fix to kicky thesis abstract

diag.bib

@@ -27973,8 +27973,7 @@ @PhdThesis{Leeu23c
   url         = {https://repository.ubn.ru.nl/handle/2066/295128},
   abstract    = {The aim of this thesis is to increase transparency of the AI software applications for the radiology market: the medical specialty which currently covers 75% of all approved medical AI software [36]. The focus is on products available for clinical use in Europe, in other words, products that are CE marked. We discuss the potential use cases of AI in radiology, map commercially available AI products, independently assess the performance of products, and measure and model the (potential) added value. With the insights we have gained and publicly shared, we enable more informed decision-making by AI purchasers, users, investors, and creators. Furthermore, it encourages use and development of AI that is safe and of value to society.
 The key contributions of this research are:
-- Three years of publicly sharing of information to a global audience on commercially available AI products, verified regulatory clearance information,
-product specifications, and scientific evidence, through www.AIforRadiology.com and associated monthly newsletter.
+- Three years of publicly sharing of information to a global audience on commercially available AI products, verified regulatory clearance information, product specifications, and scientific evidence, through www.AIforRadiology.com and associated monthly newsletter.
 - Initiating the Dutch Radiology AI-network connecting "AI-champions" among hospitals to share experiences and to enable the yearly inquiry on the clinical use of commercial AI.
 - Development of a framework for the independent and objective validation of commercially available AI products and applying this to ten products, for two different use cases, on data from seven medical centers. With this framework, we make validation more efficient and impartial, enabling informed purchasing or reimbursement decisions.
 - One of the first demonstrations of how an early health technology assessment can be performed to demonstrate the value of an AI product before implementation.},