmakers will have to untangle a minefield of issues ranging from data collection to intellectual property. At the same time, leading minds continue to use machine learning and artificial intelligence to innovate and expand the possibilities of medical research. Reality Check Between 2000 and 2019, the research community became more interested in AI: the global output of AI research grew from 52,000 journal publications and conference papers in 2000 to approximately 403,000 in 2019. Artificial intelligence is expected to contribute $15.7 trillion to the global economy in 2030. Nine out of 100 healthcare executives surveyed in 2020 said their hospitals have an AI and automation strategy in place. BIG IDEAS “The goal and expectation is that when artificial intelligence is fully integrated into the study of disease development, many unknowns will become known. The causes of disease spread, deterioration, and changes, as well as other early signs or symptoms that research has not yet uncovered, It should be revealed to make themselves possible with new areas created by automated AI,” said Hiroaki Kitano of the Okinawa Institute of Science and Technology. “The application of artificial intelligence in medical decision-making is still new, and there are many hurdles to overcome before it can be widely used in clinical practice. In order to fully realize its capabilities, broader research and a more rigorous approach to addressing the ethical issues it presents. This is an ideal time for medical professionals, stakeholders and governments, as well as individuals and their families, to work together and find a balance between the benefits and risks of new technologies,” said Alexander Merkin from Auckland University of Technology. (360info) AM 08011017 NNNN

(Only the title and images of this report may have been modified by Business Standards staff; the rest of the content was automatically generated from the syndicated feed.)

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