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A Study on Application of Machine Learning in Modern Healthcare for Improved Diagnosis and Treatment K

  • Unique Paper ID: 171333
  • Volume: 11
  • Issue: 7
  • PageNo: 3639-3645
  • Abstract:
  • Modern healthcare could undergo a revolution in diagnosis and treatment approaches with the incorporation of machine learning (ML). This paper examines how machine learning (ML) can be used in a variety of ways to improve diagnostic efficiency and accuracy, providing notable benefits over conventional techniques. ML algorithms in particular, deep learning models are being used more and more in imaging diagnostics, illness risk prediction, and pattern recognition in complicated datasets to increase the accuracy of early diagnosis and prognosis. Additionally, the study explores how ML plays a critical role in facilitating individualized treatment plans by utilizing patient-specific data to maximize therapeutic results, hence meeting the increasing need for customized healthcare solutions. The study also looks into important issues and moral dilemmas that impede the smooth integration of ML technology in healthcare, including algorithmic bias, data privacy violations, and regulatory compliance. These obstacles highlight the need for strong data governance structures and moral AI procedures. In order to promote sustainable ML integration, techniques for resolving these problems are also suggested, such as open algorithm design and cooperative stakeholder participation. (Statista Report,2024). This study demonstrates ML's ability to address the drawbacks of conventional healthcare approaches, including inefficiencies in manual diagnosis and treatment planning, through a thorough review. Important tactics are noted as being essential for successful deployment, such as collaborations with technology suppliers and investments in scalable machine learning infrastructure. (McKinsey Healthcare Survey, Q1 2024). The results address the concerns of machine learning while highlighting its revolutionary effects on healthcare delivery. This paper provides a road map for technologists, legislators, and healthcare professionals who want to use machine learning to improve patient outcomes. In order to guarantee moral, just, and scalable applications in international healthcare settings, future research should concentrate on improving machine learning models.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 7
  • PageNo: 3639-3645

A Study on Application of Machine Learning in Modern Healthcare for Improved Diagnosis and Treatment K

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Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

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