BeFOI: A Novel Method Based on Conditional Diffusion Model for Medical Image Denoising

The progress in medical imaging technology highlights the importance of image quality for effective diagnosis and treatment.Yet,noise during capture and transmission can compromise image accuracy and reliability,complicating clinical decisions.The rising interest in diffusion models has led to their exploration of denoising images.We present Be-FOI(Better Fluoro Images),a weakly supervised model that uses cine images to denoise fluoroscopic images,both DR types.Trained through precise noise estimation and simulation,BeFOI employs Markov chains to denoise using only the fluoroscopic image as guidance.Our tests show that BeFOI outperforms other methods,reducing noise and enhancing clar-ity and diagnostic utility,making it an effective post-processing tool for medical images.

Research on the Application and Effectiveness of the DRG Model on Perioperative Medical Management of Cholecystectomy

Objective:This study aimed to explore the application and effectiveness of the DRG model in the perioperative management of cholecystectomy.By comparing the DRG model with traditional management methods,this study focused on evaluating the potential impact of the DRG model in improving surgical efficiency and reducing complication rates and medical costs.Methods:The random envelope method was used to divide patients scheduled for cholecystectomy from January 2021 to October 2023 into two groups:one group underwent surgery under the DRG model(experimental group),and the other group underwent the traditional management model(control group).Data including basic information,surgery-related data,length of stay,complication records,and medical expenses were collected.Data analysis was carried out using a t-test and chi-square(χ2)test.Results:Results showed that the DRG model shortened the average length of stay,decreased the incidence of complications,reduced medical expenses,and increased patient satisfaction.These results demonstrate the effectiveness of the DRG model in the perioperative management of cholecystectomy,especially in improving surgical efficiency,reducing medical costs,and improving patient satisfaction.Conclusion:The DRG model in the perioperative management of cholecystectomy can significantly improve medical service quality and efficiency and enhance patient satisfaction as compared to traditional treatment methods.

Adapter Based on Pre-Trained Language Models for Classification of Medical Text

We present an approach to classify medical text at a sentence level automatically.Given the inherent complexity of medical text classification,we employ adapters based on pre-trained language models to extract information from medical text,facilitating more accurate classification while minimizing the number of trainable parameters.Extensive experiments conducted on various datasets demonstrate the effectiveness of our approach.

The Practice and Exploration of Applying EBM to Bilingual Teaching of Medical Genetics at OSBCM

In the process of teaching medical genetics of undergraduate clinical medicine, the practice and exploration of applying EBM to the bilingual teaching of OSBCM medical genetics are carried out. Using CBL and PBL as the carrier can make up for the shortcomings of a single teaching mode, synthesize the advantages of multiple teaching modes. It starts from integrating the basic theoretical knowledge of medicine and clinical practice knowledge, improving students’ bilingual level of medical genetics, cultivating students’ literature retrieval ability, and promoting early clinical, multi-clinical and repeated clinical consciousness for medical students. Therefore, it is more conducive to cultivate students’ ability to learn independently, accurately analyze and solve problems, improve medical students’ clinical thinking ability and scientific research awareness, improve medical students’ ability of international communication, and lay a solid foundation for improving medical students’ future post competence, innovative spirit and lifelong learning ability.

A Study of Blended-teaching Model in Medical English

Based on the analysis of the current college Medical English teaching and the study of the blendedteaching model,the author practiced the model in the real teaching.In the process,the author verified the usefulness and effectiveness of the Blended-teaching Model,which can break the limitation of the classroom teaching.The students could contact with each other and also with the teacher conveniently whatever in-class and offclass in the learning process.

Exploring and Practicing a Teaching Model of Dialogue-scene Simulation in Medical English

Practicing dialogue-scene simulation in medical English can integrate effectively learning resources, activate the class atmosphere, enrich contents of courses, train language skills and raise students' cooperated consciousness.Furthermore,practicing dialogue-scene simulation can promote reform of teaching estimation-model, teaching quality and efficiency. In a word, practicing dialogue-scene simulation deserves further exploration and promotion.

A Review of the Logistic Regression Model with Emphasis on Medical Research

This study explored and reviewed the logistic regression (LR) model, a multivariable method for modeling the relationship between multiple independent variables and a categorical dependent variable, with emphasis on medical research. Thirty seven research articles published between 2000 and 2018 which employed logistic regression as the main statistical tool as well as six text books on logistic regression were reviewed. Logistic regression concepts such as odds, odds ratio, logit transformation, logistic curve, assumption, selecting dependent and independent variables, model fitting, reporting and interpreting were presented. Upon perusing the literature, considerable deficiencies were found in both the use and reporting of LR. For many studies, the ratio of the number of outcome events to predictor variables (events per variable) was sufficiently small to call into question the accuracy of the regression model. Also, most studies did not report on validation analysis, regression diagnostics or goodness-of-fit measures;measures which authenticate the robustness of the LR model. Here, we demonstrate a good example of the application of the LR model using data obtained on a cohort of pregnant women and the factors that influence their decision to opt for caesarean delivery or vaginal birth. It is recommended that researchers should be more rigorous and pay greater attention to guidelines concerning the use and reporting of LR models.

Software Process Modeling with UML in Development of Medical Insurance MIS

This paper describes how to use the Unified Modeling Language (UML) to modeling software processes in medical insurance MIS, and compares UML Modeling method with classic PO(Process Oriented) Modeling method. It indicates that the whole performance of application system model described by UML is much better than the one described by PO.

Research on a Fog Computing Architecture and BP Algorithm Application for Medical Big Data

Although the Internet of Things has been widely applied,the problems of cloud computing in the application of digital smart medical Big Data collection,processing,analysis,and storage remain,especially the low efficiency of medical diagnosis.And with the wide application of the Internet of Things and Big Data in the medical field,medical Big Data is increasing in geometric magnitude resulting in cloud service overload,insufficient storage,communication delay,and network congestion.In order to solve these medical and network problems,a medical big-data-oriented fog computing architec-ture and BP algorithm application are proposed,and its structural advantages and characteristics are studied.This architecture enables the medical Big Data generated by medical edge devices and the existing data in the cloud service center to calculate,compare and analyze the fog node through the Internet of Things.The diagnosis results are designed to reduce the business processing delay and improve the diagnosis effect.Considering the weak computing of each edge device,the artificial intelligence BP neural network algorithm is used in the core computing model of the medical diagnosis system to improve the system computing power,enhance the medical intelligence-aided decision-making,and improve the clinical diagnosis and treatment efficiency.In the application process,combined with the characteristics of medical Big Data technology,through fog architecture design and Big Data technology integration,we could research the processing and analysis of heterogeneous data of the medical diagnosis system in the context of the Internet of Things.The results are promising:The medical platform network is smooth,the data storage space is sufficient,the data processing and analysis speed is fast,the diagnosis effect is remarkable,and it is a good assistant to doctors’treatment effect.It not only effectively solves the problem of low clinical diagnosis,treatment efficiency and quality,but also reduces the waiting time of patients,effectively solves the contradiction between doctors and patients,and improves the medical service quality and management level.

Improved Medical Image Segmentation Model Based on 3D U-Net

With the widespread application of deep learning in the field of computer vision,gradually allowing medical image technology to assist doctors in making diagnoses has great practical and research significance.Aiming at the shortcomings of the traditional U-Net model in 3D spatial information extraction,model over-fitting,and low degree of semantic information fusion,an improved medical image segmentation model has been used to achieve more accurate segmentation of medical images.In this model,we make full use of the residual network(ResNet)to solve the over-fitting problem.In order to process and aggregate data at different scales,the inception network is used instead of the traditional convolutional layer,and the dilated convolution is used to increase the receptive field.The conditional random field(CRF)can complete the contour refinement work.Compared with the traditional 3D U-Net network,the segmentation accuracy of the improved liver and tumor images increases by 2.89%and 7.66%,respectively.As a part of the image processing process,the method in this paper not only can be used for medical image segmentation,but also can lay the foundation for subsequent image 3D reconstruction work.

Maturity Assessment of Hospital Information Systems Based on Electronic Medical Record Adoption Model (EMRAM)— Private Hospital Cases in Iran

Introduction: Today, information technology is considered as an important national development principle in each country which is applied in different fields. Health care as a whole and the hospitals could be regarded as a field and organizations with most remarkable IT applications respectively. Although different benchmarks and frameworks have been developed to assess different aspects of Hospital Information Systems (HISs) by various researchers, there is not any suitable reference model yet to benchmark HIS in the world. Electronic Medical Record Adoption Model (EMRAM) has been currently presented and is globally well-known to benchmark the rate of HIS utilization in the hospitals. Notwithstanding, this model has not been introduced in Iran so far. Methods: This research was carried out based on an applied descriptive method in three private hospitals of Isfahan—one of the most important provinces of Iran—in the year 2015. The purpose of this study was to investigate IT utilization stage in three selected private hospitals. Conclusion: The findings revealed that HIS is not at the center of concern in studied hospitals and is in the first maturity stage in accordance with EMRAM. However, hospital managers are enforced and under the pressure of different beneficiaries including insurance companies to improve their HIS. Therefore, it could be concluded that these types of hospitals are still far away from desirable conditions and need to enhance their IT utilization stage significantly.

Design of Fine Life Cycle Prediction System for Failure of Medical Equipment

The inquiry process of traditional medical equipment maintenance management is complex,which has a negative impact on the efficiency and accuracy of medical equipment maintenance management and results in a significant amount of wasted time and resources.To properly predict the failure of medical equipment,a method for failure life cycle prediction of medical equipment was developed.The system is divided into four modules:the whole life cycle management module constructs the life cycle data set of medical devices from the three parts of the management in the early stage,the middle stage,and the later stage;the status detection module monitors the main operation data of the medical device components through the normal value of the relevant sensitive data in the whole life cycle management module;and the main function of the fault diagnosis module is based on the normal value of the relevant sensitive data in the whole life cycle management module.The inference machine diagnoses the operation data of the equipment;the fault prediction module constructs a fine prediction system based on the least square support vector machine algorithm and uses the AFS-ABC algorithm to optimize the model to obtain the optimal model with the regularized parameters and width parameters;the optimal model is then used to predict the failure of medical equipment.Comparative experiments are designed to determine whether or not the design system is effective.The results demonstrate that the suggested system accurately predicts the breakdown of ECG diagnostic equipment and incubators and has a high level of support and dependability.The design system has the minimum prediction error and the quickest program execution time compared to the comparison system.Hence,the design system is able to accurately predict the numerous causes and types of medical device failure.

Influence of Surface Topography on the Tactile Friction of Medical Compression Textiles against a Mechanical Skin Model

Influence of surface topography on the tactile friction of medical compression textiles was studied in this paper. The friction behavior was investigated for three kinds of medical textiles with various structures and compositions by using a textile friction analyzer under dry condition. In order to simulate the contacts of textiles/human finger, a mechanical skin model with similar texture to the skin and applied normal load oflN were selected. Meanwhile, the 3D surface topography of textiles was measured using a digital microscope. The topographical data were analyzed concerning height distribution and material ratio, and the real contact area was estimated as a function of penetration depth. Results showed that the investigated textiles revealed a significant variation on the friction coefficients, which were （ 0.41 ± 0.01 ） （ polyamide, jersey 2 × 2 ）, （0.56 ± 0. 01） （cotton, jersey 2×2） and （0. 47 ± 0. 01） （polyamide, jersey 1 × 1 ）, respectively. The textile with higher friction coefficient was found to own a relative compact and homogenous surface and larger contact area, vice versa.

Discussion on Management Model of Medical Equipment Maintenance in Hospital

With the development of technology, medical equipment plays a more important role in the modern hospital. Medical equipment provides images, physiological results or other schematics of the patients to help doctors deal with the routines. It is also the major tool to the lab assistant in the clinical teaching and studies. It becomes one of a symbol of the technological level in modern hospital. The director of the hospital should establish an effi cacious management pattern to manage the medical equipment, so that it will be operated in good condition to insure the safety of the patients. Since the maintenance is an important part of medical equipment management, it is significant that the hospital should establish a system to fit for itself. The study reviews the issues in hospital medical equipment maintenance management, the development of the maintenance management model and the characteristics, as well as the status at home and abroad. The research has been fi nished by using literature research method, questionnaire survey method and data analysis method. Then we analyze the current status of hospital medical equipment maintenance management model to fi nd the problems. Based on the authentic and effective data from the survey, we can deduce the overview about the maintenance model in Beijing. The paper discusses the advantages and the disadvantages between the different model, and it makes suggestions on the follow aspects, such as system management, quality management, personnel management, cost management, information management perspective.

Thermogravimetric characteristics and different kinetic models for medical waste composition containing polyvinyl chloride-transfusion tube

Thermogravimetric study of medical transfusion tube(MTT) waste containing polyvinyl chloride(PVC) was carried out using the thermogravimetric analyser(TGA) with N2, at different heating rates of 5, 10, 20, 30, 50 °C/min. The purpose is to obtain pyrolysis characteristics and kinetic parameters of medical waste. The experimental results indicate that the pyrolysis behavior of the MTT sample is in agreement with its main ingredient of PVC, appearing two stair stepping stages. The influence of the additives in MTT on pyrolysis behavior was also revealed, which could improve MTT pyrolysis at lower temperature in the first stage, and cause obvious unsmoothness and asymmetry of the second DTG peak. Four n-order kinetic models of Coats-Redfern, Ozawa, Kissinger and Freeman-carroll were used to get the kinetic parameters. Furthermore, a novel "two-step four-reaction model" was established to simulate the whole continuous process. The different methods and the kinetic parameters thus obtained were discussed and compared with each other in literatures. The reasons of deviation among kinetic values were tried to be elucidated. The new established model could more satisfactorily describe the pyrolysis process of MTT, being more mechanistic and conveniently serving for the engineering.

Study on Dynamic Model of Initial Emission Rights for Medical Sewage System

The chemical oxygen demand (COD) is selected as the index in this paper. The system dynamics method is used to analyze the emission right price of medical sewage, the boundary of the emission right price system is determined, and the system dynamics model of the initial emission right of medical sewage is constructed, in which the system is divided into water resources subsystem, population subsystem, economic subsystem and social subsystem. It is expected to expand the theory of the system modeling of the initial discharge right of medical sewage, and to provide the basis for the relevant decision of the environmental management authorities.

Influence of Medical Model on Therapeutic Environment

In its development history, man has always tried to be close to nature, and get physical and spiritual help from the nature. According to the development of medical model from the deity worship to modern medical science, a near-nature and ecological therapeutic and recuperative model has been more favored, thus in modern therapeutic environment, proper landscape designs can be combined with effective medical methods to achieve physical and mental immunoregulation and balance using natural and quality climatic factors. This paper introduced the development of natural science and medicinal model in different periods, and analyzed their impact on environment, concluded the benefi ts of therapeutic medicine, and demonstrated the signifi cance of therapeutic environment and landscape healing as the therapeutic factors for facilitating human rehabilitation from the perspective of therapeutic medicine. Taking "evidence-based design" as the basis of therapeutic environment design, this paper proposed landscape design methods for the therapeutic environment, in order to provide people opportunities for closing to, sharing and participating in the nature, help people to relax physically and psychologically using the positive impact of natural environment on human spirits, relieve their stress, and achieve physical and psychological peace. In addition, the development tendency of therapeutic environment in China was predicted according to the actual conditions of urban society.

Medical Treatment Process Modeling Based on Process Mining and Treatment Patterns

activities.Ex-periments on a synthetic log of the non-secondary hy-pertension MTP and empirical findings demonstrate the effectiveness of our approach.The results show that the process mining in our approach framework can automatically generate more accurate MTP mod-els,and the subprocess models based on treatment pat-terns make the models easy to understand.

Modeling and Simulation of a Renewable Energy Based-Medical Herb Dryer

The medical herbs should be dried directly after harvesting, otherwise, insects and fungi spoilage them. Conventional drying methods such as open sun drying and conventional fuel dryers are not suitable, since they contaminate the herbs, decrease the drying efficiency and at the same time increase the drying cost. Therefore, the recent trend is toward the harnessing the renewable energy to dry the medical herbs. This paper presents a new controlled drying system, which uses a solar collector and an electric heater to heat the drying air, and a PV-WIND hybrid system to supply the required electric energy to the dryer electric load. This paper also presents the dynamic modeling, simulation, and control of the suggested thermal system (i.e., the solar thermal system and the electrical heater). Moreover, this paper, exhibits the different results of the thermal system, to check the effectiveness of this system that fulfills the requirements of the drying operation. The system results are found to satisfy the ultimate goals of the drying operation.

Investigation on depression of medical students based on health belief model

Objective:Based on the health belief model,the depression status of medical students was analyzed in order to provide new ideas for the intervention of mental health problems of medical students.Methods:By using the method of stratified cluster sampling,1053 medical students in a medical college in Hainan province were investigated with self-designed general situation questionnaire,SCL-90,CSQ and emotional management health belief questionnaire.Results:The positive rate of depressive symptoms in medical students was 17.5%.Multivariate unconditional Logistic regression analysis showed that gender,coping style,"perceived obstacles","perceived severity","perceived susceptibility"and"self-efficacy"were related factors of depression in medical studengts.Conclusion:The related factors of depression in medical students include personal factors and the health belief factors such as"perceived obstacles","perceived severity","perceived susceptibility"and"self-efficacy".Psychological intervention based on Health belief model can be used for intervention of medical students.