Areas Of Medical Care Research Articles

M-Net based Stacked Autoencoder for Ransomware Detection using Blockchain Data

Ransomware is a kind of malevolent program software that encrypts the items on the hard disc and prevents the clients from accessing them until they are paid a ransom. Associations like monetary establishments and medical care areas (i.e., smart medical care) are mostly targeted by ransomware attacks. Ransomware assaults are crucial holes still in blockchain technology and prevent effective data communication in networks. This study aims to introduce an efficient system, named M-Net-based Stacked Autoencoder (M-Net_SA) for ransomware detection using blockchain data. Initially, the input data is taken from a dataset and then sent to the feature extraction process, which utilizes sequence-based statistical features. After that, data transformation is completed using the Yeo-Johnson transformation to transform the data into a usable format. After that, feature fusion is executed using a Deep Q-network (DQN) with Lorentzian similarity to enhance the representativeness of the target features. Finally, ransomware detection is accomplished by the proposed M-Net_SA, which is the integration of MobileNet and Deep Stacked Autoencoder (DSAE). The experimental validation of the proposed M-Net_SA is compared with other conventional techniques and the proposed model attained maximum accuracy, sensitivity, and specificity of 0.959, 0.967, and 0.957 respectively.

THE TECHNIQUES OF ESTABLISHING RAPPORT BETWEEN HEALTHCARE PROFESSIONALS AND PATIENTS IN THE MATERNITY AMBULANCE

The study presents communication techniques used in a specific area of medical care, namely in obstetric care. Adequate communication is crucial in the relationship between the midwife and the expectant mother, as it facilitates optimal information flow, understanding, and the development of mutual trust between the parties. By applying effective communication techniques, the midwife can clearly and comprehensibly convey information, respond to questions, and emotionally support the laboring woman. This, in turn, can help the expectant mother understand the process of labor and make informed decisions. Empathy and attention towards the expectant mother can also be expressed through communication. Research on the communication between midwives and expectant mothers (Rijnders et al. 2008; Rowe et al. 2002) has found that the quality of communication with healthcare professionals significantly influences patients’ satisfaction (Dahlberg et al. 2016). In my research, after analyzing transcripts of recorded audio from the maternity ambulance, I summarize the communication techniques employed by midwives in establishing a connection with expectant mothers. Understanding the communication techniques used by midwives can help improve communication between the parties and make the support of expectant mothers more effective.

Spatiotemporal analysis of the association between Kawasaki disease incidence and PM2.5 exposure: a nationwide database study in Japan

BackgroundKawasaki disease (KD) is an acute vasculitis primarily affecting children. While some studies suggest a link between KD and PM2.5 exposure, findings remain inconsistent. This study aimed to perform spatiotemporal...

The History and the Structure of Hospices in Uzbekistan

In the modern world, there is a constant increase in the number of patients suffering from incurable forms of diseases in the terminal stage of development. This trend actualizes the study of palliative care, which is a special area of social and medical care for terminally ill people. Palliative care is an integrated part of cancer patient care. However, the situation in palliative care in Uzbekistan is very critical. Implementing palliative care and hospice into medicine began in 2017 in Tashkent, Uzbekistan. The first Children’s Hospice -Taskin was opened in 2022 in Tashkent, Uzbekistan. Despite the fact that 2 years have passed since the opening of the hospice in the Republic of Uzbekistan, the concept of hospice has not yet formed in the minds of the population, there is still an idea that people perceive the concept of “hospice” as a house of death. This article is intended to study the history and structure of palliative care in Uzbekistan and study the perception of hospice among the population.

Climate change from the Asia-Pacific perspective: What an allergist needs to know and do.

Allergic diseases such as asthma, atopic dermatitis, and food allergies are a burgeoning health challenge in the Asia-Pacific region. Compounding this, the region has become increasingly susceptible to the impacts of climate change. The region has weathered extreme precipitation, intense heat waves, and dust storms over the recent decades. While the effects of environmental and genetic factors on allergic diseases are well understood, prevailing gaps in understanding the complex interactions between climate change and these factors remain. We aim to provide insights into the various pathways by which climate change influences allergic diseases in the Asia-Pacific population. We outline practical steps that allergists can take to reduce the carbon footprint of their practice on both a systemic and patient-specific level. We recommend that allergists optimize disease control to reduce the resources required for each patient's care, which contributes to reducing greenhouse gas emissions. We encourage the responsible prescription of metered dose inhalers by promoting the switch to dry powder inhalers for certain patients, at each clinician's discretion. We also recommend the utilization of virtual consultations to reduce patient travel while ensuring that evidence-based guidelines for rational allergy management are closely adhered to. Finally, eliminating unnecessary testing and medications will also reduce greenhouse gas emissions in many areas of medical care.

Racial disparities with PRN medication usage in inpatient psychiatric treatment

Racial disparities in psychiatric diagnoses and treatment have significant public health implications, contributing to inequities in healthcare outcomes. We specifically examined racial disparities regarding pro re nata (PRN), or as needed, medications. Data from 14,616 encounters across 2019–2020 within Community Health Network’s inpatient psychiatric setting in Indianapolis, Indiana were included in this study. Due to the demographic sample size, analyses were narrowed to Black and White patients. Primary outcomes included comparisons across race for all PRN administrations and PRN administrations of antipsychotics vs. non-antipsychotics. Logistic regression was used to examine associations between race and PRN administrations by medication category, including all antipsychotics vs. non-antipsychotics overall, hydroxyzine, and lorazepam, independently. Significant differences in the percentage of administrations between Black and White patients were observed. Black patients received more PRN medications overall (71.0%) compared to White patients (67.7%) (p < 0.01). Further, while 17.7% of Black patients were administered PRN antipsychotics, this was true for only 8.2% of White patients (p < 0.001). When comparing antipsychotic PRNs with non-antipsychotic, hydroxyzine, and lorazepam PRNs, independently, Black patients were 58% (OR 1.58, p < 0.001), 109% (OR 2.09, p < 0.001), and 32% (OR 1.32, p < 0.001), more likely to receive antipsychotic PRNs, respectively, than White patients, controlling for sex, age, length of stay, and psychotic disorder diagnosis. Our study identifies yet another area of medical care with significant racial disparities. In this analysis of PRN medications during psychiatric admission, we identified significant differences in medication utilization by race. This information provides a basis for further investigation of disparities in patient-centered data.

Key Indicators for Monitoring the Efficiency of Iranian Health System: A Synthesized Design Study.

A significant share of medical care, primary health care, and health-related education and research in Iran is provided by the Ministry of Health and its affiliated universities of medical sciences. We aimed to identify a set of key metrics for monitoring their efficiency in the four areas of medical care, primary health care, education and research. A combination of scoping review, expert panel and Delphi method was used. First, the relevant keywords were searched in the appropriate databases between 2000 and 2020. The final extracted indicators then reviewed, reduced and refined through the expert panel meetings. The last metrics were established following a three-stage Delphi study. Out of 2327 studies, 155 were selected following the different screening stages of scoping review. After summarizing and refining the indicators via several expert panel meetings and the Delphi method, a total of 36 key indicators were considered appropriate for measuring efficiency of the health system, 23 of which were for the sub-systems of public health (4 indicators), medical services (10 indicators), education (4 indicators) and research (5 indicators) and 13 indicators for the whole system efficiency. The set of indicators presented representing both the technical and allocative efficiency, might be a reliable basis for designing information systems and management dashboards for periodic monitoring of health system efficiency at national, regional and local levels.

Risk Assess: A Symptom-Based Disease Predictor

Abstract: As of late, the medical care area has seen extraordinary changes through the joining of state of data collection. This study presents "Risk Assess", an imaginative web application fastidiously created with Flask. “Risk Assess” fills in as a complete stage, working with patient vitals for generating risk assessments. This python-based web application uses different Machine Learning models such as Classification and Regression (CART), Linear Support Vector Machine (SVM), Gaussian Naïve Bayes (NB), K-Nearest Neighbor (KNN) to analyze and build a model to predict if the given set of symptoms leads to a particular disease. Outstandingly, “Risk Assess” soothes out Cancer, Diabetes, Heart –Disease, Kidney-Disease and LiverDisease based prediction upgrading comfort and functional productivity. Our undertaking highlights a solid login page empowering clients to make novel qualifications utilizing their email addresses. By requiring a username and secret key attached to their email, we focus on both security and client comfort. This research paper contains working engineering, plan standards, and execution complexities, featuring the pivotal job of Machine Learning. “Risk Assess” epitomizes utilization of Python-based advances and Machine Learning, exhibiting the potential for predictions based on symptoms through creative computerized arrangements

Cyber Security Challenges and Effective Security Measures for IOT-based Intelligent Healthcare Systems

Aims and Background: In order to keep up with the rapid development of technology, cities must enhance their offerings in the areas of public security, medical care, transportation, and citizen well-being. Healthcare systems rely heavily on patient care. Patients' life and the services offered by doctors, nurses, clinicians, pharmaceutical companies, and governments stand to benefit from the implementation of Healthcare IoT. There has been a change in the medical industry, marked by the widespread adoption of wireless healthcare-monitoring-systems (HMS) in hospitals. Objectives and Methodology: However, the Internet-of-Things(IoT) concept frequently ignores security-privacy for linked things. Security and privacy protections must be implemented systematically throughout the entire healthcare and remote health monitoring system, from the creation of equipment to their interconnection, communication, storage, and eventual destruction. This research investigates the risks associated with using smart health devices and provides recommendations for addressing those risks. The present security and privacy of IoT devices in healthcare systems, as well as the difficulties in adopting security frameworks, are discussed, and recommendations for addressing these issues are offered. Results and Conclusions: This study also contributes in two ways to the ongoing effort to investigate security-privacy concerns in the circumstance of smart cities for healthcare purposes. Moreover, this article provides a summary of the many Internet of Things applications and the cyber threats they face. On the other hand, thorough assessments of methods to reduce cyber threats to 60% are presented.

CALCULATION OF THE NATIONAL NEED FOR PALLIATIVE CARE BY THE REFINED METHOD OF TRENDS IN THE CONDITIONS OF A MILITARY CRISIS

Introduction. Palliative and Hospice Care (PHC) in Ukraine is necessary for 300,000 patients (adults and children) whose lives are coming to an end due to incurable diseases. Ukraine is improving this area of medical care due to changes in funding. The issue of reliably predicting the need for PHC in adults and children remains unresolved. The aim. Check the forecast of the need for palliative and hospice care for 2021 and 2022, made according to the methodology of the Ukrainian Center for Public Data (2019), and determine the optimal method of refined trend forecasting to increase reliability in the conditions of a military crisis. Materials and methods. The forecasting was carried out using Microsoft Excel, the method of a creeping trend with a constant segment of smoothing, with a detail that allows you to determine the reliability of the forecast at the expense of a 95% confidence interval. The updated forecast takes into account migration processes in Ukraine during the war, including the impossibility of collecting medical statistics data in the temporarily occupied territories. Results. The calculation of the need for PHC for adults and children in 2021 and years has been carried out based on the available statistical data of the State Statistics Service of Ukraine, Medical Statistic Service of Ukraine, national cancer and tuberculosis registries. Significant discrepancies were found between the calculated result and the forecast made before the war. The results of the forecast made in 2021 regarding the need for PHC of adults and children of Ukraine for 2021 and 2022 by the linear trend method are also compared with the results of the forecast by the creeping trend method with a constant smoothing segment. The latter was 4.70 times more accurate for adult palliative patients, and 1.25 times more accurate among palliative patients of all age categories. Conclusions. The tendency to decrease the need for PHC among both adults and children from the period 2018–2022 is maintained, which is associated with a decrease in the quality of data collection of medical statistics, and during the military crisis, also with significant migration processes and occupation of territories. Forecasting is necessary for further planning and financing of PHC and should be carried out on an ongoing basis. Methods for assessing the need for PHC need further improvement.

Deep Learning Technique Based State-Of-The-Art in Skin Cancer Detection: A Review

Research of skin cancer images through visual survey and manual evaluation to investigate skin threatening development has always been abnormal. This manual evaluation of skin injuries to recognize melanoma is monotonous as well as somewhat long. With movement in advancement and fast development in computational resources, different AI techniques and significant learning methods have emerged for assessment of clinical pictures most especially the skin lesion images. In late years, AI arising as an innovation equipped for tackling issues connected with horticulture, medical services, business, and soon. To diminish the endanger to human existence we can embrace AI calculations in the medical care area and can foresee the deadliest skin illnesses like dangerous melanoma in beginning phases. The point of the research is to give bits of knowledge about various classifications of skin lesions and strategies executed to arrange and foresee skin diseases and the job of dermatologists while fostering the models, at last gives a general rundown of existing work.

스마트도시의 안전성 향상을 위한 스마트기술 적용방안에 관한 연구

In order to propose ways to apply smart technology to improve the safety of smart cities, this study aims to propose smart technologies that are highly related to safety management in the areas of transportation, medical care, environment, nature, and crime prevention in smart cities, such as AR, BIM, big data, and cloud. , IoT, VR, robot automation, drones, and 3D printing were analyzed. For the study, the applicability of smart technology in each field was investigated by safety management experts using a matrix evaluation method, and the results can be summarized as follows. In the transportation field, big data technology for collecting and processing traffic information through GPS, GIS and smart phone apps, drone technology that monitors real-time traffic information and utilizes sensors such as vehicles, roads and signal devices, and various collected information The safety of smart cities can be secured by applying IoT technology that builds prediction models based on traffic patterns. In the medical field, robot automation technology that sets up predictive models for telemedicine, health management, drug processing and infectious diseases, drone technology that utilizes the movement of patients and medical staff, attachment of monitoring devices, and securing public health response data, etc. It is predicted that it will be possible to secure the safety of smart cities through 3D printing technology that can manufacture medical instruments, auxiliary devices, and various artificial bodies, as well as various medical models and educational tools. In the environmental field, drone technology enables real-time monitoring of water quality, air, and various environmental factors, robotic automation technology that uses robots in places to collect environmental data within the city, and environmental infrastructure that installs and collects buildings, vehicles, and various infrastructure facilities. IoT technology can be applied to improve the safety of smart cities. In the natural field, drone technology is capable of collecting and utilizing various data by attaching video, thermal images, LiDAR scans, radars and sensors, and integrated management linked to a central system focused on the installation of houses, buildings and various infrastructure facilities and environmental changes. The safety of smart cities can be improved by utilizing possible IoT technology, BIM technology that can establish response plans for storm and flood damage, cold waves, heatstroke, and earthquakes through 3D models, and big data technology that collects, integrates, and builds platforms for safety-related data. It can be promoted. In the crime prevention field, drone technology that can detect the occurrence of abnormal signals such as sound, heat, and optical sensors and link with the local police station, IoT technology that can collect and analyze voice recognition technology, and AI that strengthens facial and vehicle recognition in intelligent CCTV. The safety of smart cities can be secured through robot automation technology that combines the deployment of basic robots and collaboration with drones and IoT technologies.

Overview of Artificial Intelligence in Health Care System

Artificial Intelligence (AI) is Computers perform tasks that are usually assumed to require human intelligence, is currently being discussed in nearly every domain of science and engineering[1]. Major scientific competitions like ImageNet Large Scale Visual Recognition Challenges are providing evidence that computers can achieve human-like competence in image recognition [1]. All of these developments raise questions regarding how these talents might assist or perhaps improve human decision-making in the areas of health and medical care. At least in very specific cases, two recent high-profile academic articles have shown that AI can conduct clinical diagnoses on medical images at levels equal to experienced physicians[1].

Structure and establishment of the German Cochlear Implant Registry (DCIR).

Hearing rehabilitation of patients with severe hearing loss or deafness using cochlear implants (CI) is avery successful but also complex and lifelong process that requires high quality standards for structure, process, and results. Medical registries represent an ideal tool for conducting quality control relevant to care while at the same time collecting scientific data. Therefore, at the initiative of the Executive Committee of the German Society of Oto-Rhino-Laryngology, Head and Neck Surgery (DGHNO-KHC), aGermany-wide CI registry (the German Cochlear Implant Register, DCIR) was to be established. The following goals were to be achieved: 1)legal and contractual basis for the register; 2)definition of the register contents; 3)development of evaluation standards (hospital-specific and national annual reports); 4)development of alogo; 5)practical operation of the registry. After defining acatalog of services that defines the content, structure, and operation of the DCIR, aregistry operator with audiological expertise was sought. After considering various offers, the registry was technically implemented in cooperation with the provider INNOFORCE (Ruggell, Liechtenstein) as registry operator. This also included the realization of an interface for data transfer from previously existing databases and development of adata protection concept for productive operation of the DCIR under the scientific leadership of the DGHNO-KHC Executive Committee. Since January 2022, it has been possible for participating hospitals to enter pseudonymized data into the DCIR. To date, 75hospitals in Germany have contractually agreed to participate in the registry. During the first 15months, data from over 2500implants in over 2000patients were registered in the DCIR. The work presented here describes the structuring, development, and successful establishment of the DCIR. Introduction of the DCIR represents an important milestone of future scientifically based quality control in CI care. The registry presented here can therefore be considered as an example for other areas of medical care and thus also sets an international standard.

Prehospital stroke-scale machine-learning model predicts the need for surgical intervention

While the development of prehospital diagnosis scales has been reported in various regions, we have also developed a scale to predict stroke type using machine learning. In the present study, we aimed to assess for the first time a scale that predicts the need for surgical intervention across stroke types, including subarachnoid haemorrhage and intracerebral haemorrhage. A multicentre retrospective study was conducted within a secondary medical care area. Twenty-three items, including vitals and neurological symptoms, were analysed in adult patients suspected of having a stroke by paramedics. The primary outcome was a binary classification model for predicting surgical intervention based on eXtreme Gradient Boosting (XGBoost). Of the 1143 patients enrolled, 765 (70%) were used as the training cohort, and 378 (30%) were used as the test cohort. The XGBoost model predicted stroke requiring surgical intervention with high accuracy in the test cohort, with an area under the receiver operating characteristic curve of 0.802 (sensitivity 0.748, specificity 0.853). We found that simple survey items, such as the level of consciousness, vital signs, sudden headache, and speech abnormalities were the most significant variables for accurate prediction. This algorithm can be useful for prehospital stroke management, which is crucial for better patient outcomes.

Structure and establishment of the German Cochlear Implant Registry

Hearing rehabilitation of patients with severe hearing loss or deafness using cochlear implants (CI) is avery successful but also complex and lifelong process that requires high quality standards for structure, process, and results. Medical registries represent an ideal tool for conducting quality control relevant to care while at the same time collecting scientific data. Therefore, at the initiative of the Executive Committee of the German Society of Oto-Rhino-Laryngology, Head and Neck Surgery (DGHNO-KHC), aGermany-wide CI registry (the German Cochlear Implant Register, DCIR) was to be established. The following goals were to be achieved: 1)legal and contractual basis for the register; 2)definition of the register contents; 3)development of evaluation standards (hospital-specific and national annual reports); 4)development of alogo; 5)practical operation of the registry. After defining acatalog of services that defines the content, structure, and operation of the DCIR, aregistry operator with audiological expertise was sought. After considering various offers, the registry was technically implemented in cooperation with the provider INNOFORCE (Ruggell, Liechtenstein) as registry operator. This also included the realization of an interface for data transfer from previously existing databases and development of adata protection concept for productive operation of the DCIR under the scientific leadership of the DGHNO-KHC Executive Committee. Since January 2022, it has been possible for participating hospitals to enter pseudonymized data into the DCIR. To date, 75hospitals in Germany have contractually agreed to participate in the registry. During the first 15months, data from over 2500implants in over 2000patients were registered in the DCIR. The work presented here describes the structuring, development, and successful establishment of the DCIR. Introduction of the DCIR represents an important milestone of future scientifically based quality control in CI care. The registry presented here can therefore be considered as an example for other areas of medical care and thus also sets an international standard.

A BLOCKCHAIN TECHNOLOGY AND INTERNET OF THINGS TO SECURE IN HEALTHCARE SYSTEM

The huge headway of new advances like the Web of Things and wearable innovation, the medical services industry is extending rapidly these days. To guarantee far off persistent observing, these devices are generally used. Client/server engineering is utilized in the ongoing execution. Due of the security and protection issues raised by this, medical care frameworks are currently more helpless against different assaults. The utilization of a dispersed engineering is expected to resolve these issues and submit to security rules. Block chain has drawn in a ton of interest as a modern innovation to address the security issues in IoT-based frameworks in light of its conveyed nature and its security ensures. With the new presentation of block chain and IoT, the medical care area is supposed to develop altogether and experience an expansion in monetary potential as well as security, protection, effectiveness, and straightforwardness. The client/server engineering is the underpinning of the ongoing execution. In this paper, various protection and security gives that make medical services frameworks more powerless against different assaults.

Study of the problems of ageism and assessment of attitudes towards age in the medical environment

BACKGROUND: Ageism pervades all areas of life, including the areas of medical and social care. Gerontological ageism has a significant negative impact on indicators of physical, mental health, functional status and well-being of older people. In the conditions of an aging society, the study of the scale and characteristics of this problem in various spheres of life is very relevant.&#x0D; AIM: To assess the prevalence of stereotypes of attitudes towards older age among primary health care physicians, senior students of a medical university and directly elderly people.&#x0D; MATERIALS AND METHODS: In the period from 2018 to 2022, 538 people aged 20 to 75 were interviewed in 3 subgroups: 1) senior students of a medical university of medical specialties, 2) young and middle-aged primary health care doctors, 3) elderly people.&#x0D; RESULTS: It was revealed that the opinions about the problems in this age period in the elderly and the beliefs of doctors and medical students often do not coincide.&#x0D; CONCLUSIONS: When training medical personnel, it is necessary to form the correct attitude to age and skills of communicative competence with different age groups of patients.

Empathy and the work of clinical psychiatrists: narrative review

SUMMARYClinical research suggests that empathy is associated with better clinical outcomes in various areas of medical care, raising the question of whether a similar effect occurs in psychiatry. The aim of this review is to explore philosophical, neuroscientific and psychological perspectives on the concept of empathy in the context of the day-to-day work of clinical psychiatrists. The definition of empathy is outlined and sociodemographic factors, working conditions and psychiatrists’ beliefs that can potentially affect empathy in clinical encounters are explored; educational and training aspects are also reviewed. The review concludes suggesting that research on empathy is needed to understand contextual, training and relational factors that could benefit mental healthcare as well as the working conditions of clinical psychiatrists, both inextricably linked.

Regional assessment of medical care provision system by principal component analysis.

The Japanese government has promoted policies ensuring standardized medical care across the secondary medical care areas (SMCAs); however, these efforts have not been evaluated, making the current conditions unclear. Multidimensional indicators could identify these differences; thus, this study examined the regional characteristics of the medical care provision system for 21 SMCAs in Hokkaido, Japan, and the changes from 1998 to 2018. This study evaluated the characteristics of SMCAs by principal component analysis using multidimensional data related to the medical care provision system. Factor loadings and principal component scores were calculated, with the characteristics of each SMCA visually expressed using scatter plots. Additionally, data from 1998 to 2018 were analyzed to clarify the changes in SMCAs' characteristics. The primary and secondary principal components were Medical Resources and Geographical Factors, respectively. The Medical Resources components included the number of hospitals, clinics, and doctors, and an area's population of older adults, accounting for 65.28% of the total variance. The Geographical Factors components included the number of districts without doctors and the population and a land area of these districts, accounting for 23.20% of the variance. The accumulated proportion of variance was 88.47%. From 1998 to 2018, the area with the highest increase in Medical Resources was Sapporo, with numerous initial medical resources (-9.283 to -10.919). Principal component analysis summarized multidimensional indicators and evaluated SMCAs in this regional assessment. This study categorized SMCAs into four quadrants based on Medical Resources and Geographical Factors. Additionally, the difference in principal component scores between 1998 and 2018 emphasized the expanding gap in the medical care provision system among the 21 SMCAs.