Optimized Reimbursement Scheme of China's New Cooperative Medical System Using Monte Carlo Simulation

China＇s Rural Cooperative Medical System collapsed alongside communal farming at the end of the Maoist period in 1976, leaving most farmers vulnerable[1]. In rural areas, where 80% of people have been without health insurance of any kind, illness has emerged as a leading cause of poverty[24]. To address the poor state of health care among the rural population, in 2003 the Chinese government launched the New Rural Cooperative Medical System （NCMS）,

A Study on Service-Oriented Smart Medical Systems Combined with Key Algorithms in the IoT Environment

A smart medical service system architecture is proposed in this paper to increase medical resource utilization and improve the efficiency of the medical diagnosis process for complex business scenarios in the Medical Internet of Things(MIoT)environment.The resource representation model theory,multi-terminal aggregation algorithm,and the resource discovery algorithm based on latent factor model are also studied.A smart medical service system within the IoT environment is then developed,based on the open source project.Experimental results using real-world datasets illustrate that the proposed smart medical service system architecture can promote the intelligent and efficient management of medical resources to an extent,and assists in the develop towards digitization,intelligence,and precision in the field of medicine.

Significance of vulnerability assessment in establishment of Hainan provincal disaster medical system

Hainan is an island province in south China with a high frequency of unconventional emergencies due to its special geographic location and national military defense role.Given the limited transportation route from Hainan to the outside world,self-rescue is more important to Hainan Province than other provinces in China and it is therefore imperative to establish an independent, scientific as well as efficient provincal disaster medical system in Hainan.The regulatory role for vulnerability analysis/assessment has been demonstrated in establisment of disaster medical system in varoius countries and or regions.In this paper,we attempt to describe/propose how to adopt vulnerability assessment through mathematical modeling of major biophysical social vulnerability factors to establish an independent,scientific,effieicnt and comprehensive provincial disaster medical system in Hainan.

A Study on the Public Awareness of Hierarchical Medical System in Taiwan

The purpose of hierarchical medical system is to lead in terms of improving efficiency, differentiating healthcare services and promoting labor division by changing the healthcare seeking behavior. The purpose of this research aims to discuss the public awareness of hierarchical medical system in Taiwan for the reference of health policy makers. We obtained our research data using a questionnaire survey;the total number of qualified patients was 1340. This research finds that more subjects agreed to the hierarchical medical system and medical referral system, but many people still disagreed with changes to their healthcare seeking choices due to policy promotion. Subtle changes, therefore, are observed that imply a crisis in terms of the trust in healthcare. The healthcare seeking behavior will not change if there is a difference between the medical awareness of patients and policy implementation, and the government needs to be concerned with this result when making policies.

Issues concerning Migrant Workers' Participation in the New Rural Cooperative Medical System and Countermeasures——Based on the Survey in Wenjiang District and Jintang County, Chengdu City

We conduct questionnaire survey of migrant workers in Wenjiang District and Jintang County of Chengdu City,respectively,using the method of key-point investigation and the sampling survey. We describe the status quo of the sample migrant workers' participation in the New Rural Cooperative Medical System,analyze the issues concerning migrant workers' participation in the New Rural Cooperative Medical System,and put forward the countermeasures and recommendations as follows: using many types of medical insurance; establishing universal reimbursement points in strange land and premium-paying system for migrant workers; making the proportion of reimbursement open and transparent; establishing and improving medicare security system for migrant workers.

Restraining Factors and Improving Paths for the Operation Mechanism of New Rural Cooperative Medical System in China

The new rural cooperative medical system has achieved periodical achievements since its establishment.Nevertheless,there are many factors hampering the development of the new system,such as the high cost,the difficulties in fund procurement,the lack of management,the narrow coverage of benefit,the ineffective constraint to the designated medical institutions,the high fund balance rate,and the poor medical facilities and services in rural areas.Countermeasures are put forward to solve these problems,including improving the system design,expanding the coverage of the system,expanding the fund sources,reducing the financing costs,strengthening the fund supervision,enhancing the supervision of designated medical institutions,and improving the capacity of health services in rural areas.

Ultra-Wideband Systems with Energy Harvesting Units for Sensors, 5G, IoT and Medical Systems

The high tech industrial revolution in the last fifty years depleted and ruined the planet natural resources. Energy harvesting is the main challenge in the research in green technologies. Compact wideband efficient antennas are crucial for energy harvesting portable sensors and systems. Small antennas have low efficiency. The efficiency of 5G, IoT communication and energy harvesting systems may be improved by using wideband efficient passive and active antennas. The system dynamic range may be improved by connecting amplifiers to the small antenna feed line. Ultra-wideband portable harvesting systems are presented in this paper. This paper presents new Ultra-Wideband energy harvesting system and antennas in frequencies ranging from 0.15 GHz to 18 GHz. Three wideband antennas cover the frequency range from 0.15 GHz to 18 GHz. A wideband metamaterial antenna with metallic strips covers the frequency range from 0.15 GHz to 0.42 GHz. The antenna bandwidth is around 75% for VSWR better than 2.3:1. A wideband slot antenna covers the frequency range from 0.4 GHz to 6.4 GHz. A wideband fractal notch antenna covers the frequency range from 6 GHz to 18 GHz. Printed passive and active notch and slot antennas are compact, low cost and have low volume. The active antennas may be employed in energy harvesting portable systems. The antennas and the harvesting system components may be assembled on the same, printed board. The printed notch and slot antennas bandwidth are from 75% to 100% for VSWR better than 3:1. The slot and notch antenna gain is around 3 dBi with efficiency higher than 90%. The antennas electrical parameters were computed in free space and near the human body. There is a good agreement between computed and measured results.

Research on the Problems and Countermeasures of New Rural Cooperative Medical System

Our country rural area has carried out broad practice on new model system of rural cooperative medical services, and the rural new medical treatment system has developed quickly. However, there are still many problems which needs us to solve. This article will analysis its present situation, problems and reasons, then give some suggestions to solve these problems. The new rural cooperative medical system has made great achievements since its implementation, which is a radical reform of the traditional medical systen. Lcd by thc govcmmcnt, trying to solve the majority of the Chinese population of the peasant groups to see the doctor difficult and expensive medical problems, and effectively protect the vital interests of farmers, so that people=oriented, establish and improve the rural medical service system. This paper analyzes the status quo of the new rural cooperative medical system, puts forward the problems, finds the reasons, and puts forward the corresponding countermeasures on the basis of this.

Privacy-Preserving Healthcare and Medical Data Collaboration Service System Based on Blockchain and Federated Learning

As the volume of healthcare and medical data increases from diverse sources,real-world scenarios involving data sharing and collaboration have certain challenges,including the risk of privacy leakage,difficulty in data fusion,low reliability of data storage,low effectiveness of data sharing,etc.To guarantee the service quality of data collaboration,this paper presents a privacy-preserving Healthcare and Medical Data Collaboration Service System combining Blockchain with Federated Learning,termed FL-HMChain.This system is composed of three layers:Data extraction and storage,data management,and data application.Focusing on healthcare and medical data,a healthcare and medical blockchain is constructed to realize data storage,transfer,processing,and access with security,real-time,reliability,and integrity.An improved master node selection consensus mechanism is presented to detect and prevent dishonest behavior,ensuring the overall reliability and trustworthiness of the collaborative model training process.Furthermore,healthcare and medical data collaboration services in real-world scenarios have been discussed and developed.To further validate the performance of FL-HMChain,a Convolutional Neural Network-based Federated Learning(FL-CNN-HMChain)model is investigated for medical image identification.This model achieves better performance compared to the baseline Convolutional Neural Network(CNN),having an average improvement of 4.7%on Area Under Curve(AUC)and 7%on Accuracy(ACC),respectively.Furthermore,the probability of privacy leakage can be effectively reduced by the blockchain-based parameter transfer mechanism in federated learning between local and global models.

Optimizing the Clinical Decision Support System (CDSS) by Using Recurrent Neural Network (RNN) Language Models for Real-Time Medical Query Processing

This research aims to enhance Clinical Decision Support Systems(CDSS)within Wireless Body Area Networks(WBANs)by leveraging advanced machine learning techniques.Specifically,we target the challenges of accurate diagnosis in medical imaging and sequential data analysis using Recurrent Neural Networks(RNNs)with Long Short-Term Memory(LSTM)layers and echo state cells.These models are tailored to improve diagnostic precision,particularly for conditions like rotator cuff tears in osteoporosis patients and gastrointestinal diseases.Traditional diagnostic methods and existing CDSS frameworks often fall short in managing complex,sequential medical data,struggling with long-term dependencies and data imbalances,resulting in suboptimal accuracy and delayed decisions.Our goal is to develop Artificial Intelligence(AI)models that address these shortcomings,offering robust,real-time diagnostic support.We propose a hybrid RNN model that integrates SimpleRNN,LSTM layers,and echo state cells to manage long-term dependencies effectively.Additionally,we introduce CG-Net,a novel Convolutional Neural Network(CNN)framework for gastrointestinal disease classification,which outperforms traditional CNN models.We further enhance model performance through data augmentation and transfer learning,improving generalization and robustness against data scarcity and imbalance.Comprehensive validation,including 5-fold cross-validation and metrics such as accuracy,precision,recall,F1-score,and Area Under the Curve(AUC),confirms the models’reliability.Moreover,SHapley Additive exPlanations(SHAP)and Local Interpretable Model-agnostic Explanations(LIME)are employed to improve model interpretability.Our findings show that the proposed models significantly enhance diagnostic accuracy and efficiency,offering substantial advancements in WBANs and CDSS.

A novel medical image data protection scheme for smart healthcare system

The Internet of Multimedia Things(IoMT)refers to a network of interconnected multimedia devices that communicate with each other over the Internet.Recently,smart healthcare has emerged as a significant application of the IoMT,particularly in the context of knowledge‐based learning systems.Smart healthcare systems leverage knowledge‐based learning to become more context‐aware,adaptable,and auditable while maintain-ing the ability to learn from historical data.In smart healthcare systems,devices capture images,such as X‐rays,Magnetic Resonance Imaging.The security and integrity of these images are crucial for the databases used in knowledge‐based learning systems to foster structured decision‐making and enhance the learning abilities of AI.Moreover,in knowledge‐driven systems,the storage and transmission of HD medical images exert a burden on the limited bandwidth of the communication channel,leading to data trans-mission delays.To address the security and latency concerns,this paper presents a lightweight medical image encryption scheme utilising bit‐plane decomposition and chaos theory.The results of the experiment yield entropy,energy,and correlation values of 7.999,0.0156,and 0.0001,respectively.This validates the effectiveness of the encryption system proposed in this paper,which offers high‐quality encryption,a large key space,key sensitivity,and resistance to statistical attacks.

3D image system improves the learning curve and contributes to medical education of rhinoplasty

Background: Rhinoplasty is a complex surgical procedure that requires critical analysis and precise design before surgery, making it a challenging operation for both the surgical team and medical educators. This study aimed to evaluate the impact of 3D design involvement on learning curves and to establish a more effective method for rhinoplasty education.Methods: Surgeons who participated in an educational program were divided into two groups. The experimental group was involved in the 3D design before the operation, and the control group was asked to review the rhinoplasty atlas. A self-assessment questionnaire was used to evaluate the learning curve of the eight rhinoplasty procedures for each surgeon, and the overall satisfaction rate data were also collected.Results: The self-assessment scores in both groups showed an increasing trend from the first to the eighth operation. The mean scores of the experimental group were significantly higher than those of the control group at the fifth operation(P=0.01). The satisfaction rate of the experimental group(91.7%) was higher than that of the control group(54.5%).Conclusion: The 3D imaging system can improve the learning curve and satisfaction rate of rhinoplasty education,proving that it is an easy and effective tool for medical education.

Ethics of Human Resources Management in the Cameroonian Health System, Medical Nomadism and the Ineffectiveness of the Fight against High Blood Pressure

Context/objectives: The fight against Chronic Non-Communicable Diseases (NCDs) is a long-term undertaking, which requires available, motivated and well-managed human resources (HR). The administrative management of skills on both qualitative and quantitative levels is one of the essential functions of a health system. To better implement policies of fight against High Blood Pressure (HBP) and other chronic diseases, it is important to establish strategies to retain health personnel. This loyalty requires favorable working conditions and consideration of the contribution-reward couple. Good working conditions are likely to reduce the phenomenon of medical nomadism;conversely, poor HR management can contribute to their exodus towards exotic “green pastures”, thus leading to an additional crisis in the Cameroonian health system. The fight against HBP is a complex, multifaceted and multifactorial reality that requires appropriate management model for all types of resources mainly HR. The main objective of this research is to show the impact of poor management of human resources in Cameroon health system on medical nomadism and the ineffectiveness of the fight against High Blood Pressure. Method: A cross-sectional descriptive survey among five hundred (500) health facilities in the center region of Cameroon has been conducted. A stratified probabilistic technique has been used, and the number of health facilities to be surveyed has been determined using the “sample size estimation table” of Depelteau. The physical questionnaires have been printed and then distributed to data collectors. After data collection, the latter were grouped during processing in Excel sheets. The Chi-square test was used for data with a qualitative value and that of Kolmogorov-Sminorf for data with a quantitative value to assess the normality and reliability of data. The Crochach’s Alpha reliability test allowed us to have a summary of the means and variances and then to search for intragroup correlations between variables. Descriptive analysis was possible with the XLSTAT 2016 software. Results: 43.60% of Health Facilities (HF) managers were unqualified. 82.20% of HF managers have staff in a situation of professional insecurity. They are mainly contractual (49.00), decision-making agents (24.40%), casual agents (08.80). The proportion of unstable personnel is average of 22.00% and very unstable, 12.00%.

Functional Confirmation Using a Medical X-Ray System of a Semiconductor Survey Meter

In recent years, semiconductor survey meters have been developed and are in increasing demand worldwide. This study determined if it is possible to use the X-ray system installed in each medical facility to calculate the time constant of a semiconductor survey meter and confirm the meter’s function. An additional filter was attached to the medical X-ray system to satisfy the standards of N-60 to N-120, more copper plates were added as needed, and the first and second half-value layers were calculated to enable comparisons of the facility’s X-ray system quality with the N-60 to N-120 quality values. Next, we used a medical X-ray system to measure the leakage dose and calculate the time constant of the survey meter. The functionality of the meter was then checked and compared with the energy characteristics of the meter. The experimental results showed that it was possible to use a medical X-ray system to reproduce the N-60 to N-120 radiation quality values and to calculate the time constant from the measured results, assuming actual leakage dosimetry for that radiation quality. We also found that the calibration factor was equivalent to that of the energy characteristics of the survey meter.

Congruent Feature Selection Method to Improve the Efficacy of Machine Learning-Based Classification in Medical Image Processing

Machine learning(ML)is increasingly applied for medical image processing with appropriate learning paradigms.These applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws/diseases for diagnosis.The primary concern of ML applications is the precise selection of flexible image features for pattern detection and region classification.Most of the extracted image features are irrelevant and lead to an increase in computation time.Therefore,this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image features.This process trains the learning paradigm using similarity and correlation-based features over different textural intensities and pixel distributions.The similarity between the pixels over the various distribution patterns with high indexes is recommended for disease diagnosis.Later,the correlation based on intensity and distribution is analyzed to improve the feature selection congruency.Therefore,the more congruent pixels are sorted in the descending order of the selection,which identifies better regions than the distribution.Now,the learning paradigm is trained using intensity and region-based similarity to maximize the chances of selection.Therefore,the probability of feature selection,regardless of the textures and medical image patterns,is improved.This process enhances the performance of ML applications for different medical image processing.The proposed method improves the accuracy,precision,and training rate by 13.19%,10.69%,and 11.06%,respectively,compared to other models for the selected dataset.The mean error and selection time is also reduced by 12.56%and 13.56%,respectively,compared to the same models and dataset.

Medical Diagnosis Based on Multi-Attribute Group Decision-Making Using Extension Fuzzy Sets,Aggregation Operators and Basic Uncertainty Information Granule

Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.

Relationship between the use of smart medical services and mental health status

In this editorial,I comment on the article by Zhang et al.To emphasize the importance of the topic,I discuss the relationship between the use of smart medical devices and mental health.Smart medical services have the potential to positively influence mental health by providing monitoring,insights,and inter-ventions.However,they also come with challenges that need to be addressed.Understanding the primary purpose for which individuals use these smart tech-nologies is essential to tailoring them to specific mental health needs and prefe-rences.

Getting physical with medical education:Exercise based virtual anatomy review classes for medical students

The benefits of regular physical activity are well known.Yet,few studies have examined the effectiveness of integrating physical activity(PA)into curricula within a post-secondary setting.To investigate the incorporation of PA into medical curriculum,we developed a series of optional exercise-based review sessions designed to reinforce musculoskeletal(MSK)anatomy course material.These synchronous sessions were co-taught by a group fitness instructor and an anatomy instructor.The fitness instructor would lead students through both strength and yoga style exercises,while the anatomy instructor asked questions about relevant anatomical structures related to course material previously covered.After the sessions,participants were asked to evaluate the classes on their self-reported exam preparedness in improving MSK anatomy knowledge,PA levels,and mental wellbeing.Thirty participants completed surveys;a majority agreed that the classes increased understanding of MSK concepts(90.0%)and activity levels(97.7%).Many(70.0%)felt that the classes helped reduce stress.The majority of respondents(90.0%)agreed that the classes contributed to increased feelings of social connectedness.Overall,medical students saw benefit in PA based interventions to supplement MSK course concepts.Along with increasing activity levels and promoting health behaviours,integrating PA into medical curriculum may improve comprehension of learning material,alleviate stress and foster social connectivity among medical students.

Development of the New Rural Cooperative Medical System in China

Based on a survey conducted by our research team at the Chinese Academy of Social Sciences, the present paper reports on the development of China＇s new rural cooperative medical system set up in late 2002. The new rural cooperative medical system is different from the old system in that it is organized, guided and supported by the government but that rural residents voluntarily participate in its administration. It is financed by individuals, collectives and the government. The new cooperative medical system focuses on serious disease planning and mutual aid and fraternily between rural residents in health care. The results of our survey indicate that the new rural medical system has been successful up to now but that it also has some problems. China needs to pay more attention to overcoming the difficulties and challenges it faces in terms of future medical needs so that a mechanism for its sustainable development can be established.

Defects in the medical system and distortion in drug pricing

Through an analysis of China＇s healthcare system and the regulatory model of pharmaceutical pricing, the paper concludes that the prime cause of pharmaceutical pricing inflation is the twodirectional monopoly of public healthcare institutions on pharmaceutical retailing. The low cost of medical services means that public hospitals can legitimately use the sale of pharmaceuticals to subsidize the provision of services. Moreover, the policy of controlling the rate of return gives public hospitals a further incentive to buy and sell high-cost pharmaceuticals. In addition, the policy of independent pricing together with the laxity of the system for approving new drugs allows the makers of pharmaceutical products to charge higher prices and facilitates public hospitals＇ sale of high-priced drugs. All of these problems result from inappropriate government controls. Therefore, the basic strategy for solving the problem of inflated pharmaceutical prices should be to lessen government controls on healthcare, open up retail sales of prescription medicines, and reform the public healthcare system and medical insurance reimbursement, breaking the monopoly of public hospitals.