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ISSN 2063-5346
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A COMPREHENSIVE AND CRITICAL REVIEW OF ARTIFICIAL INTELLIGENCE (AI) IN PHARMACY, NURSING, LABORATORY, AND MEDICAL FIELDS

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Mohammed Saed Al-Harthi, Mohammed Talal Al-Sulaimani, Fahad Abduallah Al-Zahrani, Adel Hulayyil Al-Harthi, Sultan Abdullah Al-Harthi, Ibrahim Awadh Al-Hamyani, Marwa Shalan Al-Dhafeeri, Saleh Jabbar Al-Zahrani, Saeed Ahmed Al-Zahrani, Sabah Abdulrahman Al-Abrash, Ashwaq Abdulhamid Al-Ahmadi, Shahd Ishag Khan, Reyoof Jabr Al-Abbas, Saeed Ali Alqahtani, Ibrahim Mohammed Al-Helali, Hamed Nawar Alharthi, Ibrahim Mohammed Dighriri
» doi: 10.53555/ecb/2022.11.7.74

Abstract

Artificial Intelligence (AI) has emerged as a transformative technology with immense potential to revolutionize various healthcare and patient care aspects. This comprehensive review article explores the current state of AI in different medical fields, including pharmacies, nursing, laboratories, and medical practice. This review critically analyzes AI applications, benefits, challenges, and prospects in these domains. The literature search strategy included electronic databases, such as PubMed, Scopus, Web of Science, and Google Scholar, focusing on articles published in English. This review discusses the impact of AI on drug discovery and development, pharmacy operations and inventory management, medication adherence, patient monitoring, clinical decision support, and personalized medicine in the pharmacy field. AI's role in clinical decision support, patient monitoring and predictive analytics, nursing education and training, workflow optimization, and resource allocation is examined in nursing. The laboratory section explores AI's applications of AI in automated experimental design and optimization, data analysis and pattern recognition, robotics and automation, and predictive maintenance and quality control. The medical field section delves into AI's impact of AI on radiology, pathology, and ophthalmology, highlighting the use of convolutional neural networks (CNNs) and deep learning (DL) algorithms in image analysis and disease diagnosis. The review also addresses the challenges and ethical considerations associated with AI's integration of AI in these medical fields, such as data privacy, security, algorithmic biases, and the need for standardization and validation. The prospects of AI in healthcare are discussed, emphasizing the potential of AI to transform healthcare delivery and patient care. The review concludes by acknowledging the need for further research and development to address the challenges and ethical implications associated with its implementation and instilling a sense of optimism about the future of healthcare with AI.

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