This thesis addresses two interconnected challenges: the complexity of computer-aided analysis of scintigraphy images and the difficulty of managing the extensive scientific literature in this field. The work is designed in two parts. The first part presents a systematic literature review, analyzing the development of methods over the last two decades and identifying a shift towards deep learning. In the second, practical part, we developed a prototype web application that automates the search and summarization of open-access articles by integrating the NCBI and Google Gemini APIs. The main contribution of the thesis is the development of a tool that enables the synthesis of information from both text and image materials, thereby offering a more advanced approach to literature analysis compared to existing solutions.
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