Secure and Explainable AI for Precision Medicine: Big Data Integration of Genomics, Wearable Systems, and Predictive Health Outcomes
The quick process of digitization of the healthcare system and high-dimensional biomedical data reveal constraints in the context of traditional population-based decision-making. The similar gaps are tackled by accuracy medicine which incorporates every biological, clinical, and behavioral information at the individual level. It is possible through artificial intelligence and big data analytics to conduct multi-omics data, electronic health records, medical imaging, and wearable sensor analyses on a scalable basis. This paper is a data-driven and systematic review of big data analytics based on AI in the field of precision medicine, with a focus on predictive, preventive, and personalized care. Results demonstrate that combined AI systems are more efficient than independent approaches in disease stratification, real time-based, and clinical decision support, and determine problems of scalability, interpretability, privacy, and ethical control.
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Precision Medicine, Artificial Intelligence, Big Data Analytics, Multi-omics Integration, Wearable Health Systems, Predictive Modeling, Federated Learning
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(1) Habibullah Faisal
Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Japan.
(2) Tisha Farhana
Universiti Tun Hussein Onn Malaysia, Parit Raja, Johor Darul Ta'zim, Malaysia.
Cite this article
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APA : Faisal, H., & Farhana, T. (2021). Secure and Explainable AI for Precision Medicine: Big Data Integration of Genomics, Wearable Systems, and Predictive Health Outcomes. Global Pharmaceutical Sciences Review, VI(II), 15-30. https://doi.org/10.31703/gpsr.2021(VI-II).02
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CHICAGO : Faisal, Habibullah, and Tisha Farhana. 2021. "Secure and Explainable AI for Precision Medicine: Big Data Integration of Genomics, Wearable Systems, and Predictive Health Outcomes." Global Pharmaceutical Sciences Review, VI (II): 15-30 doi: 10.31703/gpsr.2021(VI-II).02
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HARVARD : FAISAL, H. & FARHANA, T. 2021. Secure and Explainable AI for Precision Medicine: Big Data Integration of Genomics, Wearable Systems, and Predictive Health Outcomes. Global Pharmaceutical Sciences Review, VI, 15-30.
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MHRA : Faisal, Habibullah, and Tisha Farhana. 2021. "Secure and Explainable AI for Precision Medicine: Big Data Integration of Genomics, Wearable Systems, and Predictive Health Outcomes." Global Pharmaceutical Sciences Review, VI: 15-30
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MLA : Faisal, Habibullah, and Tisha Farhana. "Secure and Explainable AI for Precision Medicine: Big Data Integration of Genomics, Wearable Systems, and Predictive Health Outcomes." Global Pharmaceutical Sciences Review, VI.II (2021): 15-30 Print.
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OXFORD : Faisal, Habibullah and Farhana, Tisha (2021), "Secure and Explainable AI for Precision Medicine: Big Data Integration of Genomics, Wearable Systems, and Predictive Health Outcomes", Global Pharmaceutical Sciences Review, VI (II), 15-30
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TURABIAN : Faisal, Habibullah, and Tisha Farhana. "Secure and Explainable AI for Precision Medicine: Big Data Integration of Genomics, Wearable Systems, and Predictive Health Outcomes." Global Pharmaceutical Sciences Review VI, no. II (2021): 15-30. https://doi.org/10.31703/gpsr.2021(VI-II).02
