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AI in Healthcare: Transforming Patient Care, Diagnosis, And Treatment

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  • Mohammed Nadeem Ansari
  • Nazia Tasleem

Abstract

Artificial Intelligence (AI) is revolutionizing modern healthcare by significantly enhancing clinical decision-making, streamlining operational workflows, and delivering advanced, patient-centered care (Smith & Zhao, 2021). This research article explores AI's pivotal role in contemporary healthcare systems, focusing on its ability to improve diagnostic accuracy, support personalized treatment planning, and enable predictive outcome modeling (Johnson et al., 2020). In particular, it examines the practical applications of AI in analyzing medical imaging, screening electronic health records (EHRs), conducting predictive analytics, and providing virtual health support each addressing persistent challenges in medical practice (Lee & Chen, 2019; Thomas & Arora, 2022). The study also evaluates the obstacles hindering AI's widespread integration, including ethical dilemmas, technical limitations, and regulatory challenges related to data privacy, algorithmic bias, and system compatibility (Nguyen, 2020; Patel & Green, 2023). Furthermore, the article explores the future trajectory of AI in healthcare, emphasizing the necessity for interdisciplinary collaboration between healthcare professionals and technology developers. Such cooperation is essential to harness AI’s full potential while safeguarding patient rights and promoting equitable access to high-quality healthcare services (Martin & Davis, 2021).

Suggested Citation

  • Mohammed Nadeem Ansari & Nazia Tasleem, 2024. "AI in Healthcare: Transforming Patient Care, Diagnosis, And Treatment," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 6(1), pages 727-744.
    • Handle: RePEc:das:njaigs:v:6:y:2024:i:1:p:727-744:id:353
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    References listed on IDEAS

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    1. Johannes Habel & Sascha Alavi & Nicolas Heinitz, 2023. "A theory of predictive sales analytics adoption," AMS Review, Springer;Academy of Marketing Science, vol. 13(1), pages 34-54, June.
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