Indian healthcare is described as the largest sector, both in revenue and employment. The quality of service—the characteristics that shape care experience beyond technical competence—is rarely... Show More

Indian healthcare is described as the largest sector, both in revenue and employment. The quality of service—the characteristics that shape care experience beyond technical competence—is rarely discussed in the medical literature. This study reveals the determinants that affect the perception of quality of healthcare services from the patients' and service providers' points of view. A cross-sectional method was followed to determine the perception of quality of healthcare services and relating variables including infrastructure, reliability and responsiveness, empathy, affordability, and administration. The data collected from 400 respondents, including patients and service providers, for the study were analyzed using confirmatory factor analysis. Results confirmed that healthcare service quality aspects (i.e., physical environment, staff behavior, responsiveness, affordable services, admission process) positively relate to customers' perception. Findings will help the hospital managers articulate effective strategies to ensure superior quality of healthcare services to customers.

Three years have passed since the sudden outbreak of COVID-19. From that year, the governments of various countries gradually lifted the measures to prevent and control the pandemic. But the number... Show More

Three years have passed since the sudden outbreak of COVID-19. From that year, the governments of various countries gradually lifted the measures to prevent and control the pandemic. But the number of new infections and deaths from novel coronavirus infections has not declined. So we still need to identify and research the COVID-19 virus to minimize the damage to society. In this paper, the authors use the gray level cooccurrence matrix for feature extraction and particle swarm optimization algorithm to find the optimal solution. After that, this method is validated by using the more common K fold cross validation. Finally, the results of the experimental data are compared with the more advanced methods. Experimental data show that this method achieves the initial expectation.

One of the most troubling aspects of the coronavirus disease (COVID-19) pandemic in the US is the disproportionate harm that it has caused to historically marginalized, low income, underserved, and... Show More

One of the most troubling aspects of the coronavirus disease (COVID-19) pandemic in the US is the disproportionate harm that it has caused to historically marginalized, low income, underserved, and uninsured groups. During the emergence of the pandemic, Black, Hispanic, and Asian people have markedly higher infection rates, hospitalization, and death compared with White people. Once infected with COVID-19, persons with lower incomes, underserved, and people of color are at greater risk for hospitalization because they often have more chronic medical comorbidities. The prevalence of hypertension, diabetes, and obesity are higher among low-income, minority populations, all of which can make a COVID-19 infection much worse. In addition, racial and ethnic minority populations are often underinsured and have inferior access to healthcare, which likely results in those infected seeking care later during their illness. This paper explores educational solution-driven discussion about racial public health disparities during the COVID-19 pandemic.

COVID-19 is extremely contagious and has brought serious harm to the world. Many researchers are actively involved in the study of rapid and reliable diagnostic methods for COVID-19. The study... Show More

COVID-19 is extremely contagious and has brought serious harm to the world. Many researchers are actively involved in the study of rapid and reliable diagnostic methods for COVID-19. The study proposes a novel approach to COVID-19 diagnosis. The multiple-distance gray-level co-occurrence matrix (MDGLCM) was used to analyze chest CT images, the GA algorithm was used as an optimizer, and the feedforward neural network was used as a classifier. The results of 10 runs of 10-fold cross-validation show that the proposed method has a sensitivity of 83.38±1.40, a specificity of 81.15±2.08, a precision of 81.59±1.57, an accuracy of 82.26±0.96, an F1-score of 82.46±0.88, an MCC of 64.57±1.90, and an FMI of 82.47±0.88. The proposed MDGLCM-GA-based COVID-19 diagnosis method outperforms the other six state-of-the-art methods.

COVID-19 has swept the world and has had great impact on us. Rapid and accurate diagnosis of COVID-19 is essential. Analysis of chest CT images is an effective means. In this paper, an automatic... Show More

COVID-19 has swept the world and has had great impact on us. Rapid and accurate diagnosis of COVID-19 is essential. Analysis of chest CT images is an effective means. In this paper, an automatic diagnosis algorithm based on chest CT images is proposed. It extracts image features by stationary wavelet entropy (SWE), classifies and trains the input dataset by extreme learning machine (LEM), and finally determines the model through k-fold cross-validation (k-fold CV). By detecting 296 chest CT images of healthy individuals and COVID-19 patients, the algorithm outperforms state-of-the-art methods in sensitivity, specificity, precision, accuracy, F1, MCC, and FMI.

In 2019, the outbreak of a new coronavirus spread rapidly around the world. The use of medical image-assisted diagnosis for suspected patients can provide a more accurate and rapid picture of the... Show More

In 2019, the outbreak of a new coronavirus spread rapidly around the world. The use of medical image-assisted diagnosis for suspected patients can provide a more accurate and rapid picture of the disease. The earlier the diagnosis is made and the earlier the patient is treated, the lower the likelihood of virus transmission. This paper reviews current research advances in the processing of lung CT images in combination with promising deep learning, including image segmentation, recognition, and classification, and provides a comparison in a tabular format, hoping to provide inspiration for their future development.

Congestive heart failure attracts quality initiatives to address its high prevalence and massive impacts. It is a major global public health problem and burden on healthcare systems, especially in... Show More

Congestive heart failure attracts quality initiatives to address its high prevalence and massive impacts. It is a major global public health problem and burden on healthcare systems, especially in developing countries, and the most common cause of hospitalization and readmission among older patients, especially 30-day readmission. This article will share achievement in reducing CHF readmission rate and address and discuss interventions to improve patient quality of life and reduce re-hospitalization.