You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A Preliminary Survey of Knowledge Discovery on Smartphone Applications (apps): Principles, Techniques and Research Directions for E-health 
Chapter Title:  A. Research Direction of Profiling Health Apps 
1. Abstract of Cited Paper (BIB001):  BACKGROUND ::: There are thousands of medical applications for mobile devices targeting use by healthcare professionals. However, several factors related to the structure of the existing market for medical applications create significant barriers preventing practitioners from effectively identifying mobile medical applications for individual professional use. ::: ::: ::: AIMS ::: To define existing market factors relevant to selection of medical applications and describe a framework to empower clinicians to identify, assess and utilise mobile medical applications in their own practice. ::: ::: ::: MATERIALS AND METHODS ::: Resources available on the Internet regarding mobile medical applications, guidelines and published research on mobile medical applications. ::: ::: ::: RESULTS ::: Mobile application stores (e.g. iTunes, Google Play) are not effective means of identifying mobile medical applications. Users of mobile devices that desire to implement mobile medical applications into practice need to carefully assess individual applications prior to utilisation. ::: ::: ::: DISCUSSION ::: Searching and identifying mobile medical applications requires clinicians to utilise multiple references to determine what application is best for their individual practice methods. This can be done with a cursory exploration of mobile application stores and then moving onto other available resources published in the literature or through Internet resources (e.g. blogs, medical websites, social media). Clinicians must also take steps to ensure that an identified mobile application can be integrated into practice after carefully reviewing it themselves. ::: ::: ::: CONCLUSION ::: Clinicians seeking to identify mobile medical application for use in their individual practice should use a combination of app stores, published literature, web-based resources, and personal review to ensure safe and appropriate use.

Literature Review:
Recent research  BIB001 BIB002 has discussed several suggestions to resolve health apps overload and quality issues. For example, management policies (e.g., standardized medical information and use of authorized open source medical data for app development) and peer review of the content of health apps. However, these potential measurements or movements could take time and large resources to be effective. Based on this current research's review, these current studies provide us deep insight into manual analyses of health apps, principles for categorizing medical apps and methods for uncovering issues of concern as well as management of security and privacy issues of products on the Android market. Even so, these studies cannot be used as a certification framework for health apps. As aforementioned, different principles and concerns may have different methods of clustering and classification of apps. From the author's perspective, some possibilities should be sought out to address these questions effectively. For example, in Fig. 1 , an app crawler is designed to obtain e-health apps from the Android market and decompile codes of these apps by open source tools. Secondly, newly developed algorithms for supporting statistic and dynamic analyses of app content will be proposed to understand the profiles of health apps on the Android market. Based on the creation of app profiles and the current potential principles for categorizing medical apps, a further large scale analysis will be executed to cluster, validate and classify e-health apps on the Android market.