Intra-Cluster Distance Minimization in DNA Methylation Analysis Using an Advanced Tabu-Based Iterative k-Medoids Clustering Algorithm (T-CLUST)

Performance Evaluation of Hospital Economic Management with the Clustering Algorithm Oriented towards Electronic Health Management

In order to study the clustering algorithm based on density grid, the performance evaluation index system of hospital economic management under the application of electronic health management system is constructed. Firstly, this work designs the basic architecture of electronic health management system, classifies and screens the process of index system of electronic health management system, compares the clustering algorithm based on density grid with the simple clustering algorithm based on density or grid, and then applies it to the performance evaluation index system of hospital economic management. According to the principle of Mitchell scoring method, the expert questionnaire of hospital economic management performance evaluation index system was designed, and Delphi method was used to evaluate the candidate indexes from the three dimensions of right, legitimacy, and urgency. The results show that, compared with simple network clustering algorithm and density clustering algorithm, the clustering algorithm based on density network produces higher purity (94% VS 73% VS 67%) and lower entropy (0.9 VS 1.4 VS 1.54), which effectively saves memory consumption, and the difference is statistically significant (P < 0.05). The core indicators with scores above 4.5 in both dimensions include budget revenue implementation rate, budget expenditure implementation rate, implementation rate of special financial appropriation, asset-liability ratio, hospitalization income cost rate, medical insurance settlement rate, average cost of discharged patients, and drug proportion. The coefficient of variation of the first grade index is between 0.05 and 0.14 and that of the second grade index is between 0.05 and 0.15. Clustering algorithm based on density network has higher purity and lower entropy, which can effectively save memory consumption. The performance evaluation index system of hospital economic management finally determines 6 first-level indexes: budget management, financial fund management, cost management, medical expense management, medical efficiency, medical quality, and 25 second-level indexes.

An independent poor-prognosis subtype of hepatocellular carcinoma based on the tumor microenvironment

Background

Hepatocellular carcinoma (HCC) is a highly malignant tumor with a particularly poor prognosis. The tumor microenvironment (TME) is closely associated with tumorigenesis, progression, and treatment. However, the relationship between TME genes and HCC patient prognosis is poorly understood.

Methods

In this study, we identified two prognostic subtypes based on the TME using data from The Cancer Genome Atlas and Gene Expression Omnibus. The Microenvironment Cell Populations-counter method was used to evaluate immune cell infiltration in HCC. Differentially expressed genes between molecular subtypes were calculated with the Limma package, and clusterProfiler was used for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analyses to identify genes related to the independent subtypes. We also integrated mRNA expression data into our bioinformatics analysis.

Results

We identified 4227 TME-associated genes and 640 genes related to the prognosis of HCC. We defined two major subtypes (Clusters 1 and 2) based on the analysis of TME-associated gene expression. Cluster 1 was characterized by increased expression of immune-associated genes and a worse prognosis than Cluster 2.

Conclusions

The identification of these HCC subtypes based on the TME provides further insight into the molecular mechanisms and prediction of HCC prognosis.