## 1 Introduction  
Electronic medical records (EMRs) have been developed in Taiwan for more than a decade [1]. They have been implemented in most of the larger medical institutions to store information about encounters and events between patients and healthcare systems [2]. The implementation of EMRs not only enables large-scale storage and collection of patient data but also makes the exchange of healthcare information between healthcare facilities possible through the Electronic Medical Record Exchange Center [2]. Almost all the medical complaints, diagnoses, processes of clinical care, laboratory results, and medication use from various departments of most domestic hospitals are readily available from EMRs. The immediate accessibility of patient information is likely to help healthcare professionals improve patient care delivery and enhance the quality of medical decision-making [3, 4]. Moreover,the development of integrated clinical decision support systems and EMRs has achieved substantial success in reducing medical errors and improving patient safety [5]. Despite the positive changes brought by EMRs, patient information explosion associated with the rapid accumulation of a large amount of unstructured data has become a threat to the effective use of EMRs. The immense amount of information stored in EMRs can lead to information overload for healthcare professionals [6]. In addition, the use of EMRs may interfere with the interaction between patients and practitioners and cause dissatisfaction and burnout among healthcare professionals [7]. Furthermore, because current EMR systems generally provide several time-saving features such as the \"copy-and-paste\" function, physicians frequently use copying and pasting to reduce the omission of what they consider important information. Clinical notes have thus become full of redundant information and barely able to convey useful information [8]. These redundant contents also cause difficulties in reading and prolong reading time. As more longitudinal clinical narratives are produced with the increasing number of healthcare encounters, the practice of copying and pasting inevitably generates more redundant information, which is actually noise and masks new and clinically relevant information within notes [9]. A systematic review found that 66% to 90% of clinicians routinely use copy-and-paste and approximately 80% of physicians use copy-and-paste regularly for inpatient documentation [10]. Such practices are similarly common among residents and attendings [11]. Despite the many deficits in notes written using copy-and-paste, approximately 80% of physicians agreed that copy-and-paste behaviors should continue [12] considering that almost half of their work time is spent on EMR-related work [13,14]. Now that the adoption of healthcare information technology has brought about lots of redundant information in EMRs, healthcare information technology should be able to help reduce the interference from redundant information. According to a survey on the usability of EMR systems, \"ease of finding the required information on the screen\" is the most desired requirement [15]. Hence, many studies have focused on the redesign of EMR interfaces, hopefully facilitating clinicians to keep track of relevant patient information. Well-designed data visualization in EMR systems not only allows healthcare professionals to communicate information efficiently and effectively but also improves data interpretation and clinical reasoning [16,17]. Besides, it is recommended that copied material should be displayed in a different font or color, so that they can be easily identified [10]. With the advances in natural language processing, investigators have tried to build applications around NLP technologies for summarization or extraction of needed information from longitudinal patient records within EMRs [17,18]. Among them, [PERSON] et al. have developed algorithms based on statistical language models to identify relevant new information in longitudinal clinical narratives [9,19].