## 1 Introduction
While various methods for SR and TAR are established, their applicability when searching for clinical data on medical devices has not yet been investigated. Applying existing methods might require adaptations to overcome the challenges of retrieving data for medical devices and entails structural limitations [21]. Firstly, input for a search, such as product descriptions provided by SMEs, usually does not follow strict wording and contains precise inclusion criteria as is the case with review protocols. Secondly, medical device assessment entails a higher level of complexity compared to other health technologies, such as the assessment of pharmaceuticals [22]. This indicates that a transfer of methods tailored to one application, such as the retrieval of literature for diagnostic test accuracy reviews in the scope of CLEF challenges, to another, such as the retrieval of clinical data on medical devices, might be problematic. Thirdly, the existing methods retrieve documents from only one database, rather than heterogeneous data from multiple databases. Hence, leveraging methods of the CLEF challenges may only retrieve a fraction of potentially relevant data, since clinical trials, for instance, are excluded. However, consistent guidance is scarce when searching for clinical trials, causing their inclusion to be particularly challenging [23]. While no consistent search method is established to locate diverse types of clinical trials, existing strategies rely on query formulation by either researchers or assisting experts, such as librarians [24]. Limited best-practice guidance is available for searching clinical data on medical devices [21], and previously conducted searches were resource-intensive and required the knowledge of review experts [9; 25]. These limitations pose a major challenge, especially for SMEs lacking the required financial resources and expertise [26]. Up to 79% of German medical device manufacturers reported difficulties with the clinical evaluation of their devices and the provision of sufficient clinical data [27]. This observation contributes to an overall European trend, as these companies make up 41% of the EU industry revenue [27]. While checklists, guidance documents, and services offered by consulting agencies for this purpose exist, resources are lacking to empower SMEs in particular [28] to conduct initial technology-assisted scoping searches without expert knowledge. Therefore, our aim is to provide assistance with the initial scoping search as a decision support and basis for possible future systematic reviews for SMEs challenged by the increased MDR requirements. Orientation should be provided to SMEs by automatically retrieving relevant clinical data for the respective medical device without expert assistance to formulate complex queries or define a search strategy. Initial results then serve as a starting point to analyze the state of the art in literature for the intended use of the medical device, thus adding transparency as a requirement to the search for it to be understandable. Enabling such low-threshold initial scoping searches then provides the basis for experts to develop a strategy for a systematic review of clinical evidence [29]. To meet the specific requirements of SMEs, the search process must be tailored to the medical device, e.g., by using all relevant bibliographic references available from prior knowledge or even using only a free-text product description as the search input. Thus, in this paper, we conceptualize novel automated search strategies for assisting with the search and screening process for relevant clinical data while incorporating relevance feedback regarding the results. The automated search methods integrate device-specific documents from heterogeneous bibliographic databases for publications and clinical trials, namely PubMed and ClinicalTrials.gov. The search methods are usable without expert knowledge and involve screening only a relatively low number of documents to lower barriers regarding applicability [29].