Uchida Wataru, Sen Guo, Zhe Sun, Lyu Tianxiang, Andica Christina, Takabayashi Kaito, Tokuda Keita, Shimoji Keigo, Kamagata Koji, Masutani Yoshitaka, Sato Mitsuhisa, Himeno Ryutaro, Aoki Shigeki
Juntendo Med J. 2025 Apr 10;71(2):82-89. doi: 10.14789/ejmj.JMJ24-0037-R. eCollection 2025.
Data science is revolutionizing various industries and its impact on healthcare and life sciences is particularly profound. The vast amounts of data generated in these fields present both opportunities and challenges, necessitating professionals to extract insights and create value from these data resources. However, effective data-driven solutions in healthcare require a unique combination of technical data science skills and deep-domain expertise in areas such as medicine, public health, and sports science. This review discusses the growing importance of domain knowledge in data science and the need for interdisciplinary professionals who can bridge the gap between data analysis and practical applications in the healthcare sector. Furthermore, this paper highlights specific applications of data science in healthcare and life sciences, leveraging artificial intelligence (AI) and advanced computational methods. By integrating cutting-edge data science techniques with profound domain understanding, these applications aim to drive innovation, advance medical research, improve patient outcomes, and deepen our understanding of human health and well-being. Overall, this review underscores the synergies between data science and domain expertise in healthcare and life sciences, emphasizing the importance of interdisciplinary collaboration in unlocking the full potential of data-driven solutions in these critical fields.
数据科学正在彻底改变各个行业,其对医疗保健和生命科学的影响尤为深远。这些领域产生的大量数据既带来了机遇,也带来了挑战,这就要求专业人员从这些数据资源中提取见解并创造价值。然而,医疗保健领域有效的数据驱动解决方案需要技术数据科学技能与医学、公共卫生和体育科学等领域的深厚专业知识的独特结合。本综述讨论了领域知识在数据科学中日益增长的重要性,以及对能够弥合医疗保健领域数据分析与实际应用之间差距的跨学科专业人员的需求。此外,本文重点介绍了数据科学在医疗保健和生命科学中的具体应用,利用了人工智能(AI)和先进的计算方法。通过将前沿数据科学技术与深入的领域理解相结合,这些应用旨在推动创新、推进医学研究、改善患者治疗效果,并加深我们对人类健康和福祉的理解。总体而言,本综述强调了数据科学与医疗保健和生命科学领域专业知识之间的协同作用,强调了跨学科合作在释放这些关键领域数据驱动解决方案全部潜力方面的重要性。