人工智能在肾脏疾病中的应用

Lijing Yao , Hengyuan Zhang , Mengqin Zhang , Xing Chen , Jun Zhang , Jiyi Huang , Lu Zhang
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引用次数: 7

摘要

人工智能(AI)已经广泛应用于我们日常生活的几乎每个领域,由于计算能力的增长,方法和技术的进步,以及数据的爆炸式增长,它在学术学科中也起着至关重要的作用,医学也不例外。人工智能可以增强临床医生在诊断、预后和治疗决策方面的智能。肾脏疾病在世界范围内造成了巨大的经济负担,无论是急性肾损伤还是慢性肾脏疾病都具有很高的发病率和死亡率。利用大数据和人工智能可以解决肾脏病学中的突出挑战。本文综述了机器学习(ML)、人工神经网络(ANN)、卷积神经网络(CNN)和深度学习(DL)的研究进展,重点介绍了急性肾损伤(AKI)、慢性肾病(CKD)、终末期肾病(ESRD)、透析、肾移植和肾脏病理学等方面的研究进展。人工智能目前可能不会取代肾病学家的医疗决策,而是帮助他们为患者提供最佳的个性化治疗。
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Application of artificial intelligence in renal disease

Artificial intelligence (AI) has been applied widely in almost every area of our daily lives, due to the growth of computing power, advances in methods and techniques, and the explosion of data, it also plays a critical role in academic disciplines, medicine is not an exception. AI can augment the intelligence of clinicians in diagnosis, prognosis, and treatment decisions. Kidney disease causes great economic burden worldwide, with both acute kidney injury and chronic kidney disease bringing about high morbidity and mortality. Outstanding challenges in nephrology may be addressed by leveraging big data and AI. In this review, we summarized advances in machine learning (ML), artificial neural network (ANN), convolution neural network (CNN) and deep learning (DL), with a special focus on acute kidney injury (AKI), chronic kidney disease (CKD), end-stage renal disease (ESRD), dialysis, kidney transplantation and nephropathology. AI may not be anticipated to replace the nephrologists’ medical decision-making for now, but instead assisting them in providing optimal personalized therapy for patients.

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