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Exploring the Impact of Artificial Intelligence in Healthcare

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  • Md. Mafiqul Islam

Abstract

The integration of artificial intelligence (AI) applications has revolutionized healthcare. This study conducts a comprehensive literature review to elucidate the multifaceted role of AI in healthcare, focusing on key aspects including medical imaging and diagnostics, virtual patient care, medical research and drug discovery, patient engagement and compliance, rehabilitation, and administrative applications. AI's impact is observed across various domains, including detecting clinical conditions in medical imaging, early diagnosis of coronavirus disease 2019 (COVID-19), virtual patient care utilizing AI-powered tools, electronic health record management, enhancing patient engagement and treatment compliance, reducing administrative burdens for healthcare professionals (HCPs), drug and vaccine discovery, identification of medical prescription errors, extensive data storage and analysis, and technology-assisted rehabilitation. However, the integration of AI in healthcare encounters several technical, ethical, and social challenges, such as privacy concerns, safety issues, autonomy and consent, cost considerations, information transparency, access disparities, and efficacy uncertainties. Effective governance of AI applications is imperative to ensure patient safety, accountability, and to bolster HCPs' confidence, thus fostering acceptance and yielding significant health benefits. Precise governance is essential to address regulatory, ethical, and trust concerns while advancing the adoption and implementation of AI in healthcare. With the onset of the COVID-19 pandemic, AI has sparked a healthcare revolution, signaling a promising leap forward to meet future healthcare demands.

Suggested Citation

  • Md. Mafiqul Islam, 2024. "Exploring the Impact of Artificial Intelligence in Healthcare," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 2(1), pages 228-238.
  • Handle: RePEc:das:njaigs:v:2:y:2024:i:1:p:228-238:id:109
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