REVIEW PAPER
From Big Data to Smart Health: Machine Learning Approaches Shaping the Future of Biomedicine.
1
Electric Power Research Institute, 1300 W W T Harris Blvd, Charlotte, NC, USA – 28262.
2
Lowe's Home Improvement, 1000 Lowe's Blvd, Mooresville, NC – 28117.
Submission date: 2025-09-16
Final revision date: 2025-11-17
Acceptance date: 2025-12-07
Online publication date: 2026-01-28
Publication date: 2026-01-28
Corresponding author
Journal of Medico Informatics 2026;2(1):1-11
HIGHLIGHTS
- Artificial intelligence transforms healthcare through predictive, personalized, and efficient medical systems.
- Foundation models and generative AI enhance diagnostics, research, and clinical decision-making.
- Digital twins enable personalized medicine, surgical planning, and real-time patient simulation.
- Quantum computing accelerates drug discovery, medical imaging analysis, and treatment optimization.
- AI-driven smart health systems improve remote monitoring, decision support, and outcomes.
KEYWORDS
Artificial Intelligence Machine LearningDigital TwinsPrecision MedicineClinical DecisionSupport SystemsHealth Care
TOPICS
ABSTRACT
The convergence of artificial intelligence, machine learning, and big data analytics continues to revolutionize healthcare delivery and biomedical research, creating unprecedented opportunities for precision medicine, enhanced diagnostic accuracy, and personalized therapeutic interventions. This comprehensive review examines the latest developments in AI-driven healthcare, incorporating breakthrough innovations from 2024 and 2025 that are fundamentally reshaping medical practice across diverse applications and clinical specialties. From generative AI and foundation models to digital twins, quantum computing, and ambient intelligence systems, these technologies are establishing new paradigms for healthcare delivery that prioritize predictive, personalized, and proactive medical care. The global AI healthcare market, valued at $20.9 billion in 2024, is projected to reach $148.4 billion by 2029, representing a compound annual growth rate of 48.1% and reflecting the transformative impact of these technologies across diagnostic imaging, clinical decision support, drug discovery, surgical robotics, and patient care delivery. Generative AI in healthcare is expected to reach $2.7 billion in 2024 and approximately $17 billion by 2034, while 85% of healthcare leaders are now exploring or have already adopted generative AI capabilities. These advancements represent a paradigm shift toward more intelligent, predictive, and personalized healthcare delivery systems that extend far beyond traditional machine learning applications. The integration of ambient intelligence technologies, robotic surgical systems, and Internet of Medical Things devices is creating comprehensive healthcare ecosystems that enhance both clinical outcomes and operational efficiency.
ACKNOWLEDGEMENTS
Not Applicable
FUNDING
Not Applicable
CONFLICT OF INTEREST
The authors declare that they have no known financial, personal, academic, or other relationships that could inappropriately influence, or be perceived to influence, the work reported in this manuscript. All authors confirm that there are no competing interests to declare.
PEER REVIEW INFORMATION
Article has been screened for originality
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