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Machine learning (ML) is set to transform healthcare by enhancing services and improving patient outcomes. This overview outlines its applications, challenges, and future possibilities. Techniques like deep learning and predictive analytics can process vast amounts of healthcare data, resulting in more precise diagnoses and tailored treatment plans. Nevertheless, issues such as data privacy, regulatory compliance, and algorithmic bias need to be tackled through collaboration among various stakeholders. Future advances in machine learning are expected to further improve healthcare delivery. By leveraging machine learning, stakeholders can improve diagnostic accuracy and optimize treatment strategies, transforming the healthcare experience for individuals around the world.

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An Overview of the Machine Learning Algorithms in Healthcare Data Analysis

  • 会议论文

  • 发表日期：

    2026年

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  • Amine Belmzoukia,
  • Kaoutar Chahbari,
  • Mohammed Ouhsine,
  • Jaafar Abouchabaka,
  • Najat Rafalia

摘要

Machine learning (ML) is set to transform healthcare by enhancing services and improving patient outcomes. This overview outlines its applications, challenges, and future possibilities. Techniques like deep learning and predictive analytics can process vast amounts of healthcare data, resulting in more precise diagnoses and tailored treatment plans. Nevertheless, issues such as data privacy, regulatory compliance, and algorithmic bias need to be tackled through collaboration among various stakeholders. Future advances in machine learning are expected to further improve healthcare delivery. By leveraging machine learning, stakeholders can improve diagnostic accuracy and optimize treatment strategies, transforming the healthcare experience for individuals around the world.