Low Resource Research Articles

The creation of a pediatric surgical checklist for adult providers

PurposeTo address the need for a pediatric surgical checklist for adult providers.BackgroundPediatric surgery is unique due to the specific needs and many tasks that are employed in the care of adults require accommodations for children. There are some resources for adult surgeons to perform safe pediatric surgery and to assist such surgeons in pediatric emergencies, we created a straightforward checklist based on current literature. We propose a surgical checklist as the value of surgical checklists has been validated through research in a variety of applications.MethodsLiterature review on PubMed to gather information on current resources for pediatric surgery, all papers on surgical checklists describing their outcomes as of October 2023 were included to prevent a biased overview of the existing literature. Interviews with multiple pediatric surgeons were conducted for the creation of a checklist that is relevant to the field and has limited bias.ResultsForty-two papers with 8,529,061 total participants were included. The positive impact of checklists was highlighted throughout the literature in terms of outcomes, financial cost and team relationship. Certain care checkpoints emerged as vital checklist items: antibiotic administration, anesthetic considerations, intraoperative hemodynamics and postoperative resuscitation. The result was the creation of a checklist that is not substitutive for existing WHO surgery checklists but additive for adult surgeons who must operate on children in emergencies.ConclusionThe outcomes measured throughout the literature are varied and thus provide both a nuanced view of a variety of factors that must be taken into account and are limited in the amount of evidence for each outcome. We hope to implement the checklist developed to create a standard of care for pediatric surgery performed in low resource settings by adult surgeons and further evaluate its impact on emergency pediatric surgery outcomes.FundingFulbright Fogarty Fellowship, GHES NIH FIC D43 TW010540.

Effectiveness of an unguided modular online intervention for highly anxious parents in preventing anxiety in their children: a parallel group randomised controlled trial

Children whose parents have anxiety problems are at increased risk of developing anxiety themselves. Parenting behaviors are a contributing factor to intergenerational transmission. Interventions which seek to limit anxiogenic parenting behaviors have shown potential in reducing anxiety in offspring but are not widely accessible. This prevention trial aimed to establish the effectiveness of an unguided modular online intervention for highly anxious parents in preventing anxiety in their children. A parallel group, block-randomised controlled trial of unblinded participants in a 1:1 ratio was conducted to compare efficacy of the online course compared to a no-intervention control. The intervention comprised 8 modules, of approximately 20min each, and participants progressed through the course at their own pace. The study was conducted entirely online with a self-referred UK-based community sample of parents (child 2-11 years) with substantial anxiety. The primary outcome measure was change in parent-reported child anxiety, as measured by the Spence Children's Anxiety Scale-Parent Report (SCAS-P) or Spence Pre-School Anxiety Scale-Parent Report (Preschool SCAS). Secondary outcomes were child internalising, externalising, and attentional symptoms (Pediatric Symptom Checklist), and parent anxiety (SCARED-Adult). Analyses using complete case analysis following intention to treat principles investigated intervention effects at 6 months (primary analysis) and additionally at 9 to 25-months' follow-up. Trial registration: ClinicalTrials.GovNCT04755933, https://clinicaltrials.gov/ct2/show/NCT04755933. 1811 participants (intervention=900; control=911; 92.7% (1677/1810) female; 85.3% (1535/1800) White-British; 66.8% (1201/1799) university educated). Participant retention (based on primary outcome completion) at T2 (6-months post consent) was 67.6% overall (n=1224) and substantially lower in the intervention arm 57.3% ((516/900) control=77.8% (708/910)). Child anxiety was lower in the intervention group compared to control at 6-month follow-up (adjusted effect size estimate-0.15 (95% CI:-0.23 to-0.08, p<0.001). There was very strong evidence that those in the intervention arm had lowered child anxiety (standardised SCAS score) compared to the control arm, with an effect size (Cohen's d) of-0.16 (95% CI:-0.23 to-0.08, p<0.001). The difference in standardised Spence Child Anxiety Scale score between the arms was-0.15 standard deviations. On the original scales for SCAS-P (0-114) and Preschool SCAS (0-112), this corresponds to a reduction of-2.38 (95% CI:-3.59 to-1.16) and-2.68 (95% CI:-4.05 to-1.31), respectively. No reported harms. A clinically unsupported online intervention designed for parents with high levels of anxiety is effective in reducing anxiety and internalising symptoms in their children, and also anxiety in parents. Given the low resource intensity of this intervention, and the positive effects reported here, these findings suggest it has promise in limiting the intergenerational transmission of severe anxiety. This work was supported by Kavli Trust (grant 38/19).

Justifying access to kidney care in low resource and humanitarian settings.

Access to and quality of kidney care is not equitable between or within countries. A natural question is whether global kidney care inequities are always unjustifiable and unfair, or are sometimes due to unavoidable competing or conflicting ethical duties or responsibilities. Health is a fundamental right for all people. People with kidney conditions should have the same claim on this human right as others. Countries have an obligation to progressively fulfil this right and a duty to do so equitably, but global progress has been slow. Countries with limited resources or faced with humanitarian emergencies must set priorities to allocate resources fairly. This process involves trade-offs and often people requiring kidney replacement therapy are left out because of costs, logistics and lack of data. Major burdens are placed on clinicians who grapple between their duty to their patient and professional codes and their responsibility to a 'greater good'. These dilemmas apply also to industry, governments and the international community who must recognize their share in these duties. Inequities in kidney health and care must be acknowledged and sustainable and collaborative solutions urgently found such that right to kidney care is progressively upheld for everyone everywhere.

Análisis crítico de las nuevas directrices de la OMS sobre alimentación complementaria en el lactante de 6 a 23 meses de edad

Introduction: the World Health Organization (WHO) has issued new recommendations on complementary feeding (CF) in 2023. The introduction of CF takes place with the period of greatest nutritional risk for the toddler. Inadequate CF increases risk for altered physical and cognitive development and the risk of chronic non-communicable diseases. The WHO sets out seven main recommendations based on the review of the available evidence. Objective: present a critical review of the new WHO guidelines on CF. Methods: the analysis has been carried out by the Spanish Group of Gastroenterology and Nutrition of the Spanish Association of Primary Care Paediatrics and has included an exhaustive review of the WHO guidelines and documents of particular relevance in infant feeding from scientific societies of our environment in order to adapt them to our environment. Results: the certainty of the scientific evidence is low or very low for six of the seven recommendations. There is a lack of randomized clinical trials to provide certainty in decision-making and to define health outcomes for each recommendation. The absence of specific recommendations on new trends in food and allergenic foods as well as adaptation to first world countries is noteworthy. Conclusions: the start of adequate CF is key for health in early life. In line with WHO, we conclude that breastfeeding should be promoted as the exclusive food for the first 6 months of life, especially in low resource areas. The introduction of CF should take place around 180 days of life through a diversified and adequate diet. CF involves the acquisition of healthy feeding behaviour. Adaptation of the recommendations to our environment is necessary, in addition to other aspects not considered by the WHO guidelines.

Impact of vaccination against Japanese encephalitis in endemic countries.

Japanese encephalitis (JE) virus is the leading cause of vaccine-preventable encephalitis and a significant cause of disability in Asia and the western Pacific. Many countries have introduced JE vaccination programs, including several low resource countries following WHO's prioritization of JE vaccination in 2006. We sought to characterize the public health impact of JE vaccination programs. JE case data and vaccination coverage rates, were requested from country health officials in 23 JE endemic countries and Chinese Taipei. Additional data were extracted from meeting presentations and published literature. JE incidence was compared before and after vaccination using a minimum three year period pre and post program introduction or expansion. Data suitable for analysis were available for 13 JE-endemic countries and Chinese Taipei, for either all age groups or for children aged under 15 years only. Five countries and Chinese Taipei introduced vaccine prior to 2006 and the all-age JE incidence was reduced by 73-100% in about 5-20 years following introduction. Six countries have introduced JE vaccine since 2006, and JE incidence in children aged younger than 15 years has been reduced by 14-79% as of 2015-2021. JE-specific data were unavailable before introduction in Thailand and Vietnam, but vaccination programs reduced acute encephalitis incidence by 80% and 74%, respectively. Even in the programs with greatest impact, it took several years to achieve their results. JE vaccination has greatly reduced JE in 13 JE-endemic countries and Chinese Taipei. Highest impact has been observed in countries that introduced prior to 2006, but it often took roughly two decades and substantial resources to achieve that level of success. For greatest possible impact, more recently introducing countries and funding agencies should commit to continuous improvements in delivery systems to sustain coverage after initial vaccine introduction.

Women and Poverty: Case Study of Female Labor (TKW) in Indramayu Regency

Women are often paired with poverty problems, structural and cultural obstacles seem to never stop entangling them. The choice to become a migrant worker has become a dream of a decent and prosperous life that for him cannot be relied on by anyone, including the government. With a more dominant economic background and low human resources, women are often powerless to get out of the problems that come to them. Even though it is widely depicted in the media about the grim portrait of migrant workers in various cases, the number of migrant workers continues to increase from year to year. Some of the underlying points are that the employment opportunities available at home are limited and labour wages abroad are much higher than those at home. As the second largest contributor of foreign exchange after oil and gas, TKW should receive more attention, including its rights to obtain protection as a citizen

Efficient Federated Learning Using Dynamic Update and Adaptive Pruning with Momentum on Shared Server Data

Despite achieving remarkable performance, Federated Learning (FL) encounters two important problems, i.e., low training efficiency and limited computational resources. In this paper, we propose a new FL framework, i.e., FedDUMAP, with three original contributions, to leverage the shared insensitive data on the server in addition to the distributed data in edge devices so as to efficiently train a global model. First, we propose a simple dynamic server update algorithm, which takes advantage of the shared insensitive data on the server while dynamically adjusting the update steps on the server in order to speed up the convergence and improve the accuracy. Second, we propose an adaptive optimization method with the dynamic server update algorithm to exploit the global momentum on the server and each local device for superior accuracy. Third, we develop a layer-adaptive model pruning method to carry out specific pruning operations, which is adapted to the diverse features of each layer so as to attain an excellent trade-off between effectiveness and efficiency. Our proposed FL model, FedDUMAP, combines the three original techniques and has a significantly better performance compared with baseline approaches in terms of efficiency (up to 16.9 times faster), accuracy (up to 20.4% higher), and computational cost (up to 62.6% smaller).

Graph neural network based intelligent tutoring system: A survey

Online education is developing rapidly driven by artificial intelligence technology. The massive learning resources lead to information overload and low resource utilization. Intelligent tutoring system (ITS) plays a vital role in the education platform, providing personalized learning services for students. The data obtained from the online education platform has complex correlations, which can be potentially transformed into multi-level graph structures. In recent years, graph neural networks (GNNs) have been tried to be introduced into intelligent learning services due to their superior performance in processing graph-structured data. This paper aims to provide researchers and engineers with a general overview of modeling processes and techniques for intelligent learning services based on GNNs. Through a careful review of the advanced models published between 2019 and 2023, existing research primarily focuses on four detailed areas within the smart services scenario. The GNN models involved are systematically classified, and the principles, pioneers and variants of various models are summarized in detail. Simultaneously, this paper analyzes the applications, the specific problems to be solved, and the technologies and innovations of graph-based models in the four key areas. In addition, we examine the commonly used datasets and evaluation metrics in the field of education. Finally, the current challenges and future development trends are summarized to provide comprehensive and in-depth guidance for research in related fields.

Shock wave generated by composite energetic material driven by electrical non-penetrating wire explosion plasma.

Underwater shock wave technology can realize dynamic rock fracture, which is helpful to increase oil and gas reservoir permeability. It can realize the efficient exploitation of medium and low maturity oil and gas resources. In practical application, the shock wave parameters require not only high intensity but also safety and controllability. To meet these requirements, insensitive composite energetic materials driven by electrical wire explosion plasma were proposed, which is one of the most promising methods. However, when in use, the load assembly process containing wires and energetic materials is complex. In this paper, a new type of energetic material load is proposed, using non-penetrating wire to drive composite energetic material. It can simplify the production process of the energetic load and produce acceptable shock wave parameters. The test results show that both the energy deposition of the wire and the shock wave intensity decrease under a non-penetrating wire structure. However, the shock wave intensity is still higher than that of the underwater electrical wire explosion. Based on schlieren diagnosis, it is found that the composite energetic material is gradually driven, and the energy release is not concentrated. In addition, the "non-wire" structure driving condition was discussed in contrast. Under this condition, the process of ionization channel establishment in composite energetic materials is random. The shock wave intensity is weak because the composite energetic material is in the process of slow detonation.

“Babies are still weeping.” Mothers’ perspectives regarding infants’ pain during vaccination in a low resource setting

“Babies are still weeping.” Mothers’ perspectives regarding infants’ pain during vaccination in a low resource setting

Exploring the Prevalence of HPV Genotypes in Women of Northeast India using the Dry Filter Paper Method and Correlation with Pap Test Findings in Low Resource Setting

Exploring the Prevalence of HPV Genotypes in Women of Northeast India using the Dry Filter Paper Method and Correlation with Pap Test Findings in Low Resource Setting

Remote Sensing Building Damage Assessment Based on Machine Learning

Abstract After the occurrence of various types of disasters, including natural disasters and man-made damage, aid workers need accurate and timely data, such as the damage status of buildings, in order to take effective measures for rescue. So as to solve this problem, this paper researches and designs a building damage classification system based on machine learning. The damage assessment system consists of two network models (building extraction network and damage classification network). This article analyzes and designs the structure of each network model, and discusses the principles related to computer vision in machine learning. Buildings in satellite images are segmented through Siamese Convolutional Neural Network, the BottleNeck Module and Feature Pyramid Network are used in the damage classification assessment network to detect damage to buildings in sub-temporal remote sensing images. Subsequently, the model was trained and tested on different disaster events on the xBD dataset. The results show that the building damage detection system based on Siamese-CNN achieves good detection accuracy, and the system has the advantages of simple operation, good timeliness and low resource consumption, and can well meet the needs of disaster assessment.

Harmony search for hyperparameters optimization of a low resource language transformer model trained with a novel parallel corpus Ocelotl Nahuatl – Spanish

Nahuatl, a low-resource language, does not have an online translator application. Instead, resources are limited to dictionaries, web pages, or digital books. Given this condition, it is vital to provide as much support to the language as possible. This research aims to enhance the BLEU score in machine translation by applying the harmony search heuristic method to state-of-the-art transformers models. This is conducted by finding the optimal hyperparameter settings for the models. Models are trained and tested using a fresh moderate-size parallel corpus of 1.5k phrases. By utilizing harmony search, the study shows an improvement in the BLEU score, enhancing it by 2.569%. In order to accomplish this, various factors related to the hyperparameters need to be considered. The application of harmony search with transformers can be extended to various parallel corpora or models, taking these considerations into account.

Candidaemia and Central Line-Associated Candidaemia in a Network of Indian ICUs: Impact of COVID-19 Pandemic.

Candidaemia is a potentially life-threatening emergency in the intensive care units (ICUs). Surveillance using common protocols in a large network of hospitals would give meaningful estimates of the burden of candidaemia and central line associated candidaemia in low resource settings. We undertook this study to understand the burden and epidemiology of candidaemia in multiple ICUs of India, leveraging the previously established healthcare-associated infections (HAI) surveillance network. Our aim was also to assess the impact that the pandemic of COVID-19 had on the rates and associated mortality of candidaemia. This study included adult patients from 67 Indian ICUs in the AIIMS-HAI surveillance network that conducted BSI surveillance in COVID-19 and non-COVID-19 ICUs during and before the COVID-19 pandemic periods. Hospitals identified healthcare-associated candidaemia and central line associated candidaemia and reported clinical and microbiological data to the network as per established and previously published protocols. A total of 401,601 patient days and 126,051 central line days were reported during the study period. A total of 377 events of candidaemia were recorded. The overall rate of candidaemia in our network was 0.93/1000 patient days. The rate of candidaemia in COVID-19 ICUs (2.52/1000 patient days) was significantly higher than in non-COVID-19 ICUs (1.05/patient days) during the pandemic period. The rate of central line associated candidaemia in COVID-19 ICUs (4.53/1000 central line days) was also significantly higher than in non-COVID-19 ICUs (1.73/1000 central line days) during the pandemic period. Mortality in COVID-19 ICUs associated with candidaemia (61%) was higher than that in non-COVID-19 ICUs (41%). A total of 435 Candida spp. were isolated. C. tropicalis (26.7%) was the most common species. C. auris accounted for 17.5% of all isolates and had a high mortality. Patients in ICUs with COVID-19 infections have a much higher risk of candidaemia, CLAC and its associated mortality. Network level data helps in understanding the true burden of candidaemia and will help in framing infection control policies for the country.

Prevalence and Impact of Psychological Disorders on Pharmacotherapy of Diabetic Patients in Low Resource Settings: A Prospective Assessment in Primary Healthcare Settings.

Prevalence of psychological disorders among individuals with diabetes is significantly higher as compared to the general population. This study aimed to assess the prevalence and impact of psychological disorders on pharmacotherapy of diabetes patients. This cross-sectional study was conducted at two primary care hospitals in Pakistan from April to June 2023. The nine-item Patient Health Care Questionnaire (PHQ-9) scale was used to assess depression in the study's population, and its effects on pharmacotherapy of diabetes. Chi-square test was used to evaluate relationship between ordinal variables/categorical variables and depression whereas; Student's t-test was used to assess the relationship between numerical variables with depression. A total of 320 patients were assessed, comprising 120 (37.5%) males and 200 (62.5%) females, with a mean age of 52.5 (SD±11.8) years. The average duration of diabetes is 7.0 (SD±5.4). The average PHQ-9 score was 8.3 (SD±5.5). Depression was found to be prevalent in 43.7% of the study population. Gender (female) (p-value 0.002), advanced age (p-value 0.002), lower income (p-value 0.001), education levels (p-value 0.001), longer duration of diabetes (p-value 0.001), poor diabetes control according to BSR value (p-value 0.001), usage of injectable insulin (p-value 0.005), and concomitant diseases (p-value 0.001) were found to be independently linked with depression. Significant association was observed between depression and treatment adherence (p-value 0.0025), number of missed doses (p-value 0.045), and difficulty in diabetes management (p-value 0.0015). Our study highlights significant prevalence of depression in study population and the prevalent depression negatively impacts on treatment adherence. It also revealed that depression complicates diabetes management resulting in poor medication adherence, poor diabetes control and diabetes related complications, making diabetes control more challenging and difficult.

The dark side of climate policy uncertainty: Hindering energy transition by shaping environmental taxes effectiveness

Climate policy uncertainty (CPU) may have an adverse impact on the environment by interfering with the effectiveness of environmental policies, but there is currently little evidence to support this indirect effect. By incorporating CPU into the transition function, this paper utilizes the panel smooth transition regression (PSTR) to dynamically analyze how CPU affects the relationship between environmental taxes (ETR) and energy transition. When CPU exceeds the threshold, the promoting effect of ETR on energy transition weakens or reverses. The robustness of the main conclusions is demonstrated by establishing a PSTR estimator with the instrumental variable. This paper also constructs a counterfactual scenario, showing that CPU reduces the positive impact of ETR on renewable energy consumption and generation by 7.6% and 3.5%, respectively. Further analysis indicates that this negative effect arises because CPU likely increases investment risk, particularly for long-term green projects, thereby inhibiting the clean energy market and energy-related green technological innovation. Heterogeneity analysis find that the weakening effect of CPU on the effectiveness of ETR is stronger in countries with low energy resource endowment, high energy intensity, and lower economic development levels, underscoring the need for tailored policy approaches. This research emphasizes that for countries with ambitious energy transition goals, climate policy stability is crucial for ensuring the healthy development of environmental taxes policy and renewable energy markets.

A Pan Plasmodium lateral flow recombinase polymerase amplification assay for monitoring malaria parasites in vectors and human populations

Robust diagnostic tools and surveillance are crucial for malaria control and elimination efforts. Malaria caused by neglected Plasmodium parasites is often underestimated due to the lack of rapid diagnostic tools that can accurately detect these species. While nucleic-acid amplification technologies stand out as the most sensitive methods for detecting and confirming Plasmodium species, their implementation in resource-constrained settings poses significant challenges. Here, we present a Pan Plasmodium recombinase polymerase amplification lateral flow (RPA–LF) assay, capable of detecting all six human infecting Plasmodium species in low resource settings. The Pan Plasmodium RPA-LF assay successfully detected low density clinical infections with a preliminary limit of detection between 10–100 fg/µl for P. falciparum. When combined with crude nucleic acid extraction, the assay can serve as a point-of-need tool for molecular xenomonitoring. This utility was demonstrated by screening laboratory-reared Anopheles stephensi mosquitoes fed with Plasmodium-infected blood, as well as field samples of An. funestus s.l. and An. gambiae s.l. collected from central Africa. Overall, our proof-of-concept Pan Plasmodium diagnostic tool has the potential to be applied for clinical and xenomonitoring field surveillance, and after further evaluation, could become an essential tool to assist malaria control and elimination.

Trauma care supported through a global telemedicine initiative during the 2023–24 military assault on the Gaza Strip, occupied Palestinian territory: a case series

Hospitals, patients, and health-care workers are legally protected by international humanitarian law and the Geneva Convention. However, since Oct 7, 2023, the health-care system in the Gaza Strip, occupied Palestinian territory, has been under unprecedented direct military attacks by Israel, with support for patients proving to be challenging for the remaining health-care workers. Peer-to-peer telemedicine holds promise for assisting surgeons in high-risk, low-resource environments, but might be of reduced utility in extremely austere settings. We present a patient case series of traumatic injuries shared in an international telemedicine group by the surgical team at Nasser Medical Complex, also known as Nasser Hospital, the largest remaining partially functioning hospital in Gaza. WhatsApp (Meta; Menlo Park, CA, USA), a widely available and user-friendly end-to-end encrypted smartphone application, was used to facilitate consultations for weapon-inflicted injuries. All the presented patient cases were shared after obtaining verbal consent from the patients and discussed through a multidisciplinary team approach. The group was developed into a community with more than 15 specialty and injury-oriented subgroups and over 1000 members who joined through non-targeted social media outreach followed by snowball recruitment. Prospective registration and formal ethics approval in Gaza was impossible because the Ministry of Health, including the local Helsinki Committee, had suspended all operations. In June, 2024, we obtained ethics approval from the local Helsinki committee in Gaza. We present 12 select patient case studies from a pool of hundreds of patients admitted to Nasser Hospital between Jan 28 and Feb 12, 2024. Four (33%) of the 12 patients were female and eight (67%) were male, with four patients (33%) being children (younger than 18 years). The age range was between 3 years and 70 years, with a median age of 25 years. Most patients presented with penetrating injuries (11 [92%] of 12), with six patients presenting with wounds secondary to fragment injury, and five patients presenting with wounds due to gunshots. One patient presented with a direct blast injury. The site of reported injuries included head and neck areas (four [33%] of 12), abdomen (four [33%] of 12), chest (three [25%] of 12), pelvis (two [17%] of 12), and limbs (one [8%] of 12). Most patients were lost to follow-up (11 [92%] of 12) and were affected by the invasion of the hospital by the Israeli Defense Forces, which subsequently rendered the hospital non-functional. One patient died following their injury. The health-care team at the now non-functioning Nasser Hospital in southern Gaza adapted their allocation and distribution of extremely low resources and relied on smartphones for specialised telemedicine outreach purposes. This enhanced the capability of the medical teams in management of mass casualties of military assaults that few are trained to work in. Nonetheless, the options available to a health-care system that is under-staffed, under-served, and under siege, are extremely constrained, regardless of such telemedicine initiatives. None.

Performance evaluation of containers for low-latency packet processing in virtualized network environments

Packet processing in current network scenarios faces complex challenges due to the increasing prevalence of requirements such as low latency, high reliability, and resource sharing. Virtualization is a potential solution to mitigate these challenges by enabling resource sharing and on-demand provisioning; however, ensuring high reliability and ultra-low latency remains a key challenge. Since bare-metal systems are often impractical because of high cost and space usage, and the overhead of virtual machines (VMs) is substantial, we evaluate the utilization of containers as a potential lightweight solution for low-latency packet processing. Herein, we discuss the benefits and drawbacks and encourage container environments in low-latency packet processing when the degree of isolation of customer data is adequate and bare metal systems are unaffordable. Our results demonstrate that containers exhibit similar latency performance with more predictable tail-latency behavior than bare metal packet processing. Moreover, deciding which mainboard architecture to use, especially the cache division, is equally vital as containers are prone to higher latencies on more shared caches between cores especially when other optimizations cannot be used. We show that this has a higher impact on latencies within containers than on bare metal or VMs, resulting in the selection of hardware architectures following optimizations as a critical challenge. Furthermore, the results reveal that the virtualization overhead does not impact tail latencies.

Theoretical analysis and technical application of mechanical intelligent manufacturing based on system digital-driven technology

With the accelerating process of global industrialization, the automated fabrication industry, as an important part of the industry, is also developing rapidly. Due to the low efficiency and high resource consumption of traditional manufacturing, it is more important to improve the production efficiency of conventional manufacturing and realize the resource-saving development mode. Due to the characteristics of system digital-driven technology, it can promote the intelligent development of the manufacturing industry. Therefore, the deep integration of system digital-driven technology and manufacturing is conducive to the intelligent promotion of manufacturing. Comparing the difference between the traditional manufacturing industry and the intelligent manufacturing industry, the application potential of system digitalization technology in the manufacturing field is analyzed. Based on the analysis of the theoretical basis of the system digital-driven technology and the application of the system digital technology in the main fields, the importance of the technology for the improvement of the accuracy index in the manufacturing process is emphatically analyzed. The maximum increase can be 5.3%, and the minimum increase can be 3.3%. It can be seen that the deep integration of digital-driven technology and manufacturing can not only improve the intelligent level of manufacturing, realize the intensive development of the industry, but also realize the data sharing of the entire industrial chain.