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One in four Singaporeans will become 65 years of age or older by 2030. Singapore is an ageing people. Nurses are in short supply, and facilities are having trouble filling critical positions like radiographers and pharmacists, which is causing a labor shortage in the healthcare industry.
The World Health Organization stated on October 19 that, if correctly interpreted, AI tools” could transform the health sector” when outlining the factors for AI regulation in healthcare. These tools complement the knowledge, skills, and talents of medical professionals and provide improvements to medical diagnosis, treatment, or self-care.
Whether AI represents a trend or an advancement in medical practice is debatable. We can all agree, though, that the use of AI types at the patient’s side is starting to pay off. There are many examples of how machine learning algorithms with strong forecast power have become a crucial new tool in the medical industry’s toolkit for enhancing patient care. The use of AI designs in health care delivery is only going to grow.
The public needs to be kept informed in general words about how the health system is changing to better serve them. These changes come with significant tasks. It is also necessary to address different issues that AI models present when used in healthcare, such as bias risks and ambiguities regarding expert, lawful, and ethical accountability for errors.
Meeting these basic requirements does not, however, imply that the current info disclosure procedures in patient care need to be overhauled. AI is hardly remarkable when it comes to choosing the information that should be given to patients.
At the National University of Singapore’s Yong Loo Lin School of Medicine, Dr. Michael Dunn teaches as an associate professor in the center for medical morality. Dr. Liu Nan is an Associate Professor at Duke – NUS Medical School’s Centre for Quantitative Medicine.