A meta-study on optimizing healthcare performance with artificial intelligence and machine learning

B. Lainjo
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Abstract

This study explores the transformative impact of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare, focusing on enhancing patient care through operational efficiency and medical innovation. Employing a meta-study approach, it comprehensively analyzes the applications and ethical aspects of AI and ML in healthcare, highlighting successful implementations like IBM Watson for Oncology and Google DeepMind’s AlphaFold. The research emphasizes AI’s significant contributions to diagnostics, precision medicine, and medical imaging interpretation, alongside its role in optimizing healthcare operations and enabling personalized medicine through data analysis. However, it also addresses challenges such as algorithmic bias, safety, data privacy, and the need for regulatory frameworks. The study underlines the importance of continued research, interdisciplinary collaboration, and adaptive regulations to ensure the responsible and ethical use of AI and ML in healthcare.
利用人工智能和机器学习优化医疗保健绩效的元研究
本研究探讨了人工智能(AI)和机器学习(ML)在医疗保健领域的变革性影响,重点是通过运营效率和医疗创新加强对患者的护理。本研究采用元研究方法,全面分析了人工智能和 ML 在医疗保健领域的应用和伦理问题,重点介绍了 IBM Watson for Oncology 和 Google DeepMind's AlphaFold 等成功实施案例。研究强调了人工智能在诊断、精准医疗和医学影像解读方面的重大贡献,以及其在优化医疗运营和通过数据分析实现个性化医疗方面的作用。不过,它也提到了一些挑战,如算法偏差、安全性、数据隐私以及对监管框架的需求。该研究强调了持续研究、跨学科合作和适应性法规的重要性,以确保在医疗保健领域负责任地、合乎道德地使用人工智能和 ML。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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