September 10, 2025DiagnosticsOpen Access

Machine Learning-Powered Smart Healthcare Systems in the Era of Big Data: Applications, Diagnostic Insights, Challenges, and Ethical Implications

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Authors

SRSita Rani RKRaman Kumar BPBhavani Sankar PandaGIET University

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Implication

This review synthesizes machine learning and big data's impact on diagnostics in smart healthcare systems, highlighting key challenges and ethical considerations.

Key Points

Enhanced diagnostic accuracy of up to 95% is achieved through the integration of machine learning in healthcare.
This review showcases applications like medical imaging and disease prediction, emphasizing the role of machine learning and big data.
The study identifies critical challenges in healthcare data, such as privacy, computational complexity, and data heterogeneity.
It explores emerging technologies, including wearables and IoMT, that support real-time data-driven healthcare delivery.

Cite This Study

Rani et al. (2025) studied this question.

synapsesocial.com/papers/68c23e02b210217d6478ffb2 https://doi.org/10.3390/diagnostics15151914

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Implication

This review synthesizes machine learning and big data's impact on diagnostics in smart healthcare systems, highlighting key challenges and ethical considerations.

Machine Learning-Powered Smart Healthcare Systems in the Era of Big Data: Applications, Diagnostic Insights, Challenges, and Ethical Implications

Discussion

Member takes

Implication

Key Points

Cite This Study

Machine Learning-Powered Smart Healthcare Systems in the Era of Big Data: Applications, Diagnostic Insights, Challenges, and Ethical Implications

Discussion

Member takes

Implication

Key Points

Cite This Study

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