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Issues And Trends In Healthcare Delivery System01:29

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Updated: Mar 13, 2026

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
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Artificial Intelligence Applications in Medical Devices for Personalized Health Care Solutions: Systematic Review.

Hemanth Ponnambalath Mohanadas1, A Manikandan2, Ahmad Fauzi Ismail3

  • 1Device Development, Abbott Diabetes Care, Alameda, CA, United States.

Journal of Medical Internet Research
|March 11, 2026
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) in medical devices personalizes treatment for better outcomes. Addressing data quality, bias, and regulations is key for AI

Keywords:
artificial intelligencedigital healthmedical devicespersonalized medicinepredictive analytics

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Area of Science:

  • Medical Technology
  • Artificial Intelligence
  • Personalized Medicine

Background:

  • AI integration in medical devices enhances personalized and precision medicine.
  • AI tailors treatments using patient data (genetics, history, physiology).
  • Challenges include data quality, bias, privacy, and regulatory hurdles.

Purpose of the Study:

  • Explore AI-driven personalization in medical devices.
  • Analyze innovations, challenges, and strategies for AI integration.
  • Highlight future research and innovation opportunities.

Main Methods:

  • Systematic review of literature, industry analyses, and regulatory advisories (2016-2023).
  • Analysis of over 100 peer-reviewed articles and reports.
  • Examination of ethical, technical, and regulatory considerations.

Main Results:

  • AI advancements in diagnostics (e.g., 98.88% accuracy in X-ray classification) and treatment personalization.
  • Key challenges identified: data security, algorithmic bias, regulatory constraints.
  • AI automation can reduce diagnostic delays by up to 50%.

Conclusions:

  • AI in medical devices offers precise, adaptive, patient-centered healthcare solutions.
  • Addressing technical, ethical, and regulatory challenges is crucial for implementation.
  • Emerging tech like quantum computing and blockchain can enhance AI capabilities.