Biomedical Informatics: State of the Art, Challenges, and Opportunities

Carson K. Leung
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引用次数: 0

Abstract

Biomedical informatics can be considered as a multidisciplinary research and educational field situated at the intersection of computational sciences (including computer science, data science, mathematics, and statistics), biology, and medicine. In recent years, there have been advances in the field of biomedical informatics. The current article highlights some interesting state-of-the-art research outcomes in these fields. These include research outcomes in areas like (i) computational biology and medicine, (ii) explainable artificial intelligence (XAI) in biomedical research and clinical practice, (iii) machine learning (including deep learning) methods and application for bioinformatics and healthcare, (iv) imaging informatics, as well as (v) medical statistics and data science. Moreover, the current article also discusses some existing challenges and potential future directions for these research areas to advance the fields of biomedical informatics.
生物医学信息学:技术现状、挑战和机遇
生物医学信息学可被视为一个多学科研究和教育领域,它位于计算科学(包括计算机科学、数据科学、数学和统计学)、生物学和医学的交叉点。近年来,生物医学信息学领域取得了一些进展。本文重点介绍了这些领域中一些令人感兴趣的最新研究成果。其中包括以下领域的研究成果:(i) 计算生物学和医学;(ii) 生物医学研究和临床实践中的可解释人工智能(XAI);(iii) 机器学习(包括深度学习)方法及其在生物信息学和医疗保健中的应用;(iv) 影像信息学;以及 (v) 医学统计学和数据科学。此外,本文还讨论了这些研究领域的一些现有挑战和潜在的未来方向,以推动生物医学信息学领域的发展。
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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CiteScore
1.70
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0.00%
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