ARTIFICIAL INTELLIGENCE IN HEALTHCARE

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University of the Cumberlands *

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534

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Health Science

Date

Nov 24, 2024

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docx

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Uploaded by MateGerbilMaster994

ARTIFICIAL INTELLIGENCE IN HEALTHCARE Student’s Name Institution Date of Submission

Rapid technological advancement has led to convenient patient management strategies. Thus, emerging technology implications have been discussed. Good and poor results are expected, but people prefer the better one. Therefore, data grouping approaches can solve complex algorithms (Jiang et al., 2017). Software in patient management helps providers discover patients who need more attention, improving care. The Socratic approach helps identify problem-solving strategies. The goal of this method is to encourage critical thinking and discourage snap judgments. Thus, the discourse addresses public health AI via the Socratic Method. Public health providers collect and analyse local health data. Based on this data, medical help is determined. They also participate in vaccine development and disease epidemic reduction studies (Jiang et al., 2017). Public health programs are crucial because they monitor health concerns and implement adequate protections. Healthcare workers give immunizations, screenings, and infection control to the public. The participants' expertise and abilities have contributed to life-saving initiatives and programs while working with local clinics on rehabilitation. Fostering a thriving environment helps people give their best services. Several businesses use AI to solve complex problems. Because medicine has many subfields, technological breakthroughs have enabled solutions that speed up patient recovery. AI has advanced in the caregiving field, but professionals have only begun to use it. This is primarily because genuine people make people feel better than robots or other automated systems. Big data and the Internet of things simplify record keeping, letting hospitals spot issues. (Yu, Beam, and Kohane 2018) found that doctors need much time to diagnose patients' medical issues. Artificial intelligence may help apply corrective procedures for effective patient care. Advanced algorithmic technology has created new moral dilemmas that must be addressed. Technology increases patient privacy and confidentiality risks, creating an ethical

issue. Patient data is subject to breaches despite the need for proper diagnosis evaluation. Machine learning algorithms and frameworks could access and distribute patient data without consent. Humans created these machines, and following their algorithms can fix any issues. Machine learning errors can change patient records. Thus, the computer cannot fully protect patient data. Treating some patients like robots is unethical. Due to ethical considerations and personal preferences, most people prefer medical care over technology. Staff must recover quickly to help patients. Medical care improves. It is crucial to invest in medical tool development and distribution. Critical thinking can be improved by playing games requiring careful consideration and evaluation before deciding (Yu, Beam, and Kohane 2018). Hospitals are planning ways to reduce staffing shortages to improve staff competency and patient care. Lack of medical job opportunities may deter many people from pursuing a career. However, people are necessary because the system will always fail and cause problems. The debate over artificial intelligence continues without a clear answer. In conclusion Healthcare dramatically improves the quality of life. They serve many objectives that improve people's well-being. Healthcare practitioners advise people on preventing and treating illness and providing acute medical care. Sharing knowledge and experience improves diagnosis accuracy. Thus, patients receive prompt care. They should be vital to every nation's healthcare. Healthcare workers must treat patients properly to help them recover and enhance community health. However, healthcare experts are vital and must have legal permits from authorized authorities. This makes it easy for doctors to treat patients and ensures high-quality care. Reference

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Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., ... & Wang, Y. (2017). Artificial intelligence in healthcare: past, present and future. Stroke and vascular neurology, 2(4), 230- 243. Yu, K. H., Beam, A. L., & Kohane, I. S. (2018). Artificial intelligence in healthcare. Nature biomedical engineering, 2(10), 719

ARTIFICIAL INTELLIGENCE IN HEALTHCARE

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