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Issues And Trends In Healthcare Delivery System01:29

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
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Big Data, Machine Learning, and Personalization in Health Systems: Ethical Issues and Emerging Trade-Offs.

Stefano Canali1, Alessandro Falcetta2, Massimo Pavan2

  • 1Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy. stefano.canali@polimi.it.

Science and Engineering Ethics
|October 13, 2025
PubMed
Summary
This summary is machine-generated.

Big data and machine learning in health systems offer personalization but raise ethical concerns. Personalized models for glucose monitoring reveal trade-offs, showing personalization isn't always beneficial.

Keywords:
AI ethicsBig dataHealth systemsMachine learningPersonalization

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Area of Science:

  • Health Informatics
  • Artificial Intelligence
  • Data Science

Background:

  • Big data and machine learning (ML) are increasingly used in health systems.
  • Ethical issues and societal implications are widely discussed.
  • Personalization in healthcare holds significant promise.

Purpose of the Study:

  • To examine the use of big data and ML for personalization in health systems.
  • To identify challenges and trade-offs associated with personalized health models.
  • To evaluate whether personalization is always a positive development in healthcare.

Main Methods:

  • Focus on concrete applications of personalized models.
  • Analysis of personalized models for glucose monitoring.
  • Analysis of personalized models for anomaly detection.

Main Results:

  • Personalized models can introduce new and exacerbated issues.
  • Personalization in health systems is not universally beneficial.
  • Identified trade-offs between personalization benefits and emerging problems.

Conclusions:

  • The pursuit of personalization in health systems requires careful consideration of its downsides.
  • New ethical concerns arise from personalized big data and ML applications.
  • Strategies for mitigation are needed to address the challenges of personalized health models.