Evaluating the Effectiveness of Artificial Intelligence in Advancing Healthcare Quality: A Systematic Review

Abstract

AI provides a workable solution in healthcare for enhancing patient care, improving diagnostic precision, allocating resources and optimising services as possible. AI can improve healthcare delivery system by utilising machine learning algorithms and predictive analytics in various domains, including patient management and disease detection. However, issues about privacy, data security, and ethical consequences have been highlighted in the increasing usage of AI in healthcare. Clear legal frameworks and norms must be in place to guarantee the accountable integration of AI technology in healthcare settings. This systematic study conducted a thorough literature search across electronic databases to assess the usefulness of AI in improving healthcare quality. Systematic reviews, meta-analyses, crosssectional research, and qualitative meta-syntheses concentrating on AI applications and their influence on healthcare quality were among the selection criteria. Data extraction and quality assessment adhered to established protocols were used to validate and ensure the reliability of the studies included. Synthesized findings from the selected studies revealed significant insights into AI's potential benefits and challenges in healthcare. AI tools, such as ordinary linguistic processing and machine learning, have shown promising impact on patient outcomes, personalised therapy, and diagnostic accuracy. However, incorporating AI into healthcare systems requires careful thought because issues like data theft, moral quandaries, and possible financial ramifications are persistent. Despite challenges, AI can enhance healthcare quality by optimising resource allocation, supporting clinical decision-making, and improving patient care efficiency. Prioritizing ethical and regulatory considerations is needed to unlock AI's full potential in healthcare and guarantee equitable access to its advantages.

Ähnliche Arbeiten