Preventive medicine
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Preventive medicine · Sep 2023
The effect of enteral nutrition nursing intervention on postoperative treatment of chronic critically ill patients: Health prevention data analysis.
The field of genomics has witnessed remarkable advancements, leading to the gradual clarification of the genetic mechanism underlying various cancers. As a result, there has been an increased emphasis on gene prevention and treatment. Against this backdrop, this paper aims to examine the impact of enteral nutrition nursing intervention on the postoperative treatment of patients with chronic critical illness, with a focus on health prevention. ⋯ The study's results provide valuable insights into the efficacy of enteral nutrition nursing intervention in the postoperative treatment of patients with chronic critical illness. By improving the nutritional status of patients, enteral nutrition nursing intervention can help reduce the risk of complications, shorten the length of hospital stay, and enhance the effectiveness of postoperative rehabilitation. These findings underscore the importance of adopting effective interventions such as enteral nutrition nursing to improve the therapeutic outcomes of chronic critical illness patients and achieve the goal of health prevention.
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Preventive medicine · Sep 2023
Predicting diabetes with multivariate analysis an innovative KNN-based classifier approach.
Diabetes seems to be a severe protracted disease or combination of biochemical disorders. A person's blood glucose (BG) levels remain elevated for an extended period because tissues lack and non-reaction to hormones. Such conditions are also causing longer-term obstacles or serious health issues. ⋯ K-Nearest Neighbourhood (KNN) seems to be a common and straightforward ML method for creating illness threat prognosis models based on pertinent clinical information. We provide an adaptable neuro-fuzzy inference K-Nearest Neighbourhood (AF-KNN) learning-dependent forecasting system relying on patients' behavioural traits in several aspects to obtain our aim. That method identifies the best proportion of neighborhoods having a reduced inaccuracy risk to improve the predicting performance of the final system.
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Preventive medicine · Sep 2023
Sex-specific population attributable risk factors for cardiovascular and all-cause mortality in the general population: Findings from the China PEACE million persons project.
Little evidence exists regarding the sex-specific population attributable risk factors for cardiovascular and all-cause mortality in the Chinese general population. We used a sub-cohort of the China Patient-Centered Evaluative Assessment of Cardiac Events million persons project to evaluate the overall and sex-specific associations and population attributable fractions (PAFs) of twelve risk factors for cardiovascular and all-cause mortality. 95,469 participants were included between January 2016 and December 2020. The twelve risk factors (including four socioeconomic status and eight modifiable risk factors) were collected or measured at baseline. ⋯ When stratified by sex, men had more risk factors that were significantly attributable to mortality than women, whereas low educational attainment had a more pronounced impact on female cardiovascular health. This study found that the twelve risk factors collectively explained a significant proportion of PAFs for all-cause and cardiovascular mortality. Several sex-related disparities in the associations between risk factors and mortality were noted.
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Preventive medicine · Sep 2023
A microbiological identification and recovery actions of critical symptoms of anammox image bacteria.
Currently, the risks posed by bacteria are becoming increasingly important. It now appears that the cell wall of Anammox image bacteria is very different from what has been generally considered for many years. Not every textbook contains the peptidoglycan on the cell wall of Anammox image bacteria - the sugar-protein chain that strengthens the cells of most bacteria. ⋯ A new algorithm is proposed to discover that Anammox image bacteria contain peptidoglycan, which completes a theory in microbiology. The identification of different diseases is listed, and the proposed model compares the exact results while comparing the parameters like accuracy, precision, recall, and F1-Score. Keywords: Anammox image bacteria, cell wall, cell stability, cryo-electron, microscope images, accuracy, precision, recall, F1-score.
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Preventive medicine · Sep 2023
Athlete body fat rate monitoring and motion image simulation based on SDN data center network and sensors.
With the development of artificial intelligence technology, new software is also emerging in an endless stream. On the basis of sensors, the new software realizes the separation of network control layer and data layer, thereby improving network throughput and link utilization. With the gradual maturity of deep reinforcement learning technology, the redefined network architecture can be managed and controlled through software, making the network evolve toward a more intelligent direction. ⋯ This paper proposes a scheduling strategy based on machine learning, combining the reinforcement learning algorithm in machine learning and deep reinforcement learning algorithm, setting the key factors of reinforcement learning, and applying it to real-time sports images of athletes, combining the sports characteristics of athletes, Set the action and reward value. Then use the algorithm to allocate a reasonable path for data transmission according to the real-time status to reduce network delay. This article will use sensor technology and data center network to provide a new method for athletes' real-time motion images and body fat percentage.