Description
文章探讨了将机器学习应用于医疗实践的日益增长的趋势，强调其在改善疾病诊断和预测方面的潜力。文章解释了机器学习模型如何通过识别复杂模式来辅助医生，这些模式是人类医生难以察觉的，从而可能节约资源并挽救生命。然而，作者对这些模型的广泛部署提出了严重的担忧，特别指出它们可能污染电子健康记录 (EHR) 中的数据。这种污染是由于成功的干预措施导致模型预测的结果与实际发生的情况不符，从而扭曲了训练和评估未来模型所需的数据可靠性。最终，文章强调了解决这些数据完整性挑战的重要性，以确保医疗领域人工智能的长期可靠性和有效性。
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