Zobrazeno 1 - 10
of 349
pro vyhledávání: '"Laskov, P."'
Machine Learning (ML) has become a valuable asset to solve many real-world tasks. For Network Intrusion Detection (NID), however, scientific advances in ML are still seen with skepticism by practitioners. This disconnection is due to the intrinsicall
Externí odkaz:
http://arxiv.org/abs/2305.00550
Fifth Generation (5G) networks must support billions of heterogeneous devices while guaranteeing optimal Quality of Service (QoS). Such requirements are impossible to meet with human effort alone, and Machine Learning (ML) represents a core asset in
Externí odkaz:
http://arxiv.org/abs/2207.01531
Autor:
Apruzzese, Giovanni, Laskov, Pavel, de Oca, Edgardo Montes, Mallouli, Wissam, Rapa, Luis Burdalo, Grammatopoulos, Athanasios Vasileios, Di Franco, Fabio
Machine Learning (ML) represents a pivotal technology for current and future information systems, and many domains already leverage the capabilities of ML. However, deployment of ML in cybersecurity is still at an early stage, revealing a significant
Externí odkaz:
http://arxiv.org/abs/2206.09707
Machine learning (ML) has become an important paradigm for cyberthreat detection (CTD) in the recent years. A substantial research effort has been invested in the development of specialized algorithms for CTD tasks. From the operational perspective,
Externí odkaz:
http://arxiv.org/abs/2205.08944
Autor:
Goupil, Francois, Laskov, Pavel, Pekaric, Irdin, Felderer, Michael, Dürr, Alexander, Thiesse, Frederic
Given the ongoing "arms race" in cybersecurity, the shortage of skilled professionals in this field is one of the strongest in computer science. The currently unmet staffing demand in cybersecurity is estimated at over 3 million jobs worldwide. Furth
Externí odkaz:
http://arxiv.org/abs/2204.13793
Autor:
Monika Klírová, Andrea Adamová, Nina Biačková, Olga Laskov, Veronika Renková, Zuzana Stuchlíková, Karolína Odnohová, Tomáš Novák
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract The study aimed to assess the efficacy of transcranial direct current stimulation (tDCS) in the treatment of neuropsychiatric (NP) symptoms of the post-acute sequelae of SARS-CoV-2 infection (PASC), known as the long COVID. A double-blind, r
Externí odkaz:
https://doaj.org/article/406cad2fc4df4e66b107394dad3524b5
Autor:
Vladimir I. Evdokimov, Anatoly A. Bloshchinenko, Alexander E. Abolmasov, Alexey A. Vilensky, Michail S. Laskov
Publikováno v:
Современная онкология, Vol 25, Iss 3, Pp 336-341 (2023)
Aim. To evaluate the effectiveness of trastuzumab deruxtecan in real-world practice in the Russian Federation. Materials and methods. We performed a retrospective analysis of clinical case series related to the use of trastuzumab deruxtecan (N=15)
Externí odkaz:
https://doaj.org/article/02e2f51c5f464211a7ce2b5365c62c79
Publikováno v:
PLoS ONE, Vol 19, Iss 4, p e0301978 (2024)
Radiomic features are usually used to predict target variables such as the absence or presence of a disease, treatment response, or time to symptom progression. One of the potential clinical applications is in patients with Parkinson's disease. Robus
Externí odkaz:
https://doaj.org/article/e34968180c2d48caae797780c3ccb1db
Autor:
Miriam R. Brezis, Eliya Shachar, Shira Peleg Hasson, Ido Laskov, Nadav Michaan, Bar Levy, Ido Wolf, Tamar Safra
Publikováno v:
Frontiers in Oncology, Vol 13 (2023)
ObjectiveTo evaluate the effectiveness and safety of standard chemotherapy administered to patients >70 years with advanced ovarian cancer (OC).MethodsMedical records of 956 advanced-stage patients with OC treated between 2002-2020 with standard surg
Externí odkaz:
https://doaj.org/article/fdc1c186302a4b198978a307a135f165
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