Search

Abstract Background Significant levels of funding have been provided to low- and middle-income countries for development assistance for health, with most funds coming through direct bilateral investment led by the USA and the UK. Direct attribution of impact to large-scale programs funded by donors remains elusive due the difficulty of knowing what would have happened without those programs, and the lack of detailed contextual information to support causal interpretation of changes. Methods This study uses the synthetic control analysis method to estimate the impact of one donor’s funding (United States Agency for International Development, USAID) on under-five mortality across several low- and middle-income countries that received above average levels of USAID funding for maternal and child health programs between 2000 and 2016. Results In the study period (2000–16), countries with above average USAID funding had an under-five mortality rate lower than the synthetic control by an average of 29 deaths per 1000 live births (year-to-year range of − 2 to − 38). This finding was consistent with several sensitivity analyses. Conclusions The synthetic control method is a valuable addition to the range of approaches for quantifying the impact of large-scale health programs in low- and middle-income countries. The findings suggest that adequately funded donor programs (in this case USAID) help countries to reduce child mortality to significantly lower rates than would have occurred without those investments.

Abstract Background Many low- and middle-income countries cannot measure maternal mortality to monitor progress against global and country-specific targets. While the ultimate goal for these countries is to have complete civil registrations systems, other interim strategies are needed to provide timely estimates of maternal mortality. Objective The objective is to inform on potential options for measuring maternal mortality. Methods This paper uses a case study approach to compare methodologies and estimates of pregnancy-related mortality ratio (PRMR)/maternal mortality ratio (MMR) obtained from four different data sources from similar time periods in Bangladesh, Mozambique, and Bolivia—national population census; post-census mortality survey; household sample survey; and sample vital registration system (SVRS). Results For Bangladesh, PRMR from the 2011 census falls closely in line with the 2010 household survey and SVRS estimates, while SVRS’ MMR estimates are closer to the PRMR estimates obtained from the household survey. Mozambique's PRMR from household survey method is comparable and shows an upward trend between 1994 and 2011, whereas the post-census mortality survey estimated a higher MMR for 2007. Bolivia's DHS and post-census mortality survey also estimated comparable MMR during 1998–2003. Conclusions Overall all these data sources presented in this paper have provided valuable information on maternal mortality in Bangladesh, Mozambique, and Bolivia. It also outlines recommendations to estimate maternal mortality based on the advantages and disadvantages of several approaches. Contribution Recommendations in this paper can help health administrators and policy planners in prioritizing investment for collecting reliable and contemporaneous estimates of maternal mortality while progressing toward a complete civil registration system.

Coking wastewater poses a serious threat to the environment due to the presence of a wide spectrum of refractory substances such as phenolic compounds, polycyclic aromatic hydrocarbons and heterocyclic nitrogenous compounds. These toxic substances are difficult to treat using conventional treatment methods alone. In recent years much attention has been given to the effective treatment of coking wastewater. Thus, this review seeks to provide a brief overview of recent developments that have taken place in the treatment of coking wastewater. In addition, this article addresses the complexity and the problems associated with treatment followed by a discussion on biological methods with special focus on bioaugmentation. As coking wastewater is refractory in nature, some of the studies have been related to improving the biodegradability of wastewater. The final section focuses on the integrated treatment methods that have emerged as the best solution for tackling the highly unmanageable coking wastewater. Attention has also been given to emerging microwave technology which has tremendous potential for treatment of coking wastewater. HIGHLIGHTS Cost-effective treatment of coking wastewater is a challenge.; A brief overview of recent developments that have taken place in the treatment of coking wastewater.; Discussion on integrated treatment methods.; The conventional biological treatment has been replaced with more efficient and practical solutions.; Technical and economic viability studies related to treatment methods.;

Abstract Gravitational-waves (GWs) data have widely been used for testing preferred modified gravity theories. In this paper, we investigate the possibility of testing them in the strong gravity regime by looking at the properties of compact objects in dense matter physics. In this direction modified gravity theories such as f(R, T) gravity can be tested with the recently discovered compact binary merger, GW 190814, containing a compact object with mass 2.50–2.67 $$M_{\odot }$$ M ⊙ . By considering these constraints on maximum mass of such an object, we predict the existence of quark stars (QSs) made of quark matter in the color-flavor-locked (CFL) phase of color superconductivity. Such a state is significantly more bound than ordinary quark matter and enhances the possibility of the existence of a pure stable QS. We focus on the following aspects in particular: mass–radius profile, mass-central mass density relation, compactness and the corresponding effective adiabatic index for stability related issues. Our result implies that predicted properties for QSs are well consistent with GW 190814 observational data that helps us to impose constraints on the theoretical models of dense nuclear matter.

Abstract Renewable energy sources have recently been integrated into microgrids that are in turn connected to electric vehicle (EV) charging stations. In this regard, the optimal planning of microgrids is challenging with such uncertain generation and stochastic charging/discharging EV models. To achieve such ambitious goals, the best sites and sizes of photovoltaic and wind energy units in microgrids with EV are accurately determined in this work using an optimization technique. This proposed technique considers 1) generation profile uncertainty in photovoltaic and wind energy units as well as the total load demand, 2) photovoltaic and wind generation units' DSTATCOM operation capability, and 3) various branch and node constraints in the microgrid. Most importantly, the possible EV requirements are also taken into account, including initial and predetermined state of charge (SOC) arrangements, arrival and departure hours, and diverse regulated and unregulated charging strategies. A bi‐level metaheuristic‐based solution is established to address this complex planning model. The outer level and inner‐level functions optimize renewable energy sources and EV decision variables. Sub‐objectives to be optimized voltage deviations as well as grid power. The results demonstrate the effectiveness of the introduced method for planning renewable energy sources and managing EV to effectively achieve autonomous microgrids.

تقع مدينة قلمرية في القسم الشمالي من تسعى هذه الدراسة الى الكشف عن القوانين العامة التي تحكم شعرية الشاعر بدر شاكر السياب في قصيدته(غريب على الخليج), عن طريق الوقوف على جوانبها الموسيقية, والبنى التركيبية؛ للكشف عن شعرية هذه القصيدة ، وعد عنصر التكرار على مستوى الصوت المفرد والكلمة والجملة عنصراً مهماً من العناصر التي شكّلت شعرية قصيدة (غريب على الخليج). فقد وظف الشاعر المستوى التركيبي من الجمل ( الاسمية والفعلية ) انسجاماً مع الرؤية النفسية بسياقات تتكشف أمامها الشعرية في القصيدة ، وتوصل البحث الى ان الشعرية علم قائم بذاته يتجلى في النصوص الإبداعية عن طريق لغة غير اعتيادية تكسر التوقع عند المتلقي .

Microstructure in alloys decides their physical properties; however, microstructure variations in metallic alloys are never quantitative. This applies to ferrous and non-ferrous alloys. Therefore, a correlative methodology is proposed for their indirect quantification using x-ray diffraction (XRD) and Raman spectroscopy. As a representative case, 16 different iron-based alloys with slight variations in composition and microstructure are considered. Changes to their properties and microstructure are correlated with XRD and Raman spectroscopy. Thermal treatments also have a role in such variation. Every x-ray peak position and FWHM was analyzed and correlated with corresponding Raman spectra and FWHM. The objective is the development of a reliable database and secondary testing methodology for fast performance estimation of different ferrous and non-ferrous alloys during production and for checking repeatability, other than by their microstructure and tensile strength, which is done at present.

The current study investigates the structural performance of lightweight concrete panels produced using ferrocement (wire-meshed), hybrid (wire-meshed and steel fiber), and sponge-cementitious immersed layers. These panels presented a novel approach to producing a lightweight concrete panel to be used as an alternative to the traditional Jack-arch masonry slab system. The panels were made in dimensions of 600mm length(l), 200mm width (w), and 54mm thickness (h), using locally available sponge materials and super cementitious mortar incorporated with ferrocement layers. To determine the proper thickness of a sponge layer to be used in panel manufacturing, a material characterization was performed. The obtained results from the material characterization indicated a significant reduction in the density compared with the conventional Jack-arch slab system. The sponge core thickness positively affected the developmental compressive strength. For all sponge thickness modes, the density of developed sponging concrete was within the acceptance criteria of lightweight structural concrete. The average density of developing sponge concrete was 15.6 kN/m3, and the average absorption ratio was 14.78 %, while the density of cementitious mortar was 21.96 kN/m3. As for the structural performance of the resulting lightweight concrete panel, the panel with a hybrid layer (incorporating short steel fiber with steel wire mesh) 10mm layer was the best reinforcement method compared with reinforcing with the wire mesh (ferrocement) solely. Furthermore, the findings of this study depicted that the bending moment capacity of the developed lightweight concrete panel was higher than the conventional Jack-arch masonry usually used in traditional residential housing and lower density.

BackgroundMalnutrition imposes enormous costs resulting from lost investments in human capital and increased healthcare expenditures. There is a dearth of research focusing on the prediction of women's body mass index (BMI) and malnutrition outcomes (underweight, overweight, and obesity) in developing countries. This paper attempts to fill out this knowledge gap by predicting the BMI and the risks of malnutrition outcomes for Bangladeshi women of childbearing age from their economic, health, and demographic features.MethodsData from the 2017-18 Bangladesh Demographic and Health Survey and a series of supervised machine learning (SML) techniques are used. Additionally, this study circumvents the imbalanced distribution problem in obesity classification by utilizing an oversampling approach.ResultsStudy findings demonstrate that the support vector machine and k-nearest neighbor are the two best-performing methods in BMI prediction based on the coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). The combined predictor algorithms consistently yield top specificity, Cohen's kappa, F1-score, and AUC in classifying the malnutrition status, and their performance is robust to alternative standards. The feature importance ranking based on several nonparametric and combined predictors indicates that socioeconomic status, women's age, and breastfeeding status are the most important features in predicting women's nutritional outcomes. Furthermore, the conditional inference trees corroborate that those three features, along with the partner's educational attainment and employment status, significantly predict malnutrition risks.ConclusionTo the best of our knowledge, this is the first study that predicts BMI and one of the pioneer studies to classify all three malnutrition outcomes for women of childbearing age in Bangladesh, let alone in any lower-middle income country, using SML techniques. Moreover, in the context of Bangladesh, this paper is the first to identify and rank features that are critical in predicting nutritional outcomes using several feature selection algorithms. The estimators from this study predict the outcomes of interest most accurately and efficiently compared to other existing studies in the relevant literature. Therefore, study findings can aid policymakers in designing policy and programmatic approaches to address the double burden of malnutrition among Bangladeshi women, thereby reducing the country's economic burden.

Background: Dracunculus medinensis or 'Guinea-worm' is the parasitic worm that causes Dracunculiasis disease. The Cyclops (Meso and Micro Cyclops), which is only spread through drinking from water sources in endemic areas, carries this worm. This study aimed to detect and identify Cyclops in wells water, Jabal Awliya locality Khartoum state, Sudan 2021 Methods: This is a cross sectional study held in Jabal Awliya locality which is located in Khartoum state Sudan from 2021-2022. The locality is one of the seven localities in the state which is considered as the main gate for the refugees from South Sudan, Chad and Ethiopia where Dracunculus medinensis has not been eradicated yet. The population is 274,321. Results: A total of 264 samples were collected,132 from well’s water and 132 from post wells water sources. Well’s water contamination with cyclops was found to be 2.4% while post well’s contamination was found to be 8.9%. The species reported by microscopy are: Afrocyclops, Mesocyclops and Microcyclops. Significant statistical difference between well’s and post well’s contamination was found (p-value 0.02). Conclusions: In conclusion, it is apparent that well’s water as well as dam water are contaminated with copepods (Afro-, Meso- and Microcyclops). Hence Residents in the research regions are at hazard for Dracunculus infection whenever larvae make their way to the water sources since mesocyclops and microcyclops are recognized Guinea worm vectors. Since no apparent water treatment system has been found in the areas under study, it is crucial that water sources in this area be treated before consumption in order to reduce the risk of illness. Awareness by the worm as well as the disease should be raised in order to ensure that the larvae from the hosts will not be carried to the wells.

Elhadi Miskeen,1 Amar Ibrahim Omer Yahia,2 Tarig Babikir Eljack,2 Hatim Khalifa Karar3 1Department of Obstetrics and Gynaecology, College of Medicine, University of Bisha, Bisha, 61922, Saudi Arabia; 2Unit of Pathology Department of Basic Medical Sciences, College of Medicine, University of Bisha, Bisha, 61922, Saudi Arabia; 3Department of Pathology and Laboratory Medicine, King Abdullah Hospital, Bisha, Saudi ArabiaCorrespondence: Elhadi MiskeenDepartment of Obstetrics and Gynaecology, College of Medicine, University of Bisha, P.O. Box 1290, Bisha, 61922, Saudi ArabiaEmail emiskeen@ub.edu.saPurpose: Since the emergence of the COVI9-19 pandemic, there has been concern about the availability and sufficiency of blood transfusions to meet patient needs. Also, the adequate and safe blood supply is a major issue to fulfill present demands. This study aims to determine the impact of the COVID-19 pandemic on the blood transfusion service and identify solutions to overcome this impact from the perspective of blood donors and healthcare professionals.Methods: This study was conducted prospectively among Saudi Arabian blood donors and healthcare professionals between May 2020 and May 2021. A group of professional health care professionals and blood donors participated in this study to determine the impact of the COVID-19 pandemic on blood transfusion services and identify possible solutions to overcome the adverse effects on blood system activities.Results: To understand the impact of pandemic COVID-19 on blood transfusion services in Saudi Arabia, we investigated population dynamics and statistical analysis from different age groups and health care professionals. A total of 424 blood donors and 372 healthcare professionals participated in this study. The suggested solution by the participants to overcome the blood shortage during pandemics was the organization of mobile blood drives at donors’ homes, work, and educational sites. Statically significant associations were found between blood donation during this pandemic and age (p=0.019) and marital status (p=0.001).Conclusion: The findings of this study highlight the main problems of blood transfusion due to the onset of COVID-19. Hence, the data could be a source of improving blood transfusion and blood donation systems by healthcare centers and on an individual basis. Healthcare professionals use this public management system in hospitals to minimize the adverse effects of the pandemic.Keywords: health-care professionals, blood transfusion, blood donation, COVID-19

Agricultural pests cause between 20 and 40 percent loss of global crop production every year as reported by the Food and Agriculture Organization (FAO). Therefore, smart agriculture presents the best option for farmers to apply artificial intelligence techniques integrated with modern information and communication technology to eliminate these harmful insect pests. Consequently, the productivity of their crops can be increased. Hence, this article introduces a new mobile application to automatically classify pests using a deep-learning solution for supporting specialists and farmers. The developed application utilizes faster region-based convolutional neural network (Faster R-CNN) to accomplish the recognition task of insect pests based on cloud computing. Furthermore, a database of recommended pesticides is linked with the detected crop pests to guide the farmers. This study has been successfully validated on five groups of pests; called Aphids, Cicadellidae, Flax Budworm, Flea Beetles, and Red Spider. The proposed Faster R-CNN showed highest accurate recognition results of 99.0% for all tested pest images. Moreover, our deep learning method outperforms other previous recognition methods, i.e., Single Shot Multi-Box Detector (SSD) MobileNet and traditional back propagation (BP) neural networks. The main prospect of this study is to realize our developed application for on-line recognition of agricultural pests in both the open field such as large farms and greenhouses for specific crops.

This study was carried out to investigate the effect of acarbose or combination of acarbose and Oleuropein (OLEU) on glycemic index and antioxidant status of male rats exposed to high fructose(40%) and 0.05% hydrogen peroxide H2O2 Thirty-two adult male rats were randomly divided into four equal groups: control group (CC); T1( HFr-H2O2) group were exposed to high fructose (40%) in drinking water and given orally 0.05% H2O2; T2: 30mg/kg of acarbose were given orally to HF-H2O2 treated rats, while combination of acarbose and Oleuropein (50mg/kg. B.W) were given orally to (HFr-H2O2) treated rats in group T3. Blood samples were taken at zero time and after two months of the experiment for measuring some parameters related to glycemic index and antioxidant status. The results declared an elevation in the glycemic index (insulin and glucose concentrations and insulin resistance (IR)) and malondialdehyde (MDA) and depression in glutathione (GSH) concentrations in T1 group at the end of experiment comparing to other treated groups. Antioxidant status and glycemic index were restored after acarbose or combination of acarbose and Oleuropein treatment characterized by significant depression of serum glucose, insulin concentrations and IR, and alleviation of oxidative stress clarified by depression of serum MDA with elevation in serum GSH concentration in groups T2 and T3. On conclusion, the current study documented the oxidative and hyperglycemic effect of fructose and H2O2 that can be ameliorating by oral administration of acarbose. Besides, combination of OLUE supplement with acarbose possessed additive effects.

Skin cancer is one of the most prevalent and deadly types of cancer. Dermatologists diagnose this disease primarily visually. Multiclass skin cancer classification is challenging due to the fine-grained variability in the appearance of its various diagnostic categories. On the other hand, recent studies have demonstrated that convolutional neural networks outperform dermatologists in multiclass skin cancer classification. We developed a preprocessing image pipeline for this work. We removed hairs from the images, augmented the dataset, and resized the imageries to meet the requirements of each model. By performing transfer learning on pre-trained ImageNet weights and fine-tuning the Convolutional Neural Networks, we trained the EfficientNets B0-B7 on the HAM10000 dataset. We evaluated the performance of all EfficientNet variants on this imbalanced multiclass classification task using metrics such as Precision, Recall, Accuracy, F1 Score, and Confusion Matrices to determine the effect of transfer learning with fine-tuning. This article presents the classification scores for each class as Confusion Matrices for all eight models. Our best model, the EfficientNet B4, achieved an F1 Score of 87 percent and a Top-1 Accuracy of 87.91 percent. We evaluated EfficientNet classifiers using metrics that take the high-class imbalance into account. Our findings indicate that increased model complexity does not always imply improved classification performance. The best performance arose with intermediate complexity models, such as EfficientNet B4 and B5. The high classification scores resulted from many factors such as resolution scaling, data enhancement, noise removal, successful transfer learning of ImageNet weights, and fine-tuning [70–72]. Another discovery was that certain classes of skin cancer worked better at generalization than others using Confusion Matrices.

Introduction: One of the major problems of preterm neonates is immature alimentation. This may lead to inadequate weight gain, higher chances of sepsis and increased mortality. Positioning during and after feeding affects nutritional tolerance. Kangaroo Mother Care (KMC) is a method of skin-to-skin contact between mother and neonate, claimed to improve infant outcomes. Aim: To compare prone and Kangaroo Mother Care positioning of preterm neonates of 28-32 weeks gestational age during orogastric tube feeding. Materials and Methods: The study was a single-centre Institution-based, non randomised cross-over clinical study, carried out at Sick Newborn Care Unit and Neonatal Intensive Care Unit (NICU), Department of Paediatrics, R.G. Kar Medical College and Hospital, Kolkata, India, from April 2020 to March 2021. The studied parameters included gastric residual volume (three hours postprandial), vital signs like respiratory rate, heart rate, SpO2 level, body temperature, Capillary Blood Glucose (CBG), also comfort scores using a comfort scale. Total 110 preterm neonates of 28-32 weeks gestational age were sampled as per inclusion criteria and divided into two groups. Each group was fed by orogastric tube feeding in its respective position, in which they were kept for three hours. Vital signs, comfort scores and gastric residual volume were re-assessed. Groups were crossed over on the next day. Statistical analysis was done by t-test. Results: Of the total 110 neonates, KMC sample and prone position sample were compared after three hours. Heart rate was 147.5±4.3 and 151.08±9.1 beats per minute and respiratory rate 52.8±2.9 and 55.6±4.9 cycles per minute, which were lower in KMC than in prone position. There was better glycaemic control {n=107 (97.27) and 80 (72.73) mg/dL}, higher comfort scores (11.2±1.1 and 10.1±2.0) and minimal to negligible gastric residuals (0.03±0.05 mL and 0.13±0.12 mL) in KMC position, when compared to prone position, respectively. Conclusion: Kangaroo mother care produced more stable physiological indices, and was more comfortable for preterm neonates and resulted in better feeding, absorption and metabolism.

تناولت الدراسة الأسباب والعوامل التي أدت الى اندلاع الحركات الاحتجاجية في السودان سلميةً كانت أم عنيفةً، منذ استقلال السودان في العام 1956م وحتى ديسمبر 2018. وتنبع أهمية الدراسة من أنها أتت في مدة كثرت فيها الاحتجاجات عالمياً، إقليمياً ومحلياً، مما يستدعي تحليل أسبابها ونتائجها. وترمي الدراسة الي التعرف على دور الاحتجاجات في إحداث التحولات السياسية والاجتماعية بالسودان، بجانب تحديد العوامل التي ساعدت في نجاح أو فشل الحكومات التي أفرزتها تلك الاحتجاجات مع التركيز على تحديات حكومة ثورة 2018 م في تحقيق الأهداف التي اندلعت الثورة من أجلها. أهم نتائج الدراسة أن احتجاجات ديسمبر 2018 م تعد أكبر الاحتجاجات التي شهدها السودان وكان قوامها الشباب والنساء وكانت مطالبها قوميةً وشاملةً، غير أن التحديات التي تمر بها الحكومة الانتقالية جديةٌ وكبيرةٌ. ويرجع ذلك الى الفرق الشاسع بين طموحات الثوار وحقائق الأمر الواقع، فواقعياً لا يعد إصلاح الاقتصاد والسياسة والوضع الاجتماعي شأناً يسيراً أو يخص السودان فحسب، بل إن التدخلات الخارجية لا تقل أهميةً عن تفاعلات الداخل. لكن تظل التحولات المنشودة مرهونةً بمقدرة القوى الفاعلة على تخطي الصراعات الداخلية وتنظيم صفوفها للخروج من الوضع الفوضوي الراهن. وتوصي الدراسة باستيعاب الثوار في منظوماتٍ سياسيةٍ لإحداث التحول المدني الديمقراطي.

Thirteen insecticides- Stake 40WV (triazophos), Polo 500SC (diafenthiuron), Actara 25WG (thiamethoxam), Chlorfenapyr 36SC (chlorfenapyr), Maximal 60WG (nitenpyram + pymetrozine), Crown 20SL, Lescenta 80WG (fipronil + imidacloprid), Fyfanon 57EC (malathion), Talstar 10EC (bifenthrin) Momentum 50WG (nitenpyram + chlorfenapyr), Jozer 202SL (imidacloprid + acetamaprid), Tresta 20SC (clothianidin) and Closer 240SC (sulfoxaflor)- were evaluated for efficacy in a controlled mango nursery experiment against an active infestation of Scirtothrips dorsalis at the Mango Research Institute, Multan during 2018 and 2019. The data was recorded before the treatments were applied, then 24, 72, 168 h after treatment. Treatments with percent mortality greater than 70 % were considered to be effective controls. Percent mortality was 74.14 % for chlorfenapyr, 70.58 % for Momentum, and 70.51 % for Crown at post-treatment on an cumulative average of 24, 72 and 168 h of both the study years. Medium percent mortality was; 69.52 % for Jazor; 59.59 % for Maximal; 57.38 % for Actara; and 45.11 for Lescenta. All other treatments had percent mortality estimates of less than 30 %. It is concluded that chlorfenapyr, Momentum and Crown are suggested to be used on mango nursery against S. dorsalis for better management since among the treatments in the trial efficacious control was found at 24, 72 and 168 h post-treatment.

Abstract A finite-difference time-domain method is developed for studying the plasmon enhancement of light absorption from vertically aligned GaAs nanowire arrays decorated with Au nanoparticles. Vertically aligned GaAs nanowires with a length of 1 µm, a diameter of 100 nm and a periodicity of 165–500 nm are functionalized with Au nanoparticles with a diameter between 30 and 60 nm decorated in the sidewall of the nanowires. The results show that the metal nanoparticles can improve the absorption efficiency through their plasmonic resonances, most significantly within the near-bandgap edge of GaAs. By optimizing the nanoparticle parameters, an absorption enhancement of almost 35% at 800 nm wavelength is achieved. The latter increases the chance of generating more electron–hole pairs, which leads to an increase in the overall efficiency of the solar cell. The proposed structure emerges as a promising material combination for high-efficiency solar cells.

Purpose Computerized medical imaging processing assists neurosurgeons to localize tumours precisely. It plays a key role in recent image-guided neurosurgery. Hence, we developed a new open-source toolkit, namely Slicer-DeepSeg, for efficient and automatic brain tumour segmentation based on deep learning methodologies for aiding clinical brain research. Methods Our developed toolkit consists of three main components. First, Slicer-DeepSeg extends the 3D Slicer application and thus provides support for multiple data input/ output data formats and 3D visualization libraries. Second, Slicer core modules offer powerful image processing and analysis utilities. Third, the Slicer-DeepSeg extension provides a customized GUI for brain tumour segmentation using deep learning-based methods. Results The developed Slicer- DeepSeg was validated using a public dataset of high-grade glioma patients. The results showed that our proposed platform’s performance considerably outperforms other 3D Slicer cloud-based approaches. Conclusions Developed Slicer-DeepSeg allows the development of novel AIassisted medical applications in neurosurgery. Moreover, it can enhance the outcomes of computer-aided diagnosis of brain tumours. Open-source Slicer-DeepSeg is available at github.com/razeineldin/Slicer-DeepSeg.