## 1 Introduction  
There have been numerous open source projects created across a variety of domains after decades of open source software advocacy [1]. With their accelerating popularity, more and more will likely be added. The plethora of open source projects offers great reuse opportunities for developers to build tools at lower cost and at a faster pace. Therefore, software reuse, also called code reuse, has become an essential topic in software development [2; 3; 4]. This is especially true in the clinical domain, where the lack of a well-trained IT workforce and an uneven geographic distribution of clinical informaticians between developed and developing countries restrain the development of clinical IT [5; 6]. Given that successful reuse of existing open source software enables the rapid and cost-effective development of clinical applications, it is of great importance to promote reuse awareness in the clinical community and facilitate software reuse practices among clinical developers and applied data scientists [7; 8; 9; 10]. [PERSON] and [PERSON] have recognized this importance and have called for more reuse of open source projects in clinical settings [7]. As a challenging topic, software reuse still faces many difficulties, particularly in clinical software development [11]. The lack of resources to support the selection of suitable reusable source codes or software from tens of thousands of open source projects is one of them. Although systematic literature studies on clinical software have helped developers obtain a deeper understanding of the existing tools and their performances [12; 13; 14], they are not particularly useful in clinical software development. First, systematic literature studies cover only a small proportion of the vast amount of clinical software. Moreover, the rapid updates of clinical software are not reflected due to the long publication process. Most importantly, these systematic literature studies do not examine source codes, software issues, and code usage, which are crucial in reuse practices. Recently, researchers in life sciences have combined literature studies and large-scale analysis on open source repositories to achieve better reusability [15; 16]. A source code repository is a file archive and web hosting facility where a large amount of source code is kept, either publicly or privately [17]. Well-organized repositories contain both brief descriptions and detailed README files that explain what the projects are and how to use them. Quantitative metrics such as stars and forks indicate how popular a repository is. [PERSON] et al. built an online software discovery platform with biomedical software-related data collected from PubMed literature and GitHub. It empowers biomedical researchers to easily find the (open source) tools they need [15]. A large-scale analysis of bioinformatics open source projects on GitHub was conducted to uncover the unknown state of bioinformatics software. The analysis covers a list of 1743 GitHub repositories manually selected from bioinformatics articles and online forums [16]. By focusing on the analysis of data extracted from open source repositories, these studies offered more information for evaluating software in reusability. However, both studies only included a limited amount of biomedical software that were mentioned in the literature. To our knowledge, there is no such research that has investigated open source clinical software. Therefore, this paper intends to contribute to clinical software reuse research by conducting a large-scale analysis of open source repositories in the clinical domain. Instead of analyzing a shortlist of open source repositories extracted from literature, this study includes all clinical-related open source repositories on GitHub. As the largest code host in the world, GitHub reached 24 million developers working across 67 million repositories in 2017 [18]. Numerous open source projects in various domains could be found and reused.