The development of PharmBot AI and HealthAI Assist is grounded in extensive research and insights from leading studies in the field of artificial intelligence and healthcare. The following references have been meticulously selected to provide a comprehensive understanding of the advancements, applications, and potential of AI in transforming pharmacy practice and patient care.
These studies highlight the convergence of AI and healthcare, the implementation challenges, and the promising outcomes of personalised medicine, all of which contribute to the foundational principles and objectives of PharmBot AI and HealthAI Assist.
1. Topol, E. J. (2019)
High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine, 25(1), 44-56.
This study discusses the integration of AI in various aspects of healthcare, emphasizing its potential to improve patient outcomes and streamline operations, which is a core aim of PharmBot AI.
2. Hinton, G. (2018)
Deep Learning—A Technology With the Potential to Transform Health Care. JAMA, 320(11), 1101-1102.
Explores the transformative capabilities of deep learning in healthcare, a technology that underpins many AI-driven solutions like HealthAI Assist.
3. Bates, D. W., Saria, S., Ohno-Machado, L., Shah, A., & Escobar, G. (2014)
Big Data in Health Care: Using Analytics to Identify and Manage High-Risk and High-Cost Patients. Health Affairs, 33(7), 1123-1131.
Reviews how big data and analytics can improve healthcare management, directly relating to how HealthAI Assist uses data to optimise pharmacy operations.
4. Zhu, H., & Liu, J. (2020)
Personalised Medication Management Through Artificial Intelligence. Journal of Pharmacy Practice, 33(2), 179-185.
Covers personalised medication management, which is a core feature of HealthAI Assist, enhancing patient care through tailored solutions.
5. Krittanawong, C., Rogers, A. J., Johnson, K. W., Wang, Z., Aydar, M., & Kitai, T. (2017)
Artificial Intelligence in Precision Cardiovascular Medicine. Journal of the American College of Cardiology, 69(21), 2657-2664.
Illustrates the potential of AI to provide precise and tailored medical interventions, similar to the objectives of HealthAI Assist in pharmacy practice.
6. Shaw, J., Rudzicz, F., Jamieson, T., & Goldfarb, A. (2019)
Artificial Intelligence and the Implementation Challenge. Journal of Medical Internet Research, 21(7), e13692.
Addresses the implementation challenges of AI in healthcare settings, relevant to the ongoing development and future research efforts for HealthAI Assist.
7. Tschandl, P., Rinner, C., Apalla, Z., Argenziano, G., Codella, N., Halpern, A., … & Kittler, H. (2020)
Human–computer collaboration for skin cancer recognition. Nature Medicine, 26(8), 1229-1234.
Showcases how AI can collaborate with healthcare professionals to enhance diagnostic accuracy, paralleling the collaborative potential of HealthAI Assist in pharmacy practice.
8. Zhang, Z., Zhang, H., & Yu, Y. (2021)
Advances in Artificial Intelligence Applications in Healthcare. Journal of Healthcare Engineering, 2021, 1-10.
A comprehensive review of recent advances in AI applications in healthcare, supporting the innovative approach of HealthAI Assist.
These studies provide valuable insights and evidence supporting the design and development of PharmBot AI and HealthAI Assist, showcasing their potential to revolutionise pharmacy practice through AI-driven solutions.