## 1 Introduction  
Search engines play a crucial role in facilitating information retrieval (IR) and supporting users' information-seeking tasks across various domains. However, the field of healthcare poses unique challenges for medical practitioners when it comes to accessing timely and comprehensible search results as the information they acquire can significantly impact their decision making processes and ultimately influence patient care outcomes. Despite the widespread availability of search engines, medical practitioners often face difficulties in finding the precise and contextually relevant information they need within the constraints of their demanding schedules. These challenges arise from the specialized nature of medical knowledge, the vast amount of scientific literature available, and the requirement for accurate and easily understandable information. Research conducted by [PERSON] and [PERSON] [1] has revealed the significant influence of factors such as a reader's level of interest, prior knowledge, and the readability of a text on their comprehension of the material. It is essential to clarify that ease of reading primarily pertains to text understandability, while technicality is more focused on the concepts and domain-specific knowledge within the text [2, 3, 4]. This understanding underscores the need to address the readability and technicality aspects in the development of search enginestailored specifically to the needs of medical practitioners. To improve IR for healthcare professionals, it is necessary to incorporate these aspects into search engines. By retrieving comprehensible information based on their language proficiency and domain knowledge, these search engines can enhance the efficiency and effectiveness of the information provided, leading to informed decisions and optimal care. Similarly, Ref. [5] proposed to use the readability aspect for accepting or revising health-related documents. While previous studies [6; 7; 8] have focused primarily on developing personalized search engines for health information consumers, such as laypeople and patients, there is a clear gap in adapting to the specific requirements of medical practitioners. Unlike laypeople, medical practitioners possess specialized expertise and language proficiency in their respective fields. Therefore, our research project aims to contribute to filling this gap by developing a model capable of extracting and classifying the ease of reading and technicality levels of medical research articles. It is important to note that ease of reading and technicality are not mutually exclusive aspects [3]. Texts can exhibit varying degrees of both characteristics, leading to different combinations that may arise between these aspects. For instance, a text can be easy to read while still containing high technicality, or it can be difficult to read with low technicality, as shown in the following examples. (All examples have been reviewed and approved by a senior medical practitioner. Examples of easy-to-read content are from [9], while examples of harder-to-read content are from [10]). * **Easy to read and high technicality** Autologous hematopoietic stem cell transplantation has emerged as a promising therapeutic intervention for individuals with refractory multiple myeloma. This treatment approach has shown remarkable advancements in terms of progression-free survival and overall response rates, signifying its potential in improving patient outcomes. * **Hard to read and high technicality** The pathophysiological mechanisms underlying idiopathic pulmonary fibrosis involve aberrant activation of transforming growth factor-beta signaling pathways, leading to excessive deposition of extracellular matrix components and subsequent progressive scarring of lung tissue.