International Journal of Molecular Medical Science, 2024, Vol.14, No.1, 16-23 http://medscipublisher.com/index.php/ijmms 16 Review and Progress Open Access The Application Prospects of Artificial Intelligence in Molecular Medicines WangWei 1 , Huang Qikun2 1 Biotechnology Research Center, Cuixi Academy of Biotechnology, Zhuji, 311800, China 2 Institute of Life Science, Jiyang College of Zhejiang A&F University, Zhuji, 311800, China Corresponding author: 2741098603@qq.com International Journal of Molecular Medical Science, 2024, Vol.14, No.1 doi: 10.5376/ijmms.2024.14.0003 Received: 02 Jan., 2024 Accepted: 03 Feb., 2024 Published: 13 Feb., 2024 Copyright © 2024 Wang and Huang, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Wang W.,and Huang Q.K., 2024, The application prospects of artificial intelligence in molecular medicine, International Journal of Molecular Medical Science, 14(1): 16-23 (doi: 10.5376/ijmms.2024.14.0003) Abstract The application of artificial intelligence in molecular medicine has garnered widespread interest and research. With the continuous increase in data volume and advancements in computing capabilities, artificial intelligence algorithms have demonstrated significant potential in the field of molecular medicine. This review introduces the basic principles and classifications of artificial intelligence, along with fundamental concepts and research content of molecular medicine. Addressing applications in early disease diagnosis, identification and prediction of molecular markers, drug design and discovery, as well as treatment response and personalized therapy in molecular medicine, the paper discusses the potential of artificial intelligence, outlines the prospects of its application in molecular medicine, and explores associated opportunities and challenges. However, artificial intelligence faces challenges in the molecular medicine field, including issues related to data quality and quantity, privacy and ethics, as well as model interpretability and trustworthiness. The review provides insights into the future directions of artificial intelligence in molecular medicine, encompassing the application of new technologies and methods, interdisciplinary collaboration and resource sharing, and the collaborative role of artificial intelligence with human physicians. It is hoped that through this review, researchers and the medical community can gain a comprehensive understanding of the application of artificial intelligence in molecular medicine. Keywords Artificial intelligence; Molecular medicine; Early diagnosis; Drug discovery; Precision medicine In recent years, the application of artificial intelligence has been continuously expanding across various fields, with molecular medicine being a particularly noteworthy and researched domain. Molecular medicine, as a critical branch of medicine, focuses on studying diseases at the molecular level, including diagnosis, treatment, and prevention, providing new methods and strategies for human health. Meanwhile, artificial intelligence, with its powerful algorithms and models, is gradually revealing significant potential in the field of molecular medicine. Understanding the occurrence and development of diseases at the molecular level is the foundation for comprehending the essence of diseases and finding treatment strategies. However, traditional approaches in the past often faced limitations in data scale and complexity. The emergence of artificial intelligence technology has provided us with a new avenue to overcome these traditional constraints. By utilizing artificial intelligence algorithms such as machine learning, deep learning, and neural networks, we can process and analyze large-scale biological data, extract valuable information, and identify key molecular markers associated with diseases. This capability offers researchers and healthcare professionals a more comprehensive and in-depth understanding of diseases. Understanding the occurrence and development of diseases at the molecular level is the foundation for comprehending the essence of diseases and finding treatment strategies. However, traditional approaches in the past often faced limitations in data scale and complexity. The emergence of artificial intelligence technology has provided us with a new avenue to overcome these traditional constraints. By utilizing artificial intelligence algorithms such as machine learning, deep learning, and neural networks, we can process and analyze large-scale biological data, extract valuable information, and identify key molecular markers associated with diseases. This capability offers researchers and healthcare professionals a more comprehensive and in-depth understanding of diseases.
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