Health Technology Research Articles

The research of influence factors that possibly lead to cardiovascular disease

Abstract. The emergence of cardiac disease is influenced by numerous variables. Every year a large percentage of people around the world die from heart attacks. This study was to look at how important clinical variables are connected to the chance of having CVD. The analysis used a Kaggle dataset with details from 70,000 patients and 10 different variables. The study examined how factors such as age, gender and changes in cardiac activity during exercise affect overall heart health. Multiple linear regression models were used to analyze these effects. The results show a significant correlation between these factors and an increased risk of heart disease. This emphasizes the importance of these predictors in clinical assessments. It can be concluded from this study that regular medical check-ups, early prevention and treatment should be carried out for these vulnerable groups. The general prevalence of heart disease in the nation can be decreased by implementing these strategies. According to the study, personalized health strategies have the potential to improve CVD outcomes and strengthen preventive measures. All of the experimental results suggest that continued documentation and study of these pathogenic factors in medical diagnostics and experiments could aid in drug development as well as improve medical technology and help more patients with cardiovascular disease recover.

Advancements in Engineering Tetrahedral Framework Nucleic Acids for Biomedical Innovations.

Tetrahedral framework nucleic acids (tFNAs) are renowned for their controllable self-assembly, exceptional programmability, and excellent biocompatibility, which have led to their widespread application in the biomedical field. Beyond these features, tFNAs demonstrate unique chemical and biological properties including high cellular uptake efficiency, structural bio-stability, and tissue permeability, which are derived from their distinctive 3D structure. To date, an extensive range of tFNA-based nanostructures are intelligently designed and developed for various biomedical applications such as drug delivery, gene therapy, biosensing, and tissue engineering, among other emerging fields. In addition to their role in drug delivery systems, tFNAs also possess intrinsic properties that render them highly effective as therapeutic agents in the treatment of complex diseases, including arthritis, neurodegenerative disorders, and cardiovascular diseases. This dual functionality significantly enhances the utility of tFNAs in biomedical research, presenting valuable opportunities for the development of next-generation medical technologies across diverse therapeutic and diagnostic platforms. Consequently, this review comprehensively introduces the latest advancements of tFNAs in the biomedical field, with a focus on their benefits and applications as drug delivery nanoplatforms, and their inherent capabilities as therapeutic agents. Furthermore, the current limitations, challenges, and future perspectives of tFNAs are explored.

Electromagnetohydrodynamic (EMHD) flow of Jeffrey fluid through parallel plate microchannels with surface charge-dependent asymmetric slip

The investigation of electromagnetohydrodynamic (EMHD) flow of non-Newtonian fluids in microchannels represents a compelling intersection of fluid dynamics, electromagnetism and materials science, particularly demonstrating significant potential and importance in contemporary microfluidic applications. This work delves into the intricate mechanisms governing the EMHD flow of non-Newtonian Jeffrey fluids within parallel plate microchannels, with a specific focus on the influence of asymmetric slip boundary conditions that depend on surface charge. The EMHD flow is propelled by the amalgamation of the Lorentz force and a consistent pressure gradient. Analytical solutions for the velocity and volumetric flow rate of this problem are derived employing both the method of separation of variables and Cramer's rule. Initially, this study undertook comparisons with prior research, leveraging pertinent assumptions to validate the precision of our findings. Subsequently, the discussion shifts to the examination of how velocities are affected by surface charge effects under various slip boundary conditions at different Reynolds numbers. The results suggest that velocities are significantly influenced by surface charge effects under asymmetric slip boundary conditions compared to scenarios involving symmetric and single-wall type, irrespective of the Reynolds number, thereby highlighting the importance of this study. Finally, the relationships among key parameters such as surface charge density, Hartmann number, relaxation time and retardation time affecting volumetric flow rate are analyzed, while approaches and specific percentages for increasing or decreasing volumetric flow rate are provided. One of the more interesting findings is that the volumetric flow rate is expected to experience a 3.9% reduction, considering the influence of the surface charge effect. These findings are not only vital for advancing microfluidics but also have the potential to drive new innovations in related medical technologies, given the notable similarities in the physical properties of Jeffrey fluid and blood.

Time from approval to reimbursement recommendations in healthcare systems with centralized HTA processes. Focus on the Polish HTA agency

ABSTRACT Background To analyze the time from drug registration to reimbursement recommendations, we examined medicinal products, including new clinical indications, registered by the EMA between 2014 and 2019 across various therapeutic areas. Materials and Methods The Polish Agency for Health Technology Assessment and Tariffication (AOTMiT) was compared with 11 agencies in England, Wales, Ireland, Scotland, the Netherlands, Norway, France, Germany, New Zealand, Canada, Australia. A total of 1,942 recommendations published by 12 HTA agencies were analyzed. Results The time from registration to recommendation in Poland was statistically significantly longer than for the other countries. The analysis revealed noticeable differences in the time it takes from drug registration to recommendation across the countries included in this analysis. Analyzing trends from 2014 to 2019 in individual countries, it is noteworthy that in most agencies the median time from registration to recommendation is declining. Conclusions This may suggest improvements in the processes of the recommending authorities and the companies responsible for providing data for assessment. Despite Poland having one of the longest times from registration to recommendation among the countries analyzed, there has been a clear year-over-year decrease in the time to publication of reimbursement recommendations.

Patient Experiences with a Smartphone Application dedicated to postoperative recovery after Elective Arthroplasty

IntroductionIn the rapidly evolving landscape of digital health technologies, the widespread use of smartphones has paved the way for innovative applications designed to enhance healthcare experiences. This introduction underscores the global prevalence of smartphone users and their potential in healthcare, particularly exemplified by therapeutic apps such as the ‘PostOp’ smartphone application. Focused on postoperative support, this app prioritises user-friendly design, data recording, and adherence to national standards. The study aims to evaluate the app's success in achieving these objectives, highlighting its continuous improvement based on real user feedback and its potential impact on improving patient experiences and recovery processes. Methods and MaterialsA cohort of elective joint arthroplasty procedure patients at Kettering General Hospital (KGH), spanning a timeframe of one to 12 months post-surgery were surveyed over the telephone regarding their experience of the ‘Post Op’ smartphone utilising a custom, well-structured standardised questionnaire. ResultsThe study surveyed 42 consecutive patients who had undergone elective joint arthroplasty procedures at Kettering General Hospital, including 22 total hip replacement (THR) and 20 total knee replacement (TKR) patients. The respondents, with a median age of 66 years, provided overwhelmingly positive feedback about the ‘Post Op’ smartphone application. On a scale of 1 to 6, the mean ease-of-use score was 5.31, with only two THR patients providing lower scores due to difficulties with photography. However, the app's overall functionality, particularly in uploading photos, received a mean score of 4.78. Despite some technical issues, 97.6% of respondents would recommend the app, emphasising its positive impact on confidence in the recovery and reducing unnecessary healthcare visits. Narrative responses highlighted the app's simplicity, support, and prompt communication with healthcare teams. Overall, the feedback indicates a high level of satisfaction with the ‘Post Op’ application among elective arthroplasty patients, showcasing its potential benefits for postoperative care. ConclusionThe study provides valuable insights into the impact of the ‘Post Op’ smartphone application on postoperative care, acknowledging both its successes and areas for enhancement. Further research and iterative improvements are crucial for optimising patient experiences and ensuring the app aligns effectively with healthcare needs.

A qualitative exploration of participants' perspectives and experiences of novel digital health infrastructure to enhance patient care in remote communities within the Home Health Project.

The Home Health Project, set on Clare Island, five kilometres off the Irish Atlantic coast, is a pilot exploration of ways in which various forms of technology can be utilised to improve healthcare for individuals living in isolated communities. The integration of digital health technologies presents enormous potential to revolutionise the accessibility of healthcare systems for those living in remote communities, allowing patient care to function outside of traditional healthcare settings. This study aims to explore the personal experiences and perspectives of participants who are using digital technologies in the delivery of their healthcare as part of the Home Health Project. Individual semi-structured interviews were conducted with nine members of the Clare Island community participating in the Home Health Project. Interviews took place in-person, in June 2023. Interviews were audio-recorded and transcribed verbatim. The data were analysed inductively using reflexive thematic analysis. To identify determinants of engagement with the Home Health Project, the data was then deductively coded to the Theoretical Domains Framework (TDF) and organised into themes. Seven of the possible 14 TDF domains were supported by the interview data as influences on engagement with the Project: Knowledge, Beliefs about capabilities, Optimism, Intentions, Environmental context and resources, Social influences and Emotion. Overall, participants evaluated the Home Health Project as being of high quality which contributed to self-reported increases in health literacy, autonomy, and feeling well supported in having their health concerns addressed. There was some apprehension related to data protection, coupled with a desire for extended training to address aspects of digital illiteracy. Future iterations can capitalise on the findings of this study by refining the technologies to reflect tailored health information, personalised to the individual user.

Thresholds for the value judgement of health technologies in the United Arab Emirates: a consensus approach through voting sessions

BackgroundIn the evolving healthcare landscape of the United Arab Emirates (UAE), establishing cost-effectiveness thresholds (CETs) is pivotal to informing decision-makers about the value of health technologies.ObjectiveThis study aimed to establish...

A Qualitative Study of Type 2 Diabetes Mellitus Outpatients' Perspectives on Readiness, Acceptance and Barriers of Mobile Apps for Medication Adherence

ObjectivesThis qualitative phenomenological study explored the perspectives of type 2 diabetes mellitus (T2DM) outpatients in adopting mobile apps for medication adherence management. MethodsThrough 25 semi-structured in-depth interviews, themes were identified using thematic analysis, guided by the Technology Readiness and Acceptance Model (TRAM). ResultsAnticipated convenience and benefits, openness to new technologies acted as drivers, while limited digital literacy and concerns about data privacy and security served as inhibitors of readiness to adopt health apps. Acceptance was influenced by elements related to medication, patient, healthcare professional, family and app aspects. The identified barriers were related to patient, smartphone and monetary factors. Patients perceived the need to adopt digital apps were for those with poor adherence, complex medication regimen and forgetfulness issues. However, concerns about effectively implementing this approach were noted as T2DM patients were predominantly late middle-aged adults who faced technical challenges, leading to combination approach between digital technology and conventional patient education and counselling. ConclusionThe findings highlighted the factors influencing patient's readiness, acceptance, and barriers on effective utilisation of digital health solutions in managing adherence issues. Practical implicationsThe elements of TRAM provide guidance for strategic actions to enhance digital health technology adoption among T2DM patients.

Implementing sensor-based digital health technologies in clinical trials: Key considerations from the eCOA Consortium.

The increased use of sensor-based digital health technologies (DHTs) in clinical trials brought to light concerns about implementation practices that might introduce burden on trial participants, resulting in suboptimal compliance and become an additional complicating factor in clinical trial conduct. These concerns may contribute to the lower-than-anticipated uptake of DHT deployment and data use for regulatory decision-making, despite well-articulated benefits. The Electronic Clinical Outcome Assessment (eCOA) Consortium gathered collective experience on deploying sensor-based DHTs and supplemented this with relevant literature focusing on mechanisms that may enhance participant compliance. The process for DHT implementation starts with identifying a clinical concept of interest followed by a digital measure selection, defining active or passive data capture and their sources, the number of sensors with respective body location, plus the duration and frequency of use in the context of perceived participant burden. Roundtable discussions among patient groups, physicians, and technology providers prior to protocol development can be very impactful for optimizing trial design. While diversity and inclusion are essential for any clinical trial, patient populations should be considered carefully in the context of trial-specific aims, requirements, and anticipated patient burden. Minimizing site burden includes assessment of training, research engagement, and logistical burden which needs to be triaged differently for early and late-stage clinical trials. Additional considerations include sharing trial results with study participants and leveraging publicly available data for compliance modeling. To the best of our knowledge, this report provides holistic considerations for sensor-based DHT implementation that may optimize participant compliance.

The Surge in Human Papillomavirus Vaccine Rejection in Nigeria.

In October 2023, Nigeria integrated the single-dose human papillomavirus (HPV) vaccine into its routine immunization program, aiming to protect 7.7 million girls aged 9 to 14 years. This milestone in the fight against HPV-related cancers, especially cervical cancer, faces significant challenges due to high vaccine rejection rates driven by misinformation and cultural barriers. Despite the vaccine's proven safety and efficacy, uptake remains low. This communication highlights the urgent need for a comprehensive public health education campaign to address these barriers. Proposed strategies include leveraging digital health technologies, integrating HPV education into school curricula, training community health workers, engaging religious and cultural leaders, and launching media campaigns featuring personal narratives. Implementing these evidence-based interventions is crucial for dispelling myths, misconceptions, and skepticism surrounding HPV vaccines. This will enhance acceptance and uptake, ultimately reducing cervical cancer mortality in Nigeria.

Economic effects of priority setting in healthcare: a scoping review of current evidence

ObjectivesStudy objective was to map the current literature on the economic effects of priority setting at the system level in healthcare.DesignThe study was conducted as a scoping review.Data sourcesScopus electronic database was searched in June 2023.Eligibility criteriaWe included peer-reviewed articles published 1 January 2020–1 January 2023. All study designs that contained empirical evidence on the financial effects or opportunity costs of healthcare priority setting were included excluding disease, condition, treatment, or patient group-specific studies.Data extraction and synthesisTwo independent researchers screened the articles, and two additional researchers reviewed the full texts and extracted data. We used Joanna Briggs Institute checklists to assess the quality of qualitative, quasi-experimental and economic evaluations and the mixed methods appraisal tool for the mixed method studies. Synthesis was done qualitatively and through descriptive statistics.Results8869 articles were screened and 15 fulfilled the inclusion criteria. The most common study focus was health technology assessment (7/15). Other contexts were opportunity costs, effects of programme budgeting and marginal analysis, and disinvestment initiatives. Priority setting activities analysed in the studies did not achieve cost savings or cost containment (4/15) or have mixed findings at best (8/15). Only five studies found some indication of cost savings, cost containment or increased efficiency. Also, many of the studies consider costs only indirectly or qualitatively.ConclusionsAll in all, there is very little research addressing the pressing question of whether explicit priority setting and priority-setting methods can support cost containment on a health service system level (regional or national). There is limited evidence of the economic effects of priority setting.

Generative AI for Health Technology Assessment: Opportunities, Challenges, and Policy Considerations - an ISPOR Working Group Report

ObjectiveTo provide an introduction to the uses of generative Artificial Intelligence (AI) and foundation models, including large language models (LLMs), in the field of health technology assessment (HTA). MethodsWe reviewed applications of generative AI in three areas: systematic literature reviews, real world evidence (RWE) and health economic modeling. Results(1) Literature reviews: generative AI has the potential to assist in automating aspects of systematic literature reviews by proposing search terms, screening abstracts, extracting data and generating code for meta-analyses; (2) Real World Evidence (RWE): generative AI can facilitate automating processes and analyze large collections of real-world data (RWD) including unstructured clinical notes and imaging; (3) Health economic modeling: generative AI can aid in the development of health economic models, from conceptualization to validation. Limitations in the use of foundation models and LLMs include challenges surrounding their scientific rigor and reliability, the potential for bias, implications for equity, as well as nontrivial concerns regarding adherence to regulatory and ethical standards, particularly in terms of data privacy and security. Additionally, we survey the current policy landscape and provide suggestions for HTA agencies on responsibly integrating generative AI into their workflows, emphasizing the importance of human oversight and the fast-evolving nature of these tools. ConclusionsWhile generative AI technology holds promise with respect to HTA applications, it is still undergoing rapid developments and improvements. Continued careful evaluation of their applications to HTA is required. Both developers and users of research incorporating these tools, should familiarize themselves with their current capabilities and limitations.

Early high-dose cryoprecipitate to reduce mortality in adult patients with traumatic haemorrhage: the CRYOSTAT-2 RCT with cost-effectiveness analysis.

Traumatic haemorrhage is common after severe injury, leading to disability and death. Cryoprecipitate, a source of fibrinogen, may improve outcomes for patients with traumatic haemorrhage. To investigate the effects of early fibrinogen supplementation in the form of 3 pools (15 units, approximately 6g of fibrinogen) of cryoprecipitate on 28-day mortality. A randomised, parallel-group, unblinded, multicentre, international trial and economic evaluation. Patients were randomised to either the intervention (early cryoprecipitate) or the comparator (standard major haemorrhage protocol) arm via opaque, sealed envelopes in the emergency department or the transfusion laboratory/blood bank. All analyses were performed on an intention-to-treat basis. A cost-effectiveness analysis was undertaken. Twenty-five major trauma centres in the UK and one level 1 trauma centre in the USA. Adults who had traumatic haemorrhage following severe injury requiring activation of the major haemorrhage protocol and had received a blood transfusion. Early cryoprecipitate - 3 pools (equivalent to 15 single units of cryoprecipitate or 6 g of fibrinogen supplementation), infused as rapidly as possible, within 90 minutes of arrival at hospital in addition to standard major haemorrhage protocol or standard major haemorrhage protocol only. The primary outcome was all-cause mortality at 28 days. The secondary outcomes were all-cause mortality at 6 hours, 24 hours, 6 months and 12 months from admission; death from bleeding at 6 hours and 24 hours; transfusion requirements at 24 hours from admission; destination of participant at discharge; quality-of-life measurements (EuroQol-5 Dimensions, five-level version and Glasgow Outcome Scale) at discharge/day 28 and 6 months after injury; and hospital resource use up to discharge or day 28 (including ventilator-days, hours spent in critical care and inpatient stays). Eight hundred and five patients were randomised to receive the standard major haemorrhage protocol (control arm). Seven hundred and ninety-nine patients were randomised to receive an additional three pools of cryoprecipitate in addition to standard care (intervention arm). Baseline characteristics appeared well matched. Patients had a median age of 39 (interquartile range 26-55) years, and the majority (79%) were male. All-cause 28-day mortality (n=1531 patients; intention to treat) was 25.3% in the intervention arm compared with 26.1% in the control arm (odds ratio 0.96; p=0.74). There was variability in the timing of cryoprecipitate administration, with overlap between the treatment arms, limiting the degree of intervention separation. There was no evidence that early empiric administration of high-dose cryoprecipitate reduced the risk of death in unselected patients with traumatic haemorrhage. There was also no difference in adverse events. The cost-effectiveness of the intervention was similar to that of standard care. Research to evaluate if fibrinogen replacement is more beneficial for selected patients, for example those with low fibrinogen blood levels, is needed, as is further exploration of whether there is a difference in outcome according to mechanism of injury. This trial is registered as ISRCTN14998314. This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 15/57/02) and is published in full in Health Technology Assessment; Vol. 28, No. 76. See the NIHR Funding and Awards website for further award information.

Managing experts’ conflicts of interest in the EU Joint Clinical Assessment

ObjectiveThis article critically evaluates the European Commission’s 2024 Implementing Regulation (IR) on conflicts of interest (COIs) management for stakeholders in the European Union (EU) Joint Clinical Assessment (JCA), with a focus on individual experts such as clinicians and patient representatives.Key findingsThe IR is the first EU-level framework to assess COIs in the context of health technology assessment (HTA). The regulation requires experts involved in the JCA to submit annual declarations of interest for both financial and non-financial interests and presents a matrix on whether these conflicts should disqualify them from participating in the joint work. We compared the IR to COIs-management approaches from other European national HTA bodies and found that the IR is closely modelled after the French guidelines. Concerns include potential over-representation of experts from a small number of countries, lack of guidance on organisational COIs, and ambiguities in how the size of financial interests are disclosed. Unclear resource allocation for enforcement could also hinder compliance.ConclusionsThe IR marks progress in EU-wide HTA collaboration, but improvements in transparency, expert diversity, and comprehensive COIs management are needed to ensure impartiality in the JCA process.

Beyond the Fill: Navigating Pharmacy's Technological Future in 2050

The pharmacy profession stands at a pivotal juncture as it faces unprecedented technological advancements that will rapidly reshape the healthcare landscape by 2050. This commentary explores the implications of technological advancements for pharmacy practice and how it may impact the workforce in the coming decades. The advent of digital health technologies (DHTs), artificial intelligence (AI), and automation is poised to transform patient engagement and care delivery. The Covid-19 Pandemic has accelerated this shift, and traditional pharmacy roles will evolve to meet these expectations. As AI and DHT adoption increase, it will push the profession beyond its historical focus on logistics and medication dispensing. Several potential scenarios may unfold by 2050, ranging from a diminished workforce overshadowed by technology to an evolved profession that leverages novel technologies to enhance clinical services and patient care. To prepare for these changes, the profession must address key challenges, including advancing education and training to incorporate new competencies, establishing sustainable financial models for emerging roles, embracing advocacy and navigating regulatory constraints to expand scopes of practice, and overcoming societal resistance to change. By embracing continuous learning and adaptability, pharmacists can seize the opportunity to redefine their roles, ensuring they remain indispensable in an evolving healthcare environment.

Perceptions of indirect treatment comparisons as an evidence base in oncology decision-making: results of an international survey of health technology assessment and payer decision-makers.

Aim: Health technology assessment (HTA) and payer organizations are often faced with early decision-making in oncology. To design and conduct robust indirect treatment comparisons (ITCs), it is important to better understand HTA and payer decision-maker perceptions of ITCs. Here we aim to describe what individuals with HTA and payer experience see as the acceptability of ITCs for HTA and payer organization coverage and reimbursement decision-making. Materials & methods: This survey included 30 current and former HTA and payer decision-makers from five countries: Australia, France, Germany, the UK (n=5 each) and the US(n=10). Main outcomes included the ratings of acceptance of ITCs and the presence of well-defined methodological guidance for ITCs. Results: ITCs are generally accepted by participants in Australia and the UK but are more likely evaluated on a case-by-case basis in France, Germany and the US. Four of five participants in Germany and the UK, two of five in Australia and one of five in France reported that well-defined and prescribed criteria regarding the use of ITCs were in place. Conclusion: There is a need for harmonization of methods used to assess ITCs by HTA and payers, especially in the rapidly evolving treatment landscape in oncology.

Optimization of Childbirth Time Phase I Using MicrocontrollerBased Nipple Stimulation

Background: The first stage of labor often takes a long time and causes discomfort forthe mother, so methods are needed to accelerate it. This study aims to evaluate theeffectiveness of microcontroller-based nipple stimulation in accelerating the laborprocess by stimulating the release of the hormone oxytocin which increases uterinecontractions and accelerates cervical opening. Microcontroller technology is used toensure the stimulation is done automatically and measured according to the mother'sphysiological needs. This study involved two groups, namely the group that receivedstimulation and the control group that did not receive stimulation. The results showedthat the stimulated group experienced shorter labor times than the control group andwere less likely to require medical interventions such as induction with drugs.Methods: Close monitoring is still required to ensure safety, especially regarding therisk of uterine hyperstimulation that may affect the condition of the mother and fetus.Further research is needed to test the long-term effectiveness and safety of this methodbefore it is widely applied in obstetric practice.Results: Based on the total library, 600 were identified and as many as 100 additionalarticles were identified. A total of 630 studies failed to meet the inclusion criteria and 70articles were read in their entirety, so that as many as 11 publications were used asreferences.Conclusion: Microcontroller-based nipple stimulation offers an innovative solution thatcan improve the efficiency of labor while providing a better quality of health care.Keywords : First Period of Labor, Medical Technology, Microcontroller, Nipple Stimulation,Time Efficiency

Systematic Literature Review: Health Technology in Nursing

Digital health technologies such as telehealth, electronic health records (EHR), and artificial intelligence (AI) have transformed nursing by enhancing patient care, improving workflow efficiency, and expanding healthcare accessibility. This systematic literature review examines the current role of these technologies in nursing practice, focusing on their impact on patient outcomes, workflow optimization, and accessibility of healthcare services. Findings indicate that telehealth increases healthcare access for underserved populations, EHRs improve care coordination and documentation accuracy, and AI supports predictive care and clinical decision-making. However, challenges such as data security, usability, and ethical considerations remain. Addressing these issues through training, system improvements, and ethical guidelines is essential for optimizing the benefits of digital health technologies in nursing. This review provides insights for healthcare providers and policymakers, emphasizing the importance of technology integration and support in advancing nursing practices.

Machine learning technology for good health and well-being for sustainable human security in South Africa

The failure to achieve sustainable development in South Africa is due to the inability to deliver quality and adequate health services that would lead to the achievement of sustainable human security. As we live in an era of digital technology, Machine Learning (ML) has not yet permeated the healthcare sector in South Africa. Its effects on promoting quality health services for sustainable human security have not attracted much academic attention in South Africa and across the African continent. Hospitals still face numerous challenges that have hindered achieving adequate health services. For this reason, the healthcare sector in South Africa continues to suffer from numerous challenges, including inadequate finances, poor governance, long waiting times, shortages of medical staff, and poor medical record keeping. These challenges have affected health services provision and thus pose threats to the achievement of sustainable security. The paper found that ML technology enables adequate health services that alleviate disease burden and thus lead to sustainable human security. It speeds up medical treatment, enabling medical workers to deliver health services accurately and reducing the financial cost of medical treatments. ML assists in the prevention of pandemic outbreaks and as well as monitoring their potential epidemic outbreaks. It protects and keeps medical records and makes them readily available when patients visit any hospital. The paper used a qualitative research design that used an exploratory approach to collect and analyse data.

Medical image segmentation network based on feature filtering with low number of parameters

In recent years, the medical image segmentation method based on hybrid convolutional neural network (CNN) and Vision Transformer (ViT) has made great progress, but it still faces the challenge of unbalanced global and local modeling, and excessive parameters. In addition, ViT repeatedly uses the whole feature map to model the global information, thus generating irrelevant and weakly related information, which will weaken the performance of the model when facing small datasets and segmentation targets. Therefore, this paper proposes a feature screening network based on similarity, named Screening Feature (SF)-MixedNet. Specifically, this paper first proposes a new feature extractor, namely Correlation based Similarity Transformer (CSimFormer). On the basis of parameter pruning, it uses the Screening Feature Multi-head Self Attention (SF-MSA) to establish the remote dependency, and calculates the similarity between local elements through the Location-Sensitive Mechanism (LsM) to obtain the weight matrix. Then, the correlation between regional elements is mined by Region Matching and Selection (RMS) mechanism, and the obtained information is filtered according to the corresponding rules to reduce the side effects of redundant information. Extensive experiments on Synapse dataset, ACDC dataset and SegPC-2021 dataset show that the segmentation accuracy reaches 83.51%, 92.20% and 81.27% respectively. Especially in the Synapse dataset, our method is 6.31% higher than the baseline. The method proposed in this paper effectively improves the segmentation accuracy, provides more detailed information for medical diagnosis and promotes the development of medical artificial intelligence technology.