在医疗分析中利用人工智能:从诊断到优化治疗

Tushar Khinvasara, Kimberly Morton Cuthrell, Nikolaos Tzenios
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引用次数: 0

摘要

人工智能(AI)在医疗分析中的应用为医疗领域的诊断和治疗优化带来了变革。人工智能技术通过结合大数据分析和先进的机器学习算法,在处理大量医疗数据和提取有价值的见解方面具有无与伦比的能力。人工智能算法为医疗保健专业人员提供了更高的准确性和更快的速度,帮助他们诊断疾病、预测病人的治疗结果,并在整个医疗保健过程中为病人量身定制治疗方案。本摘要探讨了人工智能(AI)如何在基因组学、电子健康记录(EHR)、医学影像和临床决策支持系统等多个领域彻底改变医疗分析。医疗保健提供商可以通过优化工作流程、提高患者疗效以及使用人工智能驱动的举措来改善医疗保健服务,从而使服务更便捷、更优质。为了确保在医疗保健领域合乎道德、负责任地使用人工智能,有必要解决算法偏差、数据隐私担忧和监管障碍等问题。尽管存在这些挑战,但人工智能技术的不断进步在改变患者护理模式和医疗服务方法方面具有巨大潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Harnessing Artificial Intelligence in Healthcare Analytics: From Diagnosis to Treatment Optimization
The use of artificial intelligence (AI) in healthcare analytics has brought about a transformation in the medical field of diagnosis and treatment optimization. AI technologies have unmatched abilities in processing substantial amounts of medical data and extracting valuable insights by combining big data analytics and advanced machine learning algorithms. AI algorithms provide healthcare professionals with enhanced accuracy and speed in diagnosing illnesses, predicting patient results, and tailoring treatment plans across the entire healthcare journey. This abstract explores how artificial intelligence (AI) can revolutionize healthcare analytics in various areas such as genomics, electronic health records (EHRs), medical imaging, and clinical decision support systems. Healthcare providers can improve healthcare services by optimizing workflows, enhancing patient outcomes, and using AI-driven initiatives to make services more accessible and high in quality. In order to ensure ethical and accountable use of AI in healthcare, it is necessary to address problems such as algorithm bias, data privacy worries, and regulatory obstacles. Despite these challenges, the ongoing advancement of AI technologies has vast potential to transform patient care models and healthcare delivery methods.
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