Advances in Machine Learning Models for Healthcare Applications: A Precise and Patient-Centric Approach.

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Tác giả: Kalpana, Rishabha Malviya, Bhumika Parashar, Bhupendra G Prajapati, Sathvik Belagodu Sridhar, Prerna Uniyal

Ngôn ngữ: eng

Ký hiệu phân loại: 518.6 Numerical methods in analysis

Thông tin xuất bản: United Arab Emirates : Current pharmaceutical design , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 57751

BACKGROUND: Healthcare is rapidly leveraging machine learning to enhance patient care, streamline operations, and address complex medical issues. Though ethical issues, model efficiency, and algorithmic bias exist, the COVID-19 pandemic highlighted its usefulness in disease outbreak prediction and treatment optimization. AIM: This article aims to discuss machine learning applications, benefits, and the ethical and practical challenges in healthcare. DISCUSSION: Machine learning assists in diagnosis, patient monitoring, and epidemic prediction but faces challenges like algorithmic bias and data quality. Overcoming these requires high-quality data, impartial algorithms, and model monitoring. CONCLUSION: Machine learning might revolutionize healthcare by making it more efficient and better for patients. Full acceptance and the advancement of technologies to improve health outcomes on a global scale depend on resolving ethical, practical, and technological concerns.
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