RDIGI WORKS
Artificial Intelligence and Machine Learning

Artificial Intelligence in Healthcare

Rdigi Works
International Journal of Emerging Technologies 2020 22 Citations

Abstract

This study investigates the impact of AI-driven technologies on healthcare systems, emphasizing the role of machine learning in diagnostics, drug discovery, and patient monitoring. By analyzing global case studies, it highlights both opportunities and challenges, including data privacy and ethical concerns.


  1. Artificial Intelligence (AI) has become a driving force in the healthcare industry, enabling early detection of diseases, reducing operational costs, and improving patient outcomes.
    Key contributions of AI include:

  1. Enhanced image recognition for diagnostics (MRI, CT scans).

  2. Predictive modeling for disease outbreaks.

  3. Drug discovery through deep learning algorithms.

  4. Patient engagement using chatbots and virtual assistants.

Despite these advances, challenges like data security, algorithmic bias, and high implementation costs remain. The research concludes that collaboration between medical professionals and AI experts is essential to unlock AI’s full potential in healthcare.

ISSN

2456-7890

Published Date

August 2, 2025

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How to Cite This Study

Rdigi Works (2020). "Artificial Intelligence in Healthcare". International Journal of Emerging Technologies. DOI: 10.1234/example.doi.2025