arXiv.org Authors Andrei Olar Abstract Context: Entity resolution (ER) plays a pivotal role in data management by determining whether multiple records correspond to the same real-world entity. Because of its critical importance across domains such as healthcare, finance, and machine learning and its long research history designing and implementing ER systems remains challenging in…
International Conference on Evaluation of Novel Approaches to Software Engineering Authors L. Cernau, L. Dioşan, Camelia Serban Abstract Established research directions yield concrete outcomes on the benefits of using software metrics in software development processes, such as notable correlations between software metric values and various quality attributes of software systems or defect prediction. A…
International Conference on Computer Supported Education Authors Andrei Olar, L. Dioşan Abstract Entity resolution, the process of discerning whether multiple data refer to the same real-world entity, is crucial across various domains, including education. Its quality assessment is vital due to the extensive practical applications in fields such as analytics, personalized learning or academic…
International Conference on Agents and Artificial Intelligence Authors Adél Bajcsi, A. Andreica, C. Chira Abstract Proper treatment of breast cancer is essential to increase survival rates. Mammography is a widely used, non-invasive screening method for breast cancer. A challenging task in mammogram analysis is to distinguish between tumors. In the current study, we address…
Current medical imaging Authors Z. Bálint, L.G. Coroama, L. Dioşan, T. Telecan, I. Andraș, N. Crisan, A. Andreica, C. Caraiani, A. Lebovici, B. Boca Abstract INTRODUCTION Prostate magnetic resonance imaging (MRI) has been recently integrated into the pathway of diagnosis of prostate cancer (PCa). However, the lack of an optimal contrast-to-noise ratio hinders automatic…
Frontiers in Oncology Authors Diana Mihaela Coroamă, L. Dioşan, T. Telecan, I. Andraș, N. Crisan, Paul Medan, A. Andreica, C. Caraiani, A. Lebovici, B. Boca, Z. Bálint Abstract Introduction Bladder magnetic resonance imaging (MRI) has been recently integrated in the diagnosis pathway of bladder cancer. However, automatic recognition of suspicious lesions is still challenging.…
Hybrid Artificial Intelligence Systems Authors Cristiana Moroz-Dubenco, L. Dioşan, A. Andreica Abstract In the past five years, 7.8 million women were diagnosed with breast cancer. Breast cancer is curable if it is discovered in early stages. Therefore, mammography screening is essential. But, since interpretation can prove difficult, various automated interpretation systems have been proposed…
International Conference on Virtual Storytelling Authors Cristiana Moroz-Dubenco, L. Dioşan, A. Andreica Abstract Breast cancer is the most frequent type of malignancy in women, with 2.3 million diagnostics only in 2020. However, as a consequence of early diagnosis and appropriate treatment, more and more women are being cured. Among screening methods, mammography is one…
International Conference on Cooperative Information Systems Authors Maria Popa, A. Andreica Abstract Brain disorders are becoming more prevalent, and accurate brain segmentation is a vital component of identifying the appropriate treatment. This study introduces an enhanced graph-based image segmentation technique. The node selection process involves creating an ellipsoid centered at the image’s center of…
International Conference on Knowledge-Based Intelligent Information & Engineering Systems Authors Cristiana Moroz-Dubenco, A. Andreica Abstract Between 2015 and 2020, 7.8 million women were diagnosed with breast cancer. If the cancer is discovered early, it can be completely cured. Computer-aided detection and diagnosis systems are a helpful tool. We propose such a system: after pre-processing…
