@article{MTMT:36978908,
	title = {ACETYLSALICYLIC ACID IN CARDIOLOGY: BENEFITS, RISKS, AND CLINICAL INDICATIONS},
	url = {https://m2.mtmt.hu/api/publication/36978908},
	author = {Dinu, Ciprian Adrian and Elisei, Alina Mihaela and Mihalache, Daniela and Batir, Denisa Marin},
	doi = {10.62610/RJOR.2025.1.17.89},
	journal-iso = {ROM J ORAL REHABIL},
	journal = {ROMANIAN JOURNAL OF ORAL REHABILITATION},
	volume = {17},
	unique-id = {36978908},
	issn = {2066-7000},
	abstract = {Acetylsalicylic acid (ASA) is an antiplatelet agent widely used in cardiology and has an essential role in the prevention and treatment of cardiovascular diseases. By irreversibly inhibiting cyclooxygenase-1 (COX-1), ASA reduces platelet aggregation and the risk of thrombotic events, being recommended in the secondary prevention of myocardial infarction, stroke, and peripheral arterial disease. It is also a central element in the treatment of acute coronary syndromes, administered in combination with other antiplatelet agents. However, its use is not without risks, the main adverse effects being gastrointestinal and intracranial hemorrhages. In primary prevention, the benefits are questionable, requiring a careful evaluation of the risk-benefit ratio. Current research is exploring strategies for optimizing the administration of ASA, including dose adjustment, intermittent administration, and identifying biomarkers that allow for personalized use. The development of safer alternatives and innovative formulations could improve the safety profile of ASA in the future. Thus, individualization of treatment remains essential to maximize efficiency and reduce associated risks.},
	year = {2025},
	eissn = {2601-4661},
	pages = {933-944},
	orcid-numbers = {Dinu, Ciprian Adrian/0000-0001-9600-568X; Elisei, Alina Mihaela/0000-0002-0490-2998; Batir, Denisa Marin/0009-0001-6756-7584}
}

@inproceedings{MTMT:35495657,
	title = {A network clustering method based on intersection of random spanning trees},
	url = {https://m2.mtmt.hu/api/publication/35495657},
	author = {Hajdu, László and London, András and Pluhár, András},
	booktitle = {Proceedings of the 19th Conference on Computer Science and Intelligence Systems (FedCSIS)},
	doi = {10.15439/2024F7644},
	unique-id = {35495657},
	year = {2024},
	pages = {609-614},
	orcid-numbers = {London, András/0000-0003-1957-5368; Pluhár, András/0000-0001-6576-4202}
}

@book{MTMT:36978922,
	title = {Kompaktkurs Kombinatorik: Gezählt, verteilt und wohlgeordnet},
	url = {https://m2.mtmt.hu/api/publication/36978922},
	isbn = {9783662669723},
	author = {Kraus, Mario H.},
	doi = {10.1007/978-3-662-66973-0},
	publisher = {Springer Spektrum},
	unique-id = {36978922},
	year = {2023}
}

@article{MTMT:33727352,
	title = {Acetylsalicylic Acid–Primus Inter Pares in Pharmacology},
	url = {https://m2.mtmt.hu/api/publication/33727352},
	author = {Fijałkowski, Ł. and Skubiszewska, M. and Grześk, G. and Koech, F.K. and Nowaczyk, A.},
	doi = {10.3390/molecules27238412},
	journal-iso = {MOLECULES},
	journal = {MOLECULES},
	volume = {27},
	unique-id = {33727352},
	issn = {1431-5157},
	year = {2022},
	eissn = {1420-3049}
}

@article{MTMT:32454579,
	title = {On the Utilization of Shortest Paths in Complex Networks},
	url = {https://m2.mtmt.hu/api/publication/32454579},
	author = {Alrasheed, Hend},
	doi = {10.1109/ACCESS.2021.3101176},
	journal-iso = {IEEE ACCESS},
	journal = {IEEE ACCESS},
	volume = {9},
	unique-id = {32454579},
	abstract = {Considerable effort has been devoted to the study of network structures and connectivity patterns and their influence on network dynamics. A widely used assumption in network analysis models is that traffic follows the shortest paths connecting pairs of nonneighboring vertices. For example, graph centrality measures, community extraction algorithms, and core-periphery detection algorithms use this assumption. However, this is a very restricted perspective and can be misleading as a consequence of its focus on shortest path communications. In this work, we study the utilization of shortest paths in complex networks in different data dissemination scenarios. We also explore whether there are general properties that can make networks utilize shortest paths more effectively. By conducting simulations on a set of real-world and artificial networks, we show that the utilization of shortest paths in complex networks may not be as common as assumed. This implies that longer paths can be as important (in some cases) as the shortest paths. Our results show that at least two factors clearly influence shortest path utilization in a network: the structure of the network and the data dissemination algorithm. We also find that the type of a network is not a good indicator of its shortest path utilization.},
	keywords = {complex networks; Graph theory; network analysis; Analytical models; NETWORK STRUCTURE; Social networking (online); Shortest paths; Licenses; Susceptible-Infectious-Recovered (SIR) model; Data dissemination; Image edge detection; Influence maximization (IM) model; network distance properties; small-world phenomenon; vertex centrality},
	year = {2021},
	eissn = {2169-3536},
	pages = {110989-111004},
	orcid-numbers = {Alrasheed, Hend/0000-0002-8649-5926}
}