Development Of Medical Technology Research Articles

Современные проблемы и возможности в лечении генито­уринарного менопаузального синдрома на этапе развития медицинской науки и технологии

Современные проблемы и возможности в лечении генито­уринарного менопаузального синдрома на этапе развития медицинской науки и технологии

Человеческий эмбрион как потенциальный субъект права

Nowadays, the search for the place of the human embryo in the dyad “subject and object” of law seems to be an urgent challenge for legal science due to the rapid development of medical technologies that make it possible to question the only previously known purpose of the human embryo – to be born as a child. By examining the understanding of legal subjects as developed in various legal paradigms, the author of this study seeks to delineate the place of the human embryo within the subject-object duality of law, justifying the legal status of the human embryo as a potential subject of law from the perspective of a communicative conception of law shared by him. The study employs formal-legal methods, as well as analytical, synthesis, comparative, and thought experiment methods, along with elements of an interdisciplinary approach (utilizing findings from medical research on the human embryo to support legal conclusions, thereby contributing to the scientific novelty of the study). In conclusion, the recognition of the human embryo as a potential subject of law necessitates a nuanced understanding of legal subjectivity and the evolving nature of human development. By engaging with interdisciplinary perspectives and communicative theories of law, we can pave the way for a more inclusive and ethically informed approach to legal discourse surrounding embryonic rights and protections.

Integrating blockchain and ZK-ROLLUP for efficient healthcare data privacy protection system via IPFS

With the rapid development of modern medical technology and the dramatic increase in the amount of medical data, traditional centralized medical information management is facing many challenges. In recent years blockchain, which is a peer-to-peer distributed database, has been increasingly accepted and adopted by different industries and use cases. Key areas of healthcare blockchain applications include electronic medical record (EMR) management, medical device supply chain management, remote condition monitoring, insurance claims and personal health data (PHD) management, among others. Even so, there are a number of challenges in applying blockchain concepts to healthcare and its data, including interoperability, data security privacy, scalability, TPS and so on. While these challenges may hinder the development of blockchain in healthcare scenarios, they can be improved with existing technologies In this paper, we propose a blockchain-based healthcare operations management framework that is combined with the Interplanetary File System (IPFS) for managing EMRs, protects data privacy through a distributed approach while ensuring that this medical ledger is tamper-proof. Doctors act as full nodes, patients can participate in network maintenance either as light nodes or as full nodes, and the hospital acts as the endpoint database of data, i.e., the IPFS node, which saves the arithmetic power of nodes and allows the data stored in the hospitals and departments to be shared with the other organizations that have uploaded the data. Therefore, the integration of blockchain and zero-knowledge proof proposed in this paper helps to protect data privacy and is efficient, better scalable, and more throughput.

Autoprobiotics in the Treatment of Patients with Colorectal Cancer in the Early Postoperative Period.

Despite great advances in the treatment of oncological diseases, the development of medical technologies to prevent or reduce complications of therapy, in particular, those associated with surgery and the introduction of antibiotics, remains relevant. The aim of this study is to evaluate the effectiveness of the use of autoprobiotics based on indigenous non-pathogenic strains of Enterococcus faecium and Enterococcus hirae as a personalized functional food product (PFFP) in the complex therapy of colorectal cancer (CRC) in the early postoperative period. A total of 36 patients diagnosed with CRC were enrolled in the study. Study group A comprised 24 CRC patients who received autoprobiotic therapy in the early postoperative period, while the control group C included 12 CRC patients without autoprobiotic therapy. Prior to surgery and between days 14 and 16 post-surgery, comprehensive evaluations were conducted on all patients, encompassing the following: stool and gastroenterological complaints analysis, examination of the gut microbiota (bacteriological study, quantitative polymerase chain reaction, metagenome analysis), and analysis of interleukins in the serum. Results: The use of autoprobiotics led to a decrease in dyspeptic complaints after surgery. It was also associated with the absence of postoperative complications, did not cause any side effects, and led to a decrease in the level of pro-inflammatory cytokines (IL-6 and IL-18) in the blood serum. The use of autoprobiotics led to positive changes in the structure of escherichia and enterococci populations, the elimination of Parvomonas micra and Fusobacterium nucleatum, and a decrease in the quantitative content of Clostridium perfringens and Akkermansia muciniphila. Metagenomic analysis (16S rRNA) revealed an increase in alpha diversity. Conclusion: The introduction of autoprobiotics in the postoperative period is a highly effective and safe approach in the complex treatment of CRC. Future studies will allow the discovery of additional fine mechanisms of autoprobiotic therapy and its impact on the digestive, immune, endocrine, and neural systems.

Evaluating the integration of traditional gong methods in smart home environment for the recovery of health functions of stroke patients

Since the 21st century, network and mobile communication technology are gradually entering the medical and health services field. Combining body area networks, broad-generation mobile communications, and cloud platforms has made various medical applications for large-scale populations possible. The development of digital medical technology, especially digital telemedicine, is increasingly proving to be an important means of significantly reducing the cost of medical care and access, changing the distribution of medical resources, and improving the overall level of care. To observe the effects of traditional Chinese medicine gongfu combined with rehabilitation therapy on mild depression, anxiety, and functional recovery of activities of daily living (ADL) in patients recovering from stroke, and to provide new treatment methods to improve the function and daily living ability of the group who develop mild depression and anxiety after stroke. In this paper, the digital medical engineering application combining information technology and medical treatment integrates various high-end information technologies such as body domain network and cloud computing to solve the difficulties in the current application one by one, to provide the national people with the system provides “timely”, “local” and “bottomless” remote digital health services to the Chinese people.

Reading practices as a component of preparing future teachers for personalized education of children in a hospital school

Studies show that in recent years the number of children undergoing long-term treatment has been increasing. This is due not only to the spread of cancer and other aggressive diseases among children, but also to the rapid pace of development of medical technologies, which allows more and more children to have favorable life prospects. The article substantiates the need for targeted training of specialists who are capable of psychological and pedagogical work with children in various institutional forms, in particular, in a medical hospital. The description of the university “Reading Club” model is given. The university “Reading Club” is considered a pedagogical tool that promotes the development of students’ reading competence as part of professional culture necessary to ensure the personalization of the educational process in hospital schools. The stages of work of the “Reading Club”, the structure of building the activities of its participants with the possibility of using reading practices with children in long-term treatment are given.

Application of artificial intelligence digital holography technology based on medical sensors in the development of medical image fusion

With the rapid development of artificial intelligence and medical technology, sensor technology, as an important tool to obtain medical data, provides a wealth of physiological parameter information, but the traditional medical image fusion methods are difficult to make full use of the information provided by sensors. Therefore, this paper aims to explore the application of artificial intelligence digital holographic technology based on medical sensor in medical image fusion, and improve the accuracy and effect of medical image diagnosis and treatment. Based on the physiological parameter data obtained by medical sensor, combined with deep learning and image processing algorithm, a medical image fusion method based on artificial intelligence digital holography technology was proposed. The method uses the physiological parameter information provided by the sensor and combines multiple medical image sources to realize holographic medical image presentation. The experimental results show that the artificial intelligence digital holographic technology based on medical sensor can effectively improve the resolution and information content of medical image fusion. Compared with traditional medical image fusion methods, this method has higher image quality and more accurate diagnosis results.

Optimization and Performance Evaluation of Deep Learning Algorithm in Medical Image Processing

In this paper, the optimization and performance evaluation of deep learning algorithm in medical image processing are studied. Firstly, the paper introduces the importance and challenges of medical image processing, and expounds the application prospect of deep learning in this field. Subsequently, this paper discusses the optimization methods of deep learning algorithm in detail, including model structure design, data preprocessing, super parameter adjustment and so on. In terms of performance evaluation, this study selected classic models such as U-Net, DeepLab and DenseNet, and compared them with ROC curve and AUC value to evaluate their predictive ability in medical image classification. The results show that the DenseNet model shows high performance in prediction accuracy, while the performance of U-Net and DeepLab models is slightly average. Finally, the advantages and disadvantages of each model are analyzed, and the future research direction is prospected. This study is of great significance to promote the development and application of medical image processing technology, and provides important theoretical and technical support for medical diagnosis and treatment.

ANALYSIS OF THE INTEGRAL EFFICIENCY OF MEDICAL AID FOR NEWBORN IN UKRAINE

Introduction. Preservation of life and quality of health of newborns is an urgent problem for formation of the future of society and mankind, defense capability, labor reserve and intellectual potential of the country. The fundamental basis for the formation and maintenance of health of newborns is the existence of eff ective health care systems. Objective information about the eff ectiveness of medical care of newborns and its dynamics is the basis for evaluation of achievement of planned results and development of necessary medical organizational technologies. The aim of the study is to analyze and evaluate the integrated eff ectiveness of medical care for newborns in Ukraine at the national and regional levels.Material and Methods. In order to carry out the research, statistical reporting materials on the activities of health care institutions providing medical care to mothers and newborns in all periods of their development for 2018, 2022 were used. The analysis of the integral eff ectiveness of medical care for newborns was carried out using a modifi ed model of the fi nal results of health care institutions. I with the calculations of coeffi cients of comprehensive assessment (CCA) and coeffi cients of achievement of normative values (CANV) of individual indicators with their gradation from high (0,8-1) to low (0,1-0,49) levels. The methods of system approach, bibliographic, statistical data processing and graphical representation are applied.Results. A comprehensive study of the integrated eff ectiveness of medical care for newborns at the national and regional levels conducted at the population level showed a suffi cient, above- average level of achievement of results CCA 0.75 in 2018 and 0.76 in 2022) without clear geological patterns in 2018 and signifi cant diff erences in 2022. – From a high level of CCA (0.82-0.94) in Volyn, Zakarpattia, Ivano- Frankivsk, Lviv, Mykolaiv, Ternopil, Kharkiv and Khmelnytsky regions to a low level of CCA (0.41 and 0.35) in Donetsk and Kherson regions. The study of the main indicative indicators of the eff ectiveness of medical care for newborns in 2022 proved a suffi cient achievement. The normative values of coverage of newborns by screening programs, BCG vaccination, survival and mortality rates of newborns, neonatal transfer index (CANV =0.96, 0.82, 0.94, 0.82 and 0.76, respectively). The most problematic indicators of medical care for newborns with low and below- average levels of the coeffi cient of achievement of results, which are signifi cantly associated with the deterioration of the health of pregnant women and the course of childbirth, are the frequency of low weight, sick newborns (CANV = 0.48, 0.51) and the frequency of transmission of HIV infection from mother to child (CANV = 0.4), which is associated with the fullapplication of an eff ective 4-component strategy for prevention of HIV transmission from mother to child.Conclusions. A toolkit for integral assessment of the eff ectiveness of medical care for newborns as a measure of viability and health quality of the off spring at all stages of ontogenesis has been developed. makes it possible to ensure on a unifi ed basis objective assessment and monitoring of it as a whole, by region and by individual indicators with the subsequent development of measures to infl uence the identifi ed problems and their implementation in the activities of maternal and child health care. The model of integral eff ectiveness of medical care of newborns is a pilot project and has dynamic properties, therefore, in the future, when the normative values of indicators of comprehensive assessment are reached, their revision is planned.

ScRNA‐seq determines the characteristics of T cell marker genes to predict the prognosis of esophageal cancer

AbstractEsophageal cancer (EC) mainly includes two histological subtypes, esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma, which is of high morbidity and mortality. With the continuous development of medical technology, the treatment of EC has been greatly improved, but its prognosis is still unfavorable. Recent single‐cell RNA‐sequencing (scRNA‐seq) is expected to bring breakthroughs in the treatment of EC. First, we identified T cell marker genes and generated signature by analyzing scRNA‐seq data from Expression Omnibus (GEO) database and TCGA database. Then, an immune prognostic model was constructed using the least absolute shrinkage and selection operator. We found that the survival rate of ESCC varied significantly among the low‐ and high‐risk groups. Two genes from T cell signature, DCPS and CYB5R3, were expressed in ESCC cells. Collectively, our study proposed a novel prognostic signature for ESCC patients based on T cell marker genes.

Discussion on Medical Device Adverse Event Surveillance

With the continuous development of medical technology and the wide application of medical devices, the risk of medical device adverse events is gradually increasing. In order to ensure the safety and effectiveness of medical devices, timely detection and treatment of adverse events of medical devices, and to protect the safety and rights of patients, the state continuously strengthens the monitoring of adverse events of medical devices. This paper firstly introduces the domestic and foreign medical device adverse event related regulations, it introduces the form of medical device adverse event monitoring work in China, compares and analyzes the data of medical device adverse events in recent years, and puts forward some problems in medical device adverse event monitoring work, in order to continuously improve the control and management of the risk level of medical devices, and ensure the clinical use of medical devices and patient safety.

A Survey on Transforming Healthcare with IoMT : The Power of Connected Medical Devices

This thorough analysis examines current developments in medical technology, with an emphasis on the Internet of Medical Things (IoMT) and its uses. It covers IoMT's contribution in creating wearable internet monitors for dispersed monitoring systems, addressing pregnancy-related issues, and is divided into four subject groups. Along with blockchain adaption, it also highlights privacy and dependability in IoMT-based health monitoring systems. The paper also emphasizes the contributions of IoMT to healthcare diagnosis and monitoring, including machine learning and edge-AI-based cardiovascular health monitoring and fall prediction. It also covers data science and healthcare informatics techniques, such as using lightweight cryptography to ensure real-time security in remote patient monitoring and identifying unusual user behavior. IoMT has the potential to transform patient care, diagnostics, and data-driven decision-making across a range of healthcare areas, as the paper highlights overall.

ПРОЄКТУВАННЯ АРХІТЕКТУРИ ПРОГРАМНОЇ СИСТЕМИ ДЛЯ СТВОРЕННЯ ЦИФРОВИХ ДВІЙНИКІВ МЕДИКО-БІОЛОГІЧНИХ ОБ'ЄКТІВ

The paper introduces an innovative and universal object-oriented architecture specifically tailored for the creation of digital twins pertaining to medico-biological en-tities, with otolaryngology serving as the primary exemplar. The very essence of this architecture is its profound utilization of polymorphism. By capitalizing on this tech-nique, the architecture offers a substantial reduction in the workload and complexity software developers might face when there's a necessity to adapt or modify the sys-tem for alternative medical specializations. The genesis of this architecture stems from a recognized need to establish a more modular and adaptable framework that can cater to the rapidly evolving land-scape of medical technology and digital twinning. As the medical realm continues to burgeon, having such a flexible and scalable software blueprint becomes paramount, especially when aiming to maintain relevance and efficacy in diverse medical sectors. The paper offers a comprehensive breakdown of the various component groups that constitute the system. Each group is dissected to provide clarity on its function, importance, and integration with the broader system. This hierarchical and systematic representation ensures that software developers, medical researchers, and other stakeholders have a clear roadmap when engaging with the architecture. In summation, this research stands as a pivotal contribution to the intersection of medical technology and software development. By providing a robust and adapt-able architectural blueprint for digital twinning in the medico-biological domain, it paves the way for future innovations and ensures that the medical community can harness the power of digital replication with increased accuracy, efficiency, and ver-satility.

Risk of cardiovascular death in patients with hepatocellular carcinoma based on the Fine-Gray model.

Hepatocellular carcinoma (HCC) is one of the most common types of cancers worldwide, ranking fifth among men and seventh among women, resulting in more than 7 million deaths annually. With the development of medical technology, the 5-year survival rate of HCC patients can be increased to 70%. However, HCC patients are often at increased risk of cardiovascular disease (CVD) death due to exposure to potentially cardiotoxic treatments compared with non-HCC patients. Moreover, CVD and cancer have become major disease burdens worldwide. Thus, further research is needed to lessen the risk of CVD death in HCC patient survivors. To determine the independent risk factors for CVD death in HCC patients and predict cardiovascular mortality (CVM) in HCC patients. This study was conducted on the basis of the Surveillance, Epidemiology, and End Results database and included HCC patients with a diagnosis period from 2010 to 2015. The independent risk factors were identified using the Fine-Gray model. A nomograph was constructed to predict the CVM in HCC patients. The nomograph performance was measured using Harrell's concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) value. Moreover, the net benefit was estimated via decision curve analysis (DCA). The study included 21545 HCC patients, of whom 619 died of CVD. Age (< 60) [1.981 (1.573-2.496), P < 0.001], marital status (married) [unmarried: 1.370 (1.076-1.745), P = 0.011], alpha fetoprotein (normal) [0.778 (0.640-0.946), P = 0.012], tumor size (≤ 2 cm) [(2, 5] cm: 1.420 (1.060-1.903), P = 0.019; > 5 cm: 2.090 (1.543-2.830), P < 0.001], surgery (no) [0.376 (0.297-0.476), P < 0.001], and chemotherapy(none/unknown) [0.578 (0.472-0.709), P < 0.001] were independent risk factors for CVD death in HCC patients. The discrimination and calibration of the nomograph were better. The C-index values for the training and validation sets were 0.736 and 0.665, respectively. The AUC values of the ROC curves at 2, 4, and 6 years were 0.702, 0.725, 0.740 in the training set and 0.697, 0.710, 0.744 in the validation set, respectively. The calibration curves showed that the predicted probabilities of the CVM prediction model in the training set vs the validation set were largely consistent with the actual probabilities. DCA demonstrated that the prediction model has a high net benefit. Risk factors for CVD death in HCC patients were investigated for the first time. The nomograph served as an important reference tool for relevant clinical management decisions.

System for evaluating medical technologies in military healthcare

Modern challenges and threats, as well as unprecedented sanctions pressure on the Russian Federation, have contributed to the intensification of research both on the development of innovative medical technologies and on expanding the range of use of existing ones. At the same time, on the one hand, there is an increase in incoming proposals for the use of various medical technologies in military healthcare, and on the other hand, the need to ensure accessibility and improve the quality of medical care for military personnel and other cate- gories of assigned contingents is rapidly increasing. At the same time, in con- ditions of limited resources, the level of requirements for justifying the need to introduce one or another medical technology into the activities of military medical organizations and other medical units of the Armed Forces of the Rus- sian Federation naturally increases. All this predetermines the relevance of the development of a departmental system for assessing medical technologies for effective information support for making rational management decisions. The study examined the main directions of development of the medical tech- nology assessment system in military healthcare. In particular, goals and objectives are defined, the main aspects and possible forms of organizing a departmental system for assessing medical technologies are substantiated. The main elements of the basic model for assessing medical technologies in military healthcare are identified. In addition, the characteristics of the in- formation system for assessing medical technologies in military healthcare are given, its main components are given, as well as the expected effects of implementation. The implementation of the departmental concept for assessing medical tech- nologies in the main directions of development presented in the article on the basis of a specialized information system will not only help increase the availability of effective and safe medical technologies, but also the rational use of funds and other military healthcare resources. In addition, taking into ac- count the results of departmental assessment of medical technologies at the state level will serve as the basis for the formation of priority directions for the strategic development of the domestic medical and pharmaceutical industry in the interests of national defense and state security.

Gut microbiota in the combined treatment of colorectal cancer using autoprobiotics

Despite great advances in the treatment of oncological diseases, the development of medical technologies to prevent or reduce complications of therapy, in particular, those associated with surgery and the introduction of antibiotics, remains relevant. The aim of the study was to evaluate the effectiveness of the use of autoprobiotics based on indigenous non-pathogenic strains of Enterococcus faecium and E. hirae in the complex therapy of colorectal cancer (CRC) in the early postoperative period. The use of autoprobiotics did not cause side effects and led to a decrease in the level of pro-inflammatory cytokines (IL-6 and IL-18) in the blood serum. The features of the intestinal microbiome in patients with CRC were revealed, which are fundamentally different from those of other authors by an increase in alpha- biodiversity, lactobacilli, bifidobacteria, Bacteroides thetaiotaomicron and its additional differences associated with the absence of non-pathogenic enterococci: a greater amount of Parvimonas micra, a smaller amount of Akkermansia spp., an increase in the content of Klebsiella sp., Fusobacterium nucleatum and Clostridium perfringens. The use of autoprobiotics led to the elimination of P. micra, a decrease in C. perfringens, which led to the normalization of the microbiota in most patients. The effectiveness of autoprobiotics in the treatment of CRC has been proven, which, apparently, is associated with a change in the composition of intestinal microbiocenosis.

Machine Learning-Based Medical Imaging Detection and Diagnostic Assistance

With the development of medical technology, medical imaging technology plays an increasingly important role in diagnosing and monitoring diseases. At the same time, machine learning technology has shown strong capabilities in data processing and analysis, providing new possibilities for the detection and auxiliary diagnosis of medical images. This paper will deeply discuss the application of machine learning in medical images, especially the application of deep learning in medical images, and how to achieve effective medical image detection and auxiliary diagnosis through steps such as preprocessing, feature extraction, model training and optimization.

INTISARI ANALISIS PERSIAPAN PELAKSANAAN PATIENT SAFETY DI RUANG RAWAT INAP (STUDY KASUS DI RSUD KABUPATEN BIMA)

The era of globalization impact very rapidly, in the development of advanced medical technology. These conditions have an impact on medical services is very complex and it is potentially causing the error, so that the necessary improvement of health care quality. Patient safety is one important component in the quality of health care. Improved patient safety is a necessary step to prevent and minimize unwanted incident (KTD). Nurses are one of the health workers who are at the forefront of health care and have a very important role in improving patient safety. To determine attitudes on the analysis of patient safety in the inpatient unit nurse Bima district hospital and in particular to identify the components of patient safety attitudes include climate of team work, working conditions, employment decisions, and some factors that support and hinder patient safety attitudes. The research is descriptive qualitative. Subjects were 3 nurses and 3 patients with interview techniques. Data collection techniques in this study used the analysis of qualitative data. A qualitative data analysis technique is using descriptive analysis techniques to describe the data in the field which were analyzed and concluded. Components of the patient safety attitudes is climate of teamwork that showed lower patient safety attitudes, job satisfaction showed high patient safety attitudes, working conditions showed lower patient safety attitudes, for logistical support in the form of medical equipment are laboratory equipments that still lacking. Components of the patient safety attitudes were high that consist job satisfaction, and the low patient safety attitudes components were the teamwork climate and conditions of employment, because they needed additional medical equipment such as laboratory equipments.

Trends in COVID-19 Vaccine Development: Vaccine Platform, Developer, and Nationality.

Various vaccine platforms, including emerging platforms, have been applied in the development of COVID-19 vaccines. Biotechnology startups often lead the development of new medical technologies, whereas major pharmaceutical companies and public institutions have long contributed to vaccine development. In this study, vaccine platforms and developers involved in COVID-19 vaccine development were analyzed, elucidating the trends of vaccine platforms used, the country distribution of the developers, and differences in the profiles of developers by vaccine platform technologies and country. The analysis revealed that conventional, established, and emerging vaccine platforms have been widely used and that older platforms are more advanced in clinical development. It also demonstrated the emergence of China, in addition to the U.S., while many pharmerging countries have been engaged in development. Startups have significantly contributed to the development of viral vector and RNA-based vaccines, suggesting their important role in the application of novel technologies. The major developers differ by country and region. Alliances, including international collaborations, have progressed in late clinical development. Based on these results, future perspectives of pandemic vaccine development and implications for policy and corporate strategies are discussed.

Chronicling the Experiences of Life Sciences Teachers and Learners on the Usage of Enquiry-Based Learning in Enhancing Learners’ Academic Performance

Life sciences research provides critical insights into disease processes and allows for the development of novel treatments and innovative medical technologies, thereby directly improving human health and technology. Despite the widely acknowledged relevance of life sciences, there has been a long-term pattern of low performance. This is due to inefficient teaching methods, as how a lesson is delivered influences the learners' level of understanding, among other things. Hence, the present study examined the experiences of life sciences teachers and learners in using IBL to enhance the academic performance of life science learners. This study was underpinned by the interpretivism paradigm, a qualitative approach, and a participatory research approach. The study population consisted of all life sciences learners in a rural school in the Amathole West district, Eastern Cape province of South Africa, from which 2 life sciences teachers and 14 learners were conveniently sampled. Data were collected using interviews, observations, and document reviews, and they were analysed using thematic analysis. The research findings revealed that enquiry-based learning has the potential to foster the development of critical thinking, problem-solving, and communication skills among life sciences learners. However, several issues make it difficult to successfully implement enquiry-based learning in the context of teaching and learning life sciences, including a lack of resources, time constraints, misreading of instructions, a lack of support or supervision, and a lack of pedagogical topic expertise among teachers. The study concludes that enquiry-based learning, when done right, can help learners understand life sciences concepts deeper and remember what they have learnt for a longer period.