Exploration and Practice of Postgraduate Training Mode Based on Medical Imaging Information Security

In the process of continuous maturity and development of medical imaging diagnosis,it is common to transmit images through public networks.How to ensure the security of transmission,cultivate talents who combine medical imaging and information security,and explore and cultivate new discipline growth points are difficult problems and challenges for schools and educators.In order to cope with industrial changes,a new round of scientific and technological revolution,and the challenges of the further development of artificial intelligence in medicine,this article will analyze the existing problems in the training of postgraduates in medical imaging information security by combining the actual conditions and characteristics of universities,and put forward countermeasures and suggestions to promote the progress of technology in universities.

A method based on mutual information and gradient information for medical image registration

Mutual information is widely used in medical image registration, because it does not require preprocessing the image. However, the local maximum problem in the registration is insurmountable. We combine mutual information and gradient information to solve this problem and apply it to the non-rigid deformation image registration. To improve the accuracy, we provide some implemental issues, for example, the Powell searching algorithm, gray interpolation and consideration of outlier points. The experimental results show the accuracy of the method and the feasibility in non-rigid medical image registration.

Coping up with the Information Overload in the Medical Profession

The recent technological advancement has proved to be tremendously helpful for medical consultants. However, this advancement has also generated an enormous volume and variety of data, with a high velocity causing an information load for the medical consultants. Information overload can be defined as a difficulty a person can have in comprehending issue and making judgments that are caused by the presence of too much information. Information overload occurs when the amount of input to a system surpasses its processing capability. Decision-makers have a limited cognitive processing ability. Consequently, when information overload happens, it is possible that a decline in decision quality will take place. Decision-makers, such as medical consultants, have fairly limited cognitive processing capacity. Consequently, when information overload occurs, it is likely that a reduction in decision quality will occur. The aim of this study is to assess the impact of information overload on medical consultants’ life, its causes, and potential ways to deal with it. We performed a literature review to find the effects of information overload on medical consultants. Twelve research papers were considered for thematic analysis using NVivo 10 tool. These papers revealed four themes: 1) traditional methods of data collection;2) modern ways of data collection;3) consequences of modern ways of data collection;and 4) the need for handling information overload. This study suggests the development of a Continuing Professional Development course that explains how to deal with information overload, and availing the same through E-Learning mode might be one immediate solution.

Design of an Information Security Service for Medical Artificial Intelligence

The medical convergence industry has gradually adopted ICT devices,which has led to legacy security problems related to ICT devices.However,it has been difficult to solve these problems due to data resource issues.Such problems can cause a lack of reliability in medical artificial intelligence services that utilize medical information.Therefore,to provide reliable services focused on security internalization,it is necessary to establish a medical convergence environment-oriented security management system.This study proposes the use of system identification and countermeasures to secure systemreliabilitywhen using medical convergence environment information in medical artificial intelligence.We checked the life cycle of medical information and the flow and location of information,analyzed the security threats that may arise during the life cycle,and proposed technical countermeasures to overcome such threats.We verified the proposed countermeasures through a survey of experts.Security requirements were defined based on the information life cycle in the medical convergence environment.We also designed technical countermeasures for use in the security management systems of hospitals of diverse sizes.

Proposal of ZigBee Systems for the Provision of Location Information and Transmission of Sensor Data in Medical Welfare

This paper proposes a scheme to obtain location and vital health information using ZigBee system. ZigBee systems are wireless communication systems defined by IEEE 802.154. In the proposed scheme, location information is obtained using the Link Quality Indication (LQI) function of a ZigBee system, which represents the received signal strength. And, the vital health information are collected from the electrocardiogram monitor, the pulse and blood pressure device, attached to the patient’s body. This information is then transmitted to an outside network by ZigBee systems. In this way, vital health information can be transmitted as ZigBee sensor data while patients with the ZigBee terminal are moving. In the experiments using actual ZigBee devices, the proposed scheme could obtain accurate location and vital health information from the sensor data. Moreover, to achieve high reliability in the actual service, the collected amount of sensor data was confirmed by the theoretic calculation, when a ZigBee terminal passed through ZigBee routers. These results indicate that the proposed scheme can be used to detect the accurate location of the ZigBee terminal. And over 99% of the sensor data on vital health information was obtained when the ZigBee terminal passed through approximately four ZigBee routers.

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.

Smart Dynamic Resource Allocation Model for Patient-Driven Mobile Medical Information System Using C4.5 Algorithm

A mobile medical information system (MMIS) is an integrated application (app) of traditional hospital information systems (HIS) which comprise a picture archiving and communications system (PACS), laboratory information system (LIS), pharmaceutical management information system (PMIS), radiology information system (RIS), and nursing information system (NIS). A dynamic resource allocation table is critical for optimizing the performance to the mobile system, including the doctors, nurses, or other relevant health workers. We have designed a smart dynamic resource allocation model by using the C4.5 algorithm and cumulative distribution for optimizing the weight of resource allocated for the five major attributes in a cooperation communications system. Weka is used in this study. The class of concept is the performance of the app, optimal or suboptimal. Three generations of optimization of the weight in accordance with the optimizing rate are shown.

TOWARDS AN ONTOLOGY-BASED MULTI-AGENT MEDICAL INFORMATION SYSTEM BASED ON THE WEB

This paper described an ontology based multi agent knowledge process made (MAKM) which is one of multi agents systems (MAS) and uses semantic network to describe agents to help to locate relative agents distributed in the workgroup. In MAKM, an agent is the entity to implement the distributed task processing and to access the information or knowledge. Knowledge query manipulation language (KQML) is adapted to realize the communication among agents. So using the MAKM mode, different knowledge and information on the medical domain could be organized and utilized efficiently when a collaborative task is implemented on the web.

Using mutual information to evaluate performance of medical imaging systems

Information on physical image quality of medical images is important for imaging system assessment in order to promote and stimulate the development of state-of-the-art imaging systems. In this paper, we present a method for evaluating physical performance of medical imaging systems. In this method, mutual information (MI) which is a concept from information theory was used to measure combined properties of image noise and resolution of an imaging system. In our study, the MI was used as a measure to express the amount of information that an output image contains about an input object. The more the MI value provides, the better the image quality is. To validate the proposed method, computer simulations were per- formed to investigate the effects of noise and resolution degradation on the MI, followed by measuring and comparing the performance of two imaging systems. Our simulation and experimental results confirmed that the combined effect of deteriorated blur and noise on the images can be measured and analyzed using the MI metric. The results demonstrate the potential usefulness of the proposed method for evaluating physical quality of medical imaging systems.

Path Selection of China’s Medical Reform Based on Empirical Measurement of Asymmetric Information

Based on the micro individual data from China Health and Nutrition Survey (CHNS) database and the development of China’s medical and health system reform since the reform and opening-up in 1978, this paper applies a two-tier stochastic frontier model to measure the degree of asymmetric information between physicians and patients in China’s medical service market and estimate the impact of bargaining on the final price of health care both holistically and annually. The empirical results show that: 1) The information mastered by physicians and patients have significant but opposing effects on the final medical service price. Physicians hold more information relative to patients and thus have stronger bargaining power. 2) Almost all patients will be forced to accept a medical price higher than the benchmark price by 16.52% on average by receiving excessive and expensive medical services, despite the differences in bargaining power between physicians and patients are highly heterogeneous. 3) The series of medical reforms in China had different impacts on medical care pricing efficiency. Especially, the early medical reforms could impose a positive impact on the efficiency of the medical market in the initial stage. I further propose that the path choice of China’s new round of medical reform should be as follows: It is necessary to insist on government-led efforts to protect the public welfare of medical services, and to introduce market mechanisms to mobilize social resources and improve the efficiency of the medical market. In addition, I point out that the establishment and improvement of the general practitioner system may reduce the degree of information asymmetry between physicians and patients, thus alleviating China's deteriorating physician-patient relationship.

ExpressionHash: Securing Telecare Medical Information Systems Using BioHashing

The COVID-19 outbreak and its medical distancing phenomenon have effectively turned the global healthcare challenge into an opportunity for Telecare Medical Information Systems.Such systems employ the latest mobile and digital technologies and provide several advantages like minimal physical contact between patient and healthcare provider,easy mobility,easy access,consistent patient engagement,and cost-effectiveness.Any leakage or unauthorized access to users’medical data can have serious consequences for any medical information system.The majority of such systems thus rely on biometrics for authenticated access but biometric systems are also prone to a variety of attacks like spoong,replay,Masquerade,and stealing of stored templates.In this article,we propose a new cancelable biometric approach which has tentatively been named as“Expression Hash”for Telecare Medical Information Systems.The idea is to hash the expression templates with a set of pseudo-random keys which would provide a unique code(expression hash).This code can then be serving as a template for verication.Different expressions would result in different sets of expression hash codes,which could be used in different applications and for different roles of each individual.The templates are stored on the server-side and the processing is also performed on the server-side.The proposed technique is a multi-factor authentication system and provides advantages like enhanced privacy and security without the need for multiple biometric devices.In the case of compromise,the existing code can be revoked and can be directly replaced by a new set of expression hash code.The well-known JAFFE(The Japanese Female Facial Expression)dataset has been for empirical testing and the results advocate for the efcacy of the proposed approach.

How reliable is online diffusion of medical information targeting patients and families?

AIM: To determine whether online diffusion of the "Ten Warning Signs of Primary Immunodeficiency Diseases(PID)'' adheres to accepted scientific standards.METHODS: We analyzed how reproducible is online diffusion of a unique instrument, the "Ten Warning Signs of PID", created by the Jeffrey Modell Foundation(JMF),by Google-assisted searches among highly visited sites from professional, academic and scientific organizations;governmental agencies; and patient support/advocacy organizations. We examined the diffusion, consistency of use and adequate referencing of this instrument.Where applicable, variant versions of the instrument were examined for changes in factual content that would have practical impact on physicians or on patients and their families.RESULTS: Among the first 100 sites identified by Google search, 85 faithfully reproduced the JMF model, and correctly referenced to its source. By contrast, the other15 also referenced the JMF source but presented one or more changes in content relative to their purported model and therefore represent uncontrolled variants, of unknown origin. Discrepancies identified in the latter included changes in factual content of the original JMF list(C), as well as removal(R) and introduction(I) of novel signs(Table 2), all made without reference to any scientific publications that might account for the drastic changes in factual content. Factual changes include changes inthe number of infectious episodes considered necessary to raise suspicion of PID, as well as the inclusion of various medical conditions not mentioned in the original.Together, these changes will affect the way physicians use the instrument to consult or to inform patients,and the way patients and families think about the need for specialist consultation in view of a possible PID diagnosis.CONCLUSION: The retrieved adaptations and variants,which significantly depart from the original instrument,raise concerns about standards for scientific information provided online to physicians, patients and families.

Medical Information Breaches Occurrence with Respect to Social Media Usage, in Selected Medical Institutions in Uganda

The purpose of this manuscript is to present research findings based on the reported cases of medical information breaches due to Social Media (SM) usage, in selected medical institutions in Uganda. The study employed online survey techniques. Altogether, 710 questionnaires (Google forms) were developed, and operationalized. The main respondents included 566 medical students, and 143 medical staff from Mbarara University of Science and Technology (MUST), and Kampala International University (KIU), accordingly. Using SPSS, the main statistical analysis tools employed include frequency distribution summary, and Chi-square (x2) test. According to the frequency distribution summary, 27% to 42% of the respondents within categorical divides acknowledged occurrence of medical information breaches due to SM usage. Notably, higher levels of the breaches were reported among male students (64%), age-group 18 to 35 years (68%), and WhatsApp users (63%). On the other hand, Chi-square results showed significant levels (p p > 0.05) between medical institutions and medical information breaches. Overall, the vulnerable areas of the breaches identified would serve as important reference points in the process of rationalizing SM usage in medical institutions. Nevertheless, further studies could focus on identification of the key SM usage factors associated with medical information breaches in medical institutions in Uganda.

Development of IT Triage System （TRACY） to Share Regional Disaster Medical Information

We developed an IT （Information Technology） triage system for collecting disaster medical information in real time. FeliCa cards and card readers are used to obtain the number and condition of patients. The system is composed of two elements. First, the number of patients for each triage level and the accepted number of patients in each diagnosis and treatment department are obtained in real time, including response for changing triage level. Second, this information is shared in real time among hospitals, the admim＇stration, and residents who are searching for their family. A disaster drill utilizing this system was held at the University of Yamanashi Hospital with 450 participants. From the result of that, the present system could work for those two elements. TRACY was examined its availability and practicability in this drill.

A Culturally-Sensitive Model for CME Distance Learning Demonstratesa Way Forward： Kenya＇s Experience with ACME-IT （Advancing Continuing Medical Education Through Information Technology）

A distance learning Continuing Medical Education （CME） project based on live interactive presentations and a group participatory model demonstrated that important strides can be made in the quality of CME available to health care professionals in African rural settings. Implementers choose a communication model consistent with the fundamental orality of Kenyan and other sub-Saharan African countries. The project involved four hospitals and one training institution in rural Kenya. The testing of learners and focus group discussions with learners, facilitators and presenters indicated that the project＇s methodologies, that strove to be culturally and work place friendly, contributed to gains in knowledge, competencies including case management, the continuity of patient care, team work, staff morale and other issues of expressed importance to the hospital healthcare work force and hospital administrators. The learning system, known as Advancing Continuing Medical Education through Information Technology （ACME-IT）, was implemented by the Kenyan Ministry of Medical Services, EC Associates and the US-funded Aphia2 Western initiative implemented by PATH. The findings of this pilot suggests that the ACME-IT methodology that set up learning centers at the participating institutions is a promising viable alternative to the traditional and relatively expensive workshop training that characterizes much of CME in lower and middle income countries.

Study on Clinical Thinking of Traditional Chinese Medicine Based on Wang Yongyan＇s MedicalRecord Information System

Medical record information system engineering technology is used to set professor Wang Yongyan5s medical record as the master system, and model the disease, syndrome, treatment and prescription. According to the experience of doctors, we will combine them according to the procedure of ＂problem-solution＂, to study Professor Wang＇s treatment experience and his clinical thinking.

Application of Big Data Information Platform in Medical Equipment

The application of big data in the medical device industry mainly refers to the analysis and processing of various medical devices,so as to provide patients with better treatment and rehabilitation services.At present,our country already has a relatively mature and reliable large database system.This article studies the application of medical equipment in the big data information platform.The main methods used in this article are survey method,case analysis method,and interview method.The big data information platform and medical devices are studied from different aspects.The survey results show that 41%of people completely agree with the role of big data information platforms in medical devices.

Fast Mutual Information Registration Method of 3-D Medical Image

Currently the voxel based registration methods have been used widely such as the well known mutual information (MI). Although the accuracy of their results is plausible, the registration procedure is slow. This paper proposed some methods to rigid registration based on mutual information, aiming for an acceleration of the registration process without significantly loss of precision in the final results. The efficiency of these methods is examined by registration of CT MR and PET MR. Experimental results show that the speedup is effective and efficient. By using the fast methods, the registration of 3 D medical image could also be implemented on PC rapidly.

LGNet:Local and global representation learning for fast biomedical image segmentation

Medical image segmentation plays a crucial role in clinical diagnosis and therapy systems,yet still faces many challenges.Building on convolutional neural networks(CNNs),medical image segmentation has achieved tremendous progress.However,owing to the locality of convolution operations,CNNs have the inherent limitation in learning global context.To address the limitation in building global context relationship from CNNs,we propose LGNet,a semantic segmentation network aiming to learn local and global features for fast and accurate medical image segmentation in this paper.Specifically,we employ a two-branch architecture consisting of convolution layers in one branch to learn local features and transformer layers in the other branch to learn global features.LGNet has two key insights:(1)We bridge two-branch to learn local and global features in an interactive way;(2)we present a novel multi-feature fusion model(MSFFM)to leverage the global contexture information from transformer and the local representational features from convolutions.Our method achieves state-of-the-art trade-off in terms of accuracy and efficiency on several medical image segmentation benchmarks including Synapse,ACDC and MOST.Specifically,LGNet achieves the state-of-the-art performance with Dice's indexes of 80.15%on Synapse,of 91.70%on ACDC,and of 95.56%on MOST.Meanwhile,the inference speed attains at 172 frames per second with 224-224 input resolution.The extensive experiments demonstrate the effectiveness of the proposed LGNet for fast and accurate for medical image segmentation.

A Knowledge-enhanced Two-stage Generative Framework for Medical Dialogue Information Extraction

This paper focuses on term-status pair extraction from medical dialogues(MD-TSPE),which is essential in diagnosis dia-logue systems and the automatic scribe of electronic medical records(EMRs).In the past few years,works on MD-TSPE have attracted increasing research attention,especially after the remarkable progress made by generative methods.However,these generative methods output a whole sequence consisting of term-status pairs in one stage and ignore integrating prior knowledge,which demands a deeper un-derstanding to model the relationship between terms and infer the status of each term.This paper presents a knowledge-enhanced two-stage generative framework(KTGF)to address the above challenges.Using task-specific prompts,we employ a single model to com-plete the MD-TSPE through two phases in a unified generative form:We generate all terms the first and then generate the status of each generated term.In this way,the relationship between terms can be learned more effectively from the sequence containing only terms in the first phase,and our designed knowledge-enhanced prompt in the second phase can leverage the category and status candidates of the generated term for status generation.Furthermore,our proposed special status"not mentioned"makes more terms available and en-riches the training data in the second phase,which is critical in the low-resource setting.The experiments on the Chunyu and CMDD datasets show that the proposed method achieves superior results compared to the state-of-the-art models in the full training and low-re-sourcesettings.