Department of Human Genetics, University of Michigan, Ann Arbor, Michigan, USA.
Department of Science, University of Western Ontario, London, Ontario, Canada.
Clin Transl Sci. 2023 Nov;16(11):2106-2111. doi: 10.1111/cts.13619. Epub 2023 Aug 30.
Artificial intelligence (AI) utilization in health care has grown over the past few years. It also has demonstrated potential in improving the efficiency of diagnosis and treatment. Some types of AI, such as machine learning, allow for the efficient analysis of vast datasets, identifying patterns, and generating key insights. Predictions can then be made for medical diagnosis and personalized treatment recommendations. The use of AI can bypass some conventional limitations associated with rare diseases. Namely, it can optimize traditional randomized control trials, and may eventually reduce costs for drug research and development. Recent advancements have enabled researchers to train models based on large datasets and then fine-tune these models on smaller datasets typically associated with rare diseases. In this mini-review, we discuss recent advancements in AI and how AI can be applied to streamline rare disease diagnosis and optimize treatment.
人工智能(AI)在医疗保健领域的应用在过去几年中得到了迅猛发展。它也展现出了提高诊断和治疗效率的潜力。某些类型的 AI,如机器学习,允许对大量数据集进行高效分析,识别模式,并生成关键见解。然后可以对医疗诊断和个性化治疗建议进行预测。AI 的使用可以避免一些与罕见病相关的传统局限性。具体来说,它可以优化传统的随机对照试验,最终可能降低药物研发的成本。最近的进展使研究人员能够基于大型数据集训练模型,然后在通常与罕见病相关的较小数据集上对这些模型进行微调。在这个迷你综述中,我们讨论了 AI 的最新进展以及如何应用 AI 来简化罕见病的诊断和优化治疗。