Logo

Publikacije (37480)

Nazad

Background: Medical professionals (doctors and other medical staff) in the field of healthcare everyday must make calculated decisions which have important consequences, impacting patients on the individual level, local (community), national or global level. Healthcare professionals must at times make these choices with limited information, resources, and knowledge, and yet is is expected that these decisions are highly calculated and accurate. It is important to familiarise oneself with the exact definitions regarding medical decision making. Objective: The aim of this study was to describe application of the most important rules to help decision makers to be good or excellent decision makers in medical practice at every level of health care system. Methods: The author used descriptive method of explanation teoretical and practical issues regarding application of od decision making processes in the praxis, based on searchied scientific literature about this topic deposited in online databases. Results and Discussion: The author of this paper discussed about important topics: a) the importance of medical decision in emergency situations; b) the varies of decision making with solving problems by medical professionals; c) the limitations when it comes to medical decison making; and d) what doctors need to follow regarding decision making in the praxis. Two factors that have influenced to the decision process: a) degree of uncertainty about future events; b) usefulness of outcomes in any particular case. The clinical decision problem analysis process demands: a) explicit formalization of a decision making problem or the description of the medical problem decision with a registration of all possible actions which have to be undertaken and registration of all the possible so determined outcomes. b) construction of the decision tree which presents all described actions and outcomes with predictions of the probabilities and the choice of the most optimal action based on the probability outcome and its use. Doing this allows us to delve deeper into more intricate options present within medical decision making. Simple put, a decision is a choice between two options. The person or entity conducting that decision is the decision maker. The exact definition is “Under the decision should imply some specific action which is selected from several variables or which satisfies the expectation that is previously set”.Many different factors and individuals may be involved in medical decision making, with varying consequences, according to different players and settings. Conclusion: A vital component of medical decision making is evaluation. Decision makers must concisely evaluate situations, in order to make better choices. For example, when examining a health care system, their decisions should consider the following questions, such as, what is the health status of the given population? What economic resources are at the disposal of our patients, and government? How effective is the current healthcare model that is already in place? Does the existing social system pay enough attention to the healthcare protection? Does the organisation structure of the healthcare system satisfy? Are the existing practice and the healthcare technologies secure, effective, and suitable? Are the planning, programming, determination and the choice of priority the adequate to the needs of people? How are the monitoring and evaluation of healthcare system quality organised? These are a few examples of evaluation in medical decision making.

M. Montero‐Odasso, N. van der Velde, F. Martin, M. Petrovic, M. Tan, J. Ryg, Sara G. Aguilar-Navarro, Neil B. Alexander et al.

Abstract Background falls and fall-related injuries are common in older adults, have negative effects on functional independence and quality of life and are associated with increased morbidity, mortality and health related costs. Current guidelines are inconsistent, with no up-to-date, globally applicable ones present. Objectives to create a set of evidence- and expert consensus-based falls prevention and management recommendations applicable to older adults for use by healthcare and other professionals that consider: (i) a person-centred approach that includes the perspectives of older adults with lived experience, caregivers and other stakeholders; (ii) gaps in previous guidelines; (iii) recent developments in e-health and (iv) implementation across locations with limited access to resources such as low- and middle-income countries. Methods a steering committee and a worldwide multidisciplinary group of experts and stakeholders, including older adults, were assembled. Geriatrics and gerontological societies were represented. Using a modified Delphi process, recommendations from 11 topic-specific working groups (WGs), 10 ad-hoc WGs and a WG dealing with the perspectives of older adults were reviewed and refined. The final recommendations were determined by voting. Recommendations all older adults should be advised on falls prevention and physical activity. Opportunistic case finding for falls risk is recommended for community-dwelling older adults. Those considered at high risk should be offered a comprehensive multifactorial falls risk assessment with a view to co-design and implement personalised multidomain interventions. Other recommendations cover details of assessment and intervention components and combinations, and recommendations for specific settings and populations. Conclusions the core set of recommendations provided will require flexible implementation strategies that consider both local context and resources.

H. Pretzsch, A. Bravo‐Oviedo, T. Hilmers, R. Ruiz‐Peinado, L. Coll, M. Löf, Shamim Ahmed, J. Aldea et al.

Heterogeneity of structure can increase mechanical stability, stress resistance and resilience, biodiversity and many other functions and services of forest stands. That is why many silvicultural measures aim at enhancing structural diversity. However, the effectiveness and potential of structuring may depend on the site conditions. Here, we revealed how the stand structure is determined by site quality and results from site-dependent partitioning of growth and mortality among the trees. We based our study on 90 mature, even-aged, fully stocked monocultures of Scots pine ( Pinus sylvestris L.) sampled in 21 countries along a productivity gradient across Europe. A mini-simulation study further analyzed the site-dependency of the interplay between growth and mortality and the resulting stand structure. The overarching hypothesis was that the stand structure changes with site quality and results from the site-dependent asymmetry of competition and mortality. First, we show that Scots pine stands structure across Europe become more homogeneous with increasing site quality. The coefficient of variation and Gini coefficient of stem diameter and tree height continuously decreased, whereas Stand Density Index and stand basal area increased with site index. Second, we reveal a site-dependency of the growth distribution among the trees and the mortality. With increasing site index, the asymmetry of both competition and growth distribution increased and suggested, at first glance, an increase in stand heterogeneity. However, with increasing site index, mortality eliminates mainly small instead of all-sized trees, cancels the size variation and reduces the structural heterogeneity. Third, we modelled the site-dependent interplay between growth partitioning and mortality. By scenario runs for different site conditions, we can show how the site-dependent structure at the stand level emerges from the asymmetric competition and mortality at the tree level and how the interplay changes with increasing site quality across Europe. Our most interesting finding was that the growth partitioning became more asymmetric and structuring with increasing site quality, but that the mortality eliminated predominantly small trees, reduced their size variation and thus reversed the impact of site quality on the structure. Finally, the reverse effects of mode of growth partitioning and mortality on the stand structure resulted in the highest size variation on poor sites and decreased structural heterogeneity with increasing site quality. Since our results indicate where heterogeneous structures need silviculture interventions and where they emerge naturally, we conclude that these findings may improve system understanding and modelling and guide forest management aiming at structurally rich forests.

OBJECTIVE To examine the influence of vehicles on the stability of extemporaneous suspensions of proton pump inhibitors (PPIs), to single out the formulation most suitable for children, providing appropriate evidence and arguments. METHODS A review was performed of data identified from Medline, Embase, Science Direct, as well as public digital archive PubMed, including reference texts, related to the field of stability testing of extemporaneous PPI suspensions. RESULTS Fourteen selected formulations of extemporaneous suspensions are presented and discussed. Depending on the vehicle and its composition, which was analyzed and explained in detail, the suspensions had various beyond-use dates (BUDs). CONCLUSIONS Selected vehicles and the process of preparation had great influence on the stability of extemporaneous PPI suspensions. The suspension with the longest BUD has been singled out, which is especially suitable for use in newborns. Because an explanation is provided for the influence of individual vehicle components on the stability of the mentioned suspensions, this can aid not only in the selection of an adequate formulation, but also in the development of new ones, which will be suited to individual patients.

Can Kızılkale, F. Mehrabadi, Erfan Sadeqi Azer, Eva Pérez-Guijarro, Kerrie L. Marie, M. Lee, Chi-Ping Day, G. Merlino et al.

Background: Coronary New blood in the vascular bed after Coronary Artery Bypass Grafting (CABG) may represent a turning point between ischemia and normal tissue nutrition. Its quantification can help to better understand coronary artery hemodynamics after revascularization. Objective: Quantification of coronary sinus blood flow changes over time after Coronary Artery Bypass Grafting (CABG) using Transthoracic Echocardiography (TTE). Methods: Prospective basic research, with repeated measurements on hospital sample of 61 patients whom CABG was conducted. We performed TTE recordings to measure CS flow before and two times after CABG (1 and 6 postoperative day). We measure CS diameter, Velocity Time Integral (VTI) and systemic hemodynamic data. Data needed for LV mass calculation were recorded once. During statistical analysis we define: α = 0,01, β = 0,01 (power = 1-β β= 0,99), Sample size = 60, Effect size= 0,68. We used ANOVA for Repeated Measures as main statistical test in SPSS. Results: Preoperatively we found low overall CS flow of 181 ±72 ml/min (0,68 ±0,30 ml/gram-LV/min). After surgery there was constant increase of CS flow from 276 ±79 ml/min (1,13 ±0,35 ml/gram-LV/min) first postoperative day, to 355 (±99) ml/min (1,30 ±0,46 ml/gram-LV/min) sixth postoperative day. Discussion: Amount of new blood was statistically significant after CABG with P<0,001. Same result was found after classifying patients per number of graft received, with the highest amount of new blood after four bypasses. Amount of new blood was not different if patient gets two or three bypasses. Conclusion: There was significantly new amount of blood in coronary bed after CABG, with constant increase over first 6 days.

A. Vidak, I. M. Šapić, M. Hadžimehmedović

In the past decade, we have witnessed the emergence of a large number of different computer-based animations and simulations that have the goal to foster better learning of different physics topics. Past studies have shown many benefits of animations and simulations, but for their efficient usage it is very important that teachers are well educated in the teaching material and usage of selected visualizations. Furthermore, studies have proven that augmented reality technology has a potential to reduce cognitive load and improve the quality of physics lectures. Many of these visualizations are generally designed for targeted physics phenomena, and sometimes it is not easy to address specific students’ misconceptions. In this paper, we will present augmented reality animations and a simulation that can generally be useful for teaching about counterintuitive aspects of rolling motion, and specifically address students’ misconceptions about rolling friction and velocity in contact with the ground.

Yibin Zhang, Yang Peng, B. Adebisi, Guan Gui, H. Gačanin, H. Sari

The fast development of intelligent wireless communications enables many devices to access various networks. It often leads to the security risks of malicious access of illegal devices. To ensure a secure and reliable wireless access, it is necessary to identify illegal devices and prevent their attacks accurately. To improve the performance of specific emitter identification (SEI), this paper proposes a multi-scale convolution neural network (MSCNN) based on convolution layers of three branches with different convolution kernel sizes. MSCNN extracts radio frequency fingerprints (RFF) in three receptive fields through different convolution kernels. We verify the identification accuracy using the RF signals conforming to long term evolution (LTE) standard. The experimental results show that our proposed MSCNN-based SEI method can improve the absolute accuracy by 15% and the relative accuracy by 22% in perfect communication environment. In addition, we verify the robustness of proposed MSCNN by comparing identification performance in imperfect environment. Simulation results show that the proposed MSCNN can extract more hidden features through convolution kernels of different sizes, and thus achieves better SEI performance than existing methods.

Xixi Zhang, Haitao Zhao, Hongbo Zhu, B. Adebisi, Guan Gui, H. Gačanin, F. Adachi

Automatic modulation recognition (AMR) technique plays an important role in the identification of modulation types of unknown signal of integrated sensing and communication (ISAC) systems. Deep neural network (DNN) based AMR is considered as a promising method. Considering the complexity of a typical ISAC system, devising the DNN manually with limited knowledge of its various classifications will be very tasking. This paper proposes a neural architecture search (NAS) based AMR method to automatically adjust the structure and parameters of DNN and find the optimal structure under the combination of training and constraints. The proposed NAS-AMR method will improve the flexibility of model search and overcome the difficulty of gradient propagation caused by the non-differentiable quantization function in the process of back propagation. Simulation results are provided to confirm that the proposed NAS-AMR method can identify the modulation types in various ISAC electromagnetic environments. Furthermore, compared with other fixed structure networks, our proposed method delivers the highest recognition accuracy, under the condition of low parameters and floating-point operations (FLOPs).

Yuxin Ji, Xixi Zhang, Yu Wang, H. Gačanin, H. Sari, F. Adachi, Guan Gui

To address the problem of spectrum resources and transmitting power for vehicular networks, this paper proposes a resource allocation (RA) method based on dueling double deep-Q network (D3QN) reinforcement learning (RL). Due to the high mobility of the vehicle, the channel changes rapidly which makes it difficult to accurately collect high-accuracy channel state information at the base station and to perform centralized management. In response of this difficulty, we construct a multi-intelligence model, using Manhattan Grid Layout City Model as the basis of environment and with each vehicle-to-vehicle (V2V) link as an intelligence. They work together to interact with the environment, receive appropriate observations, get rewards, and finally learn to improve the allocation of power and spectrum to enable users to achieve a better entertainment experience and a safer driving environment. Experimental results demonstrate that with proper training mechanism and reward function construction, cooperation among multiple intelligence can be performed in a distributed manner, with improvements in both the capacity of total vehicle-to-infrastructure links and the effective payload delivery success rate of the V2V links compared to common Q-network.

Jie Zhou, Yang Peng, Guan Gui, Yun Lin, B. Adebisi, H. Gačanin, H. Sari

Radio frequency fingerprint (RFF) is regarded as a key technology in physical layer security in various wireless communications systems. Deep learning (DL) has achieved great success in the field of signal identification, particularly in improving performance and eliminating manual feature extraction. However, the training cost of these DL-based methods is usually large. It is unwise to retrain the network with whole data when it comes to new data. Therefore, we propose a novel RFF identification method based on incremental learning (IL), which uses continuous data stream to update the identification model, constantly. Experimental results show that with the increase of increment times, the accuracy of the proposed IL-based method gradually approaches the performance of joint training, and finally reaches 96.79%, which is only 1.9% lower than the performance upper bound.

Nema pronađenih rezultata, molimo da izmjenite uslove pretrage i pokušate ponovo!

Pretplatite se na novosti o BH Akademskom Imeniku

Ova stranica koristi kolačiće da bi vam pružila najbolje iskustvo

Saznaj više