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1,818 results on '"Varga, M."'

3. Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score

Author

Dajti, I, Valenzuela, JI, Boccalatte, LA, Gemelli, NA, Smith, DE, Dudi-Venkata, NN, Kroon, HM, Sammour, T, Roberts, M, Mitchell, D, Lah, K, Pearce, A, Morton, A, Dawson, AC, Drane, A, Sharpin, C, Nataraja, RM, Pacilli, M, Cox, DRA, Muralidharan, V, Riddiough, GE, Clarke, EM, Jamel, W, Qin, KR, Pockney, P, Cope, D, Egoroff, N, Lott, N, Putnis, S, De Robles, S, Ang, Z, Mitteregger, M, Uranitsch, S, Stiegler, M, Seitinger, G, Aigner, F, Lumenta, DB, Nischwitz, PS, Richtig, E, Pau, M, Srekl-Filzmaier, P, Eibinger, N, Michelitsch, B, Fediuk, M, Papinutti, A, Seidel, G, Kahn, J, Cohnert, TU, Messner, D, Öfner, F, Presl, J, Varga, M, Weitzendorfer, M, Emmanuel, K, Binder, AD, Zimmermann, M, Holawe, S, Nkenke, E, Grimm, C, Kranawetter, M, Rahman Mitul, A, Islam, N, Karim, S, Komen, N, Ang, E, De Praetere, H, Tollens, T, Schols, G, Smets, C, Haenen, L, Quintens, J, Van Belle, K, Van Ramshorst, GH, Pattyn, P, Desender, L, Martens, T, Van de Putte, D, Lerut, P, Grimonprez, A, Janssen, M, De Smul, G, Wallaert, P, Van den Eynde, J, Oosterlinck, W, Van den Eynde, R, Sermon, A, Boeckxstaens, A, Cordonnier, A, De Coster, J, Jaekers, J, Politis, C, Miserez, M, Duchateau, N, De Gheldere, C, Flamey, N, Christiano, A, and Guidi, B

Subjects
Clinical Research, Patient Safety, Vaccine Related, Biodefense, Prevention, 6.4 Surgery, Evaluation of treatments and therapeutic interventions, Good Health and Well Being, COVID-19, Cohort Studies, Datasets as Topic, Humans, Machine Learning, Models, Statistical, Risk Assessment, SARS-CoV-2, Surgical Procedures, Operative, COVIDSurg Collaborative, Medical and Health Sciences, Surgery
Abstract

To support the global restart of elective surgery, data from an international prospective cohort study of 8492 patients (69 countries) was analysed using artificial intelligence (machine learning techniques) to develop a predictive score for mortality in surgical patients with SARS-CoV-2. We found that patient rather than operation factors were the best predictors and used these to create the COVIDsurg Mortality Score (https://covidsurgrisk.app). Our data demonstrates that it is safe to restart a wide range of surgical services for selected patients.

Published
2021

4. Croatian public companies for energy distribution and supply: integration of information subsystems

Author

Simovic, V. and Varga, M.

Subjects
Computer Science - Computers and Society, Electrical Engineering and Systems Science - Systems and Control
Abstract

This research is about integration of information subsystems from:information system procurement, financial information system, information system security, technical information systems and legal information systems, and about their mutual dependence and close connections in Croatian public companies for energy distribution and supply. Also, herewe research the main goals of procurement information system which must be achieved in every organization because procurement process takes place in every public organization. Based on the model of the business technology matrix their processes can be executed by other companies engaged in similar activities. This research paper describes the timing of the sub processes, also. The timing of sub processes needs to be reduced as much as possible to achieve the planned results at the exit of the sub processes so that the costs of running sub-processes are equal to or lower than they had been so far, but with a higher quality output. We discuss possible threats to the information systems organization, and how to protect electronic information in the process of restoration of electronic data base for the financial information system. At the end the research paper we explain the advantages and disadvantages of cloud computing, information security in the event of possible applications of computing in the clouds and activities for technical information system in the flow diagram.

Published
2020

25. Histological Scoring Systems in the Cartilage Repair of Sheep

Author

Gullberg S., Simaiová V., Holovská K., Luptaková L., Koľvek F., Varga M., and Petrovová E.

Subjects
animal model, articular cartilage, cartilage repair, histology, regeneration, scoring system, Veterinary medicine, SF600-1100
Abstract

Researchers around the world use histological analysis to provide the most detailed morphological information of articular cartilage repair and it predominantly relies on the use of histological scoring systems which are important tools for valid evaluations. Due to hyaline cartilage complex structure and avascular nature, damaged cartilage does not heal spontaneously and it is still a challenge to regenerate and restore its tissue function. The aim of this study was to investigate the quality of regenerated cartilage by using three different histological scoring systems; O’Driscoll, Pineda and Wakitani which are all classic scores described for such animal studies. We used an in vivo ovine model in which a full thickness chondral defect was created and then implanted with the biomaterial (polyhydroxybutyrate/chitosan; PHB/ CHIT). The results of this histological analysis demonstrated that the cartilage repaired tissues received scores indicating that the majority of the regenerated tissue resembled hyaline-like cartilage. After six months of repair the regenerated cartilage showed characteristics like good surface continuity, uniformed stained extracellular matrix, clearly visible zones and cellular proliferation. In conclusion, this study may be used to investigate and improve the regenerative capacity of hyaline cartilage in preclinical models and it also sheds further light on both the evaluation and methods used for the regeneration of damaged cartilage.

Published
2019
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26. Degradation of Ag/Si multilayers during heat treatments

Author

Kapta, K., Daroczi, L., Papp, Z., Beke, D. L., Langer, G. A., Csik, A., Kis-Varga, M., Greer, A. L., and Barber, Z. H.

Subjects
Condensed Matter - Materials Science
Abstract

Microstructure changes during annealing of nano-crystalline silver and amorphous silicon multilayers (Ag/a-Si) have been studied by X-ray diffraction and transmission electron microscopy. The dc-magnetron sputtered Ag/a-Si multilayers remained stable even after annealing at 523K for 10h, and microstructural changes occurred only above 600K. The degradation of Ag/a-Si multilayers can be described by the increase of size of Ag grains, formation of grooves and pinholes at Ag grain boundaries and by the diffusion of silicon atoms through the silver grain boundaries and along the Ag/a-Si interfaces. This results in thinning of a-Si layers, and in formation of Ag granulates after longer annealing times.

Published
2009

27. Application of Secondary Neutral Mass Spectrometry in the investigation of doped perovskites

Author

Vad, K., Hakl, J., Csik, A., Meszaros, S., Kis-Varga, M., Langer, G. A., Pallinger, A., and Bodog, M.

Subjects
Condensed Matter - Materials Science, Condensed Matter - Superconductivity
Abstract

Electromagnetic properties of doped perovskites depend sensitively on the doping level. Both the superconducting transition temperature of Bi2Sr2Ca(Pr)Cu2O8+d compounds and the magnetic and electronic transport properties of La(Sr)Co(Fe)O3 perovskites change dramatically with the doping level. Apart from doping, oxygen deficiency is influenced by the details of preparation processes such as calcination and sintering. Simultaneous determination of constituents is of crucial importance from sample characterization point of view. Quantitative analysis of perovskite oxides can be performed by Secondary Neutral Mass Spectrometry (SNMS) which is a suitable technique to measure the chemical composition of almost any sample because the flux of atoms sputtered from the sample is representative of the stoichiometry of the top-most layers. The composition and oxygen content of Bi2Sr2Ca0.86Pr0.14Cu2O8.4 and La1-xSrxCo0.975Fe0.025O3-d, where 0

Published
2009

49. Early prediction of acute necrotizing pancreatitis by artificial intelligence: A prospective cohort-analysis of 2387 cases

Author

Kiss, Szabolcs, primary, Pintér, J., additional, Molontay, R., additional, Nagy, M., additional, Farkas, N., additional, Sipos, Z., additional, Fehérvári, P., additional, Pecze, L., additional, Vincze, A., additional, Takács, T., additional, Czakó, L., additional, Izbéki, F., additional, Halász, A., additional, Boros, E., additional, Hamvas, J., additional, Varga, M., additional, Mickevicius, A., additional, Faluhelyi, N., additional, Farkas, O., additional, Váncsa, S., additional, Nagy, R., additional, Bunduc, S., additional, Hegyi, P. Jenő, additional, Márta, K., additional, Borka, K., additional, Doros, A., additional, Hosszúfalusi, N., additional, Zubek, L., additional, Erőss, B., additional, Párniczky, A., additional, Hegyi, P., additional, Szentesi, A., additional, Molnár, Z., additional, and Földi, M., additional

Published
2022
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