Rethinking Medical Report Generation: Disease Revealing Enhancement with Knowledge Graph

Knowledge Graph (KG) plays a crucial role in Medical Report Generation (MRG) because it reveals the relations among diseases and thus can be utilized to guide the generation process. However, constructing a comprehensive KG is labor-intensive and its applications on the MRG process are under-explored. In this study, we establish a complete KG on chest X-ray imaging that includes 137 types of diseases and abnormalities. Based on this KG, we find that the current MRG data sets exhibit a long-tailed problem in disease distribution. To mitigate this problem, we introduce a novel augmentation strategy that enhances the representation of disease types in the tail-end of the distribution. We further design a two-stage MRG approach, where a classifier is first trained to detect whether the input images exhibit any abnormalities. The classified images are then independently fed into two transformer-based generators, namely, ``disease-specific generator" and ``disease-free generator" to generate the corresponding reports. To enhance the clinical evaluation of whether the generated reports correctly describe the diseases appearing in the input image, we propose diverse sensitivity (DS), a new metric that checks whether generated diseases match ground truth and measures the diversity of all generated diseases. Results show that the proposed two-stage generation framework and augmentation strategies improve DS by a considerable margin, indicating a notable reduction in the long-tailed problem associated with under-represented diseases

Zhodnocení finanční pozice vybrané společnosti

Financial analysis should be based on value, and the range of value is very wide. Value is based on the business. The foothold is the good and bad of the business, to judge whether the current business development is good or bad, and how to maintain or improve it in the future. The results of the analysis can make investors know more clearly whether this company is worth investing in. The goal of the thesis is to analyze and evaluate Evergrande Group's financial performance, based on data from Evergrande Group's financial statements from 2014 to 2018. This thesis is divided into five chapters. The first and the last chapter is introduction and conclusion of the thesis. The second chapter is devoted to financial analysis methodology, we will describe meaning and goal of financial analysis and financial statement as a basic tool for analysis. The third chapter includes the overview of Evergrande Group, social responsibility of Evergrande Group and Evergrande Group's main competitors. In the fourth chapter we will calculate and analyze the results of financial analysis.Financial analysis should be based on value, and the range of value is very wide. Value is based on the business. The foothold is the good and bad of the business, to judge whether the current business development is good or bad, and how to maintain or improve it in the future. The results of the analysis can make investors know more clearly whether this company is worth investing in. The goal of the thesis is to analyze and evaluate Evergrande Group's financial performance, based on data from Evergrande Group's financial statements from 2014 to 2018. This thesis is divided into five chapters. The first and the last chapter is introduction and conclusion of the thesis. The second chapter is devoted to financial analysis methodology, we will describe meaning and goal of financial analysis and financial statement as a basic tool for analysis. The third chapter includes the overview of Evergrande Group, social responsibility of Evergrande Group and Evergrande Group's main competitors. In the fourth chapter we will calculate and analyze the results of financial analysis.154 - Katedra financívelmi dobř

Analýza EaR aplikací metodologie CorporateMetrics

The main goal is to use the CorporateMetrics methodology to predict the Sinopec's operating profit in 2021 under market risk. This thesis includes five chapters. The first chapter is a general introduction to the thesis. The second chapter deals with a theoretical description. The third chapter focuses on Sinopec. The fourth chapter applies the CorporateMetrics methodology to the analysis of the selected company. The fifth chapter is a conclusion of the whole thesis. In chapter 2, the theoretical introduction to CorporateMetrics is divided into three main parts. These are definition of CorporateMetrics, framework components and the comparison to other risk management tools. The framework components include the metric specification, the exposure mapping, the scenario generation, valuation and the risk computation. In chapter 3, the Sinopec will be introduced in more detail. It will start with a general introduction to Sinopec, followed by the history of the company. A brief overview of Sinopec's main competitors will also be presented and compared. Finally, a SWOT analysis of Sinopec will be presented. In chapter 4, the part of CorporateMetrics that will be used to measure risk, mainly using the Earning-at-Risk analysis. The 1000 scenarios of crude oil prices and market rates will be modelled. Then, the parameters that will be used to calculate the operating profit will then be calculated. Finally, a valuation of the operating profit can be obtained. The results are expressed as frequency and probability distributions and are also presented graphicallyThe main goal is to use the CorporateMetrics methodology to predict the Sinopec's operating profit in 2021 under market risk. This thesis includes five chapters. The first chapter is a general introduction to the thesis. The second chapter deals with a theoretical description. The third chapter focuses on Sinopec. The fourth chapter applies the CorporateMetrics methodology to the analysis of the selected company. The fifth chapter is a conclusion of the whole thesis. In chapter 2, the theoretical introduction to CorporateMetrics is divided into three main parts. These are definition of CorporateMetrics, framework components and the comparison to other risk management tools. The framework components include the metric specification, the exposure mapping, the scenario generation, valuation and the risk computation. In chapter 3, the Sinopec will be introduced in more detail. It will start with a general introduction to Sinopec, followed by the history of the company. A brief overview of Sinopec's main competitors will also be presented and compared. Finally, a SWOT analysis of Sinopec will be presented. In chapter 4, the part of CorporateMetrics that will be used to measure risk, mainly using the Earning-at-Risk analysis. The 1000 scenarios of crude oil prices and market rates will be modelled. Then, the parameters that will be used to calculate the operating profit will then be calculated. Finally, a valuation of the operating profit can be obtained. The results are expressed as frequency and probability distributions and are also presented graphically154 - Katedra financídobř

Catalytic single particle nano-impacts: Theory and experiment. poly(vinylferrocene) modified graphene nanoplatelet mediated L-cysteine oxidation

The theory of catalytic nano-impacts is developed specifically for the case of a single particle in contact with an electrode for a short period of time in which it mediates electron transfer to or from a species in homogeneous solution. The theory is applied to impacts of chemically modified graphene nanoplatelets in which the immobilized ferrocene/ferrocenium couple is used to mediate the oxidation of L-cysteine in aqueous solution. Theory and experiment are in good agreement and the catalytic rate constant is found to be 2.4 ± 1.2 M-1s-

Research on the Status Quo and Satisfaction of ' Internet + ' Home Care Model in Hangzhou in the Post-Epidemic Era

This paper takes Hangzhou as an example to study the current situation of the "Internet +" home care model in Hangzhou in the post-epidemic era and the satisfaction of citizens with this new pension model. We established a structural equation model of citizens' satisfaction with the "Internet +" home care model, and calculated the satisfaction index by combining the CSI satisfaction index

FedAC: An Adaptive Clustered Federated Learning Framework for Heterogeneous Data

Clustered federated learning (CFL) is proposed to mitigate the performance deterioration stemming from data heterogeneity in federated learning (FL) by grouping similar clients for cluster-wise model training. However, current CFL methods struggle due to inadequate integration of global and intra-cluster knowledge and the absence of an efficient online model similarity metric, while treating the cluster count as a fixed hyperparameter limits flexibility and robustness. In this paper, we propose an adaptive CFL framework, named FedAC, which (1) efficiently integrates global knowledge into intra-cluster learning by decoupling neural networks and utilizing distinct aggregation methods for each submodule, significantly enhancing performance; (2) includes a costeffective online model similarity metric based on dimensionality reduction; (3) incorporates a cluster number fine-tuning module for improved adaptability and scalability in complex, heterogeneous environments. Extensive experiments show that FedAC achieves superior empirical performance, increasing the test accuracy by around 1.82% and 12.67% on CIFAR-10 and CIFAR-100 datasets, respectively, under different non-IID settings compared to SOTA methods.Comment: 14 pages, 4 figure