Scholarlink

The growing interest in machine learning (ML) and deep learning (DL) applications for healthcare management has led to a plethora of research outputs. In this exploratory study, the state-of-the-art ML and DL applications in healthcare management are synthesized to provide an overview of the advancements, challenges, and future directions. A total of 65 studies were analyzed, focusing on four main categories: patient care, medical imaging, electronic health records, and healthcare operations. The review highlights the potential of ML and DL in improving healthcare outcomes and efficiency while emphasizing the need for further research to address concerns such as data privacy, model interpretability, and integration into clinical practice.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

An Exploratory Review of Machine Learning and Deep Learning Applications in Healthcare Management

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Narasimha Rao Vajjhala,
  • Philip Eappen

摘要

The growing interest in machine learning (ML) and deep learning (DL) applications for healthcare management has led to a plethora of research outputs. In this exploratory study, the state-of-the-art ML and DL applications in healthcare management are synthesized to provide an overview of the advancements, challenges, and future directions. A total of 65 studies were analyzed, focusing on four main categories: patient care, medical imaging, electronic health records, and healthcare operations. The review highlights the potential of ML and DL in improving healthcare outcomes and efficiency while emphasizing the need for further research to address concerns such as data privacy, model interpretability, and integration into clinical practice.