American International Journal of Research and Innovation

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Intelligent Healthcare Analytics for Preventive Medicine Innovation

Author(s) Krit Pongpirul
Country Thailand
Abstract The transformation of healthcare systems from reactive treatment-oriented approaches toward preventive and predictive models has become increasingly important in addressing global health challenges. Traditional healthcare practices often focus on diagnosing and treating diseases after symptoms appear, whereas preventive medicine emphasizes early detection, risk assessment, and proactive intervention. Intelligent Healthcare Analytics has emerged as an advanced approach that integrates artificial intelligence, machine learning, big data analytics, and digital health technologies to support preventive medicine innovation.
This research examines intelligent healthcare analytics frameworks and their role in improving preventive healthcare strategies. The study adopts a conceptual research approach based on existing theoretical perspectives related to healthcare informatics, artificial intelligence, predictive analytics, personalized medicine, and digital health transformation.
The analysis highlights that intelligent healthcare analytics enables early disease prediction, personalized risk assessment, continuous health monitoring, and evidence-based clinical decision support. Advanced analytical systems can process diverse healthcare data sources, including electronic health records, medical imaging, wearable devices, and population health information, to identify potential health risks and support timely interventions.
The study identifies important challenges associated with intelligent healthcare analytics implementation, including data privacy concerns, algorithmic bias, interoperability limitations, ethical issues, and the need for healthcare workforce adaptation. Effective adoption requires secure data governance, transparent artificial intelligence systems, clinical validation, and responsible innovation practices.
The research concludes that intelligent healthcare analytics represents a significant pathway for advancing preventive medicine. Future healthcare ecosystems will increasingly depend on intelligent technologies that combine clinical expertise, data-driven insights, and patient-centred approaches to improve health outcomes and promote proactive disease prevention.
Keywords Intelligent Healthcare Analytics, Preventive Medicine, Artificial Intelligence, Predictive Healthcare, Digital Health, Machine Learning, Personalized Medicine.
Field Engineering
Published In Volume 8, Issue 3, May-June 2026
Published On 2026-06-28
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