Evaluation Of Feasibility Research Articles

Navigating the virtual restaurant frontier: motivations and challenges for restaurateurs in post-pandemic era

ABSTRACT This study explores the motivations and challenges steering restaurateurs toward the operation of virtual restaurants in post-pandemic Malaysia. With a dual objective of furnishing actionable guidance for current and prospective virtual restaurant entrepreneurs and proposing recommendations for stakeholders like SME Trade Associations, financial institutions, and government agencies, the research extracts qualitative insights from semi-structured interviews with 31 restaurant operators. Distinct motivations, including financial considerations, capitalization on pandemic-induced market shifts, procedural simplification, reliance on supportive networks, and learning from past physical restaurant setbacks, are identified. Correspondingly, challenges such as high overhead costs, limited visibility, unpredictable circumstances, and operational inefficiencies are unveiled. The study harmonizes both motivations and challenges to offer a practical framework, facilitating the evaluation of virtual restaurant feasibility and sustainability. These findings hold significant implications for fostering the adoption of virtual restaurants in post-pandemic Malaysia, presenting a comprehensive guide for restaurateurs navigating the evolving landscape.

A low-carbon evaluation framework for regional power systems

With the escalating challenges of climate change and the imperative for carbon neutrality, evaluating the carbon footprint of regional power systems becomes crucial. To address this issue, a low-carbon evaluation framework for regional power systems is developed. First, this study identifies the fundamental requirements that the index system for the low-carbon power system should follow and specifies the general direction for the index system’s creation. Second, an evaluation model for carbon reduction ability is proposed by considering generation side, grid side and load side of the power system. Then, a comparative evaluation model for the carbon reduction capability of multi-regional power systems is proposed to spatiotemporally compare the carbon reduction capability of different power systems. Next, a quantification method for the weights of low-carbon evaluation indicators is established based on the power system simulation of multi-scenario scheduling and index sensitivity analysis method. Finally, a low-carbon comprehensive score for regional power systems is created by combining the evaluation results of the system’s carbon reduction capacity with index weights. The practical research results in a region of Zhejiang province in China demonstrate that the proposed model can provide a reasonable and feasible evaluation plan for the low-carbon construction of regional power systems.

Development and Feasibility Evaluation of Smart Cancer Care 2.0 Based on Patient-Reported Outcomes for Post-Discharge Management of Patients with Cancer.

A "Smart Cancer Care" platform that integrates patient-reported outcomes (PROs) with management has been established in Korea. This study focused on improving health behaviors and connecting patients to welfare services by introducing and assessing the feasibility of "Smart Cancer Care 2.0," an enhanced version designed for monitoring complications post-cancer treatment. Smart Cancer Care 2.0 was developed by conducting a literature review and consulting with expert panels to identify symptoms or variables requiring monitoring and management guidelines based on the treatment type. Qualitative and quantitative surveys were conducted to assess the feasibility of the app and web system based on the experiences of patients with cancer and healthcare workers. A total of 81 symptoms or variables (chemotherapy-, surgery-, radiotherapy-, rehabilitation-, and health management-related) were selected for management in Smart Cancer Care 2.0. PROs for these symptoms were basically categorized into three severity grades: (1) preventive management, (2) self-treatment, and (3) consultation with a healthcare worker or visit to a healthcare institution. The overall mean scores in the feasibility evaluation by patients and healthcare workers were 3.83 and 3.90 points, respectively, indicating high usefulness. Smart Cancer Care 2.0 leverages the existing ICT-based platform, Smart Cancer Care, and further includes health behaviors and welfare services. Smart Cancer Care 2.0 may play a crucial role in establishing a comprehensive post-discharge management system for patients with cancer as it provides suitable interventions based on patients' responses and allows the regularly collected PROs to be easily viewed for streamlined care.

A grey wolf optimization algorithm for solving partial destructive disassembly line balancing problem consider feasibility evaluation and noise pollution

Partial destructive disassembly (PDD) is a crucial tool for enhancing efficiency and reducing disassembly costs when recycling complex end-of-life (EOL) products. Evaluating the feasibility of PDD is crucial for determining its implementation. However, the existing partial destructive disassembly line balancing (PDDLB) problem prioritizes profitability and randomly selects components for destructive, disregarding the feasibility of PDD and the noise pollution resulting from destructive operations. To address this concern, this paper introduces the integration of feasibility evaluation and noise considerations into the PDDLB problem for the first time. Subsequently, a mathematical model is established for the PDDLB problem, aiming to minimize disassembly costs, achieve smoothness balance, minimize the number of stations, and mitigate the adverse effects of noise. Then, an improved grey wolf optimization algorithm (IGWOA) considering feasibility evaluation and noise limitations is developed. It non-linearizes the convergence factor to enhance accuracy in the search for optimality, introduces a Lévy flight operation to further expand the search solution space, and incorporates an interference factor to prevent local optimality. In addition, the superiority of the proposed algorithm in solving different cases is verified by comparing five algorithms for the 25-task example and seven algorithms for the 52-task example in the latest literature. Finally, the proposed method is applied to a real engine case. The obtained results are compared with several classical Swarm Intelligence methods. The comparison results show that IGWOA has advantages due to other group intelligence methods in solving small, medium, and large-scale example. Moreover, the disassembly cost is comparatively low.

Laying the Groundwork: A Pilot Study Exploring Improved Endometriosis Management Strategies in Primary Healthcare.

To evaluate if a brief educational intervention for primary health care staff regarding endometriosis gives sustainable knowledge of endometriosis symptoms and if a brief questionnaire for women seeking care for common symptoms is feasible in the Swedish primary care context. Pilot study. 3 primary care centres (PCCs) in Sweden. Exploring knowledge among staff about endometriosis at baseline and 3 months after an information workshop. Evaluation of feasibility of a brief questionnaire for women seeking care for common symptoms For PCC personnel: knowledge about endometriosis at baseline and after 3 months. For patient questionnaire: whether adequate, understandable, acceptable, and feasible. Females in primary care centre waiting room, and staff members at participating PCCs. The knowledge level of endometriosis was improved or sustained after 3 months compared to baseline among staff at PCCs. Over 90% of the patients stated that the questionnaire was adequate, understandable, acceptable, and feasible. We found that an educational programme improved the staff's knowledge about endometriosis. The programme together with the patient questionnaire could be a way to enhance knowledge about endometriosis among PCCs. This combined effort might facilitate earlier detection and treatment of women with endometriosis.

Feasibility evaluation of near dissolved organic matter microfiltration (NDOM MF) for the efficient removal of microplastics in the water treatment process

Microfiltration (MF) using membranes with a mean pore size smaller than 0.45 μm has generally been used for particle removal from water, given that materials larger and smaller than 0.45 μm are regarded as particulates and dissolved organic matter (DOM), respectively. It is also the case for removing small-size microplastics (MPs). However, given their sizes (ca. 1 μm), there is room for further improvement of the productivity (i.e., water flux) in the pore size range of 0.45–1 μm on the condition that the removal rate is maintained. With this in mind, MF's water flux and removal rate were tested using seven different MF membranes, and the right pore, with the size of 0.8 μm, was found for MP removal, which is called near DOM (NDOM) MF. In the filtration test using polystyrene surrogate beads with an average particle diameter of 1.20 μm, NDOM MF exhibited a 1.7 to 13 times higher permeate flux than the conventional MF using 0.1, 0.2, and 0.45 μm membranes while maintaining a higher removal rate than 2 log. The excellent removal rate of the NDOM MF was attributable to the following three factors: (1) smaller mean pore size than the average particle diameter, (2) particle screening effect enhanced by the secondary layer formed by surface deposition, and (3) symmetric sublayer structure favorable for capturing penetrated particles. Furthermore, the outstanding filtration performance also appeared in a low-temperature (<10 °C) process, demonstrating that NDOM MF is feasible independently of temperature. Additionally, in constant flux filtration, NDOM MF demonstrated the long-term feasibility by lowering the transmembrane pressure and specific filtration energy by more than 2 times.

Thermodynamic Feasibility Evaluation of Alkaline Thermal Treatment Process for Hydrogen Production and Carbon Capture from Biomass by Process Modeling

Hydrogen is attracting attention as a low-carbon fuel. In particular, economical hydrogen production technologies without carbon emissions are gaining increasing attention. Recently, alkaline thermal treatment (ATT) has been proposed to reduce carbon emissions by capturing carbon in its solid phase during hydrogen production. By adding an alkali catalyst to the conventional thermochemical hydrogen production reaction, ATT enables carbon capture through the reaction of an alkali catalyst and carbon. In this study, a thermodynamic feasibility evaluation was carried out, and the effects of the process conditions for ATT with wheat straw grass (WSG) as biomass were investigated using Aspen Plus software V12.1. First, an ATT process model was developed, and basic thermodynamic equilibrium compositions were obtained in various conditions. Then, the effects of the process parameters of the reactor temperature and the mass ratio of NaOH/WSG (alkali/biomass, A/B value) were analyzed. Finally, the product gas compositions, process efficiency, and amount of carbon capture were evaluated. The results showed that the ATT process could be an efficient hydrogen production process with carbon capture, and the optimal process conditions were a reactor temperature of 800 °C, an A/B value of three, and a flow rate of steam of 6.9 × 10−5 L/min. Under these conditions, the maximum efficiency and the amount of carbon dioxide captured were 56.9% and 28.41 mmol/g WSG, respectively.

Development of consensus quality indicators for cancer supportive care: a Delphi study and pilot testing

BackgroundHigh quality supportive care is fundamental to achieve optimal health outcomes for people affected by cancer. Use of quality indicators provides comparative information for monitoring, management, and improvement of care within and across healthcare systems. The aim of this Australian study was to develop and test a minimum viable set of cancer supportive care quality indicators that would be feasible to implement and generate usable data for policy and practice.MethodsA two-round, modified reactive Delphi process was employed firstto develop the proposed indicators. Participants with expertise in cancer control in Australia, the United Kingdom, and Canada rated their level of agreement on a 7-point Likert scale against criteria assessing the importance, feasibility, and usability of proposed indicators. Relative response frequencies were assessed against pre-specified consensus criteria and a ranking exercise, which delivered the list of proposed indicators. Draft indicators were then presented to a purposive sample of clinicial and health management staff via qualitative interviews at two acute care settings in Melbourne, Australia for feedback regarding feasibility. Desktop audits of online published health service policy and practice descriptions were also conducted at participating acute care settings to confirm health service data availability and feasibility of collection to report against proposed indicators.ResultsSixteen quality indicators associated with the delivery of quality cancer supportive care in Australian acute healthcare settings met pre-specified criteria for inclusion. Indicators deemed ‘necessary’ were mapped and ranked across five key categories: Screening, Referrals, Data Management, Communication and Training, and Culturally Safe and Accessible Care. Testing confirmed indicators were viewed as feasible by clinical and health management staff, and desktop audits could provide a fast and reasonably effective method to assess general adherence and performance.ConclusionsThe development of quality indicators specific to cancer supportive care provides a strong framework for measurement and monitoring, service improvement, and practice change with the potential to improve health outcomes for people affected by cancer. Evaluation of implementation feasibility of these expert consensus generated quality indicators is recommended.

AIIMS ICU Rehabilitation (AIR): development and description of intervention for home rehabilitation of chronically ill tracheostomized patients

Background The paucity of state-supported rehabilitation for chronically ill patients with long-term tracheostomies has ramifications of prolonged hospital-stay, increased burden on acute-care resources, and nosocomial infections. Few interventions describe home rehabilitation of adult tracheostomized patients. Almost none involve stakeholders. This paper describes the All-India Institute of Medical Sciences (AIIMS) ICU rehabilitation (AIR) healthcare intervention developed to facilitate home rehabilitation of chronically ill tracheostomized patients. Methods The AIR intervention development was based on the experience-based codesign theory (EBCD). A core research-committee studied prevalent knowledge and gaps in the area. Patients-carer and health-care stakeholders’ experiences of barriers and facilitators to home care resulted in an intervention with interlinked components: family-carer training, equipment bank, m-health application, and follow-up, guided by the Medical Research Council (MRC) framework. Healthcare stakeholders (doctors, nurses, medical equipment vendors) and patient-carer dyads were engaged to gather experiences at various stages to form smaller codesign teams for each component. Multiple codesign meetings iteratively allowed refinement of the intervention over one year. The Template for Intervention Description and Replication (TIDieR) checklist was used to report the AIR intervention. Results The first component comprised a minimum of three bedside hands-on training sessions for carers relating to tracheostomy suction, catheter care, monitoring oxygenation, enteral feeding, skincare, and physiotherapy, buttressed by pictorial-books and videos embedded in a mobile-application. The second was an equipment-bank involving a rental-retrieval model. The third component was a novel m-health tool for two-way communication with the core group and community of other patient-carers in the project for follow-up and troubleshooting. Home visits on days 7 and 21 post-discharge assessed patient hygiene, nutrition, physiotherapy, and established contact with the nearest primary healthcare facility for the future. Conclusions Findings support the EBCD-based development using active feedback from stakeholders. Assessment of feasibility, process and effectiveness evaluation will follow.

Effect of High Salinity on Elemental Sulfur Autotrophic Partial Denitrification and Feasibility Evaluation of an Enhanced Strategy with Glycine Betaine Addition: Performance, Microorganisms, and Mechanisms

Effect of High Salinity on Elemental Sulfur Autotrophic Partial Denitrification and Feasibility Evaluation of an Enhanced Strategy with Glycine Betaine Addition: Performance, Microorganisms, and Mechanisms

From solution to structure: empowering inclusive cryo-EM with a pre-characterization pipeline for biological samples.

In addressing the challenges faced by laboratories and universities with limited (or no) cryo-electron microscopy (cryo-EM) infrastructure, the ESRF, in collaboration with the Grenoble Institute for Structural Biology (IBS), has implemented the cryo-EM Solution-to-Structure (SOS) pipeline. This inclusive process, spanning grid preparation to high-resolution data collection, covers single-particle analysis and cryo-electron tomography (cryo-ET). Accessible through a rolling access route, proposals undergo scientific merit and technical feasibility evaluations. Stringent feasibility criteria demand robust evidence of sample homogeneity. Two distinct entry points are offered: users can either submit purified protein samples for comprehensive processing or initiate the pipeline with already vitrified cryo-EM grids. The SOS pipeline integrates negative stain imaging (exclusive to protein samples) as a first quality step, followed by cryo-EM grid preparation, grid screening and preliminary data collection for single-particle analysis, or only the first two steps for cryo-ET. In both cases, if the screening steps are successfully completed, high-resolution data collection will be carried out using a Titan Krios microscope equipped with a latest-generation direct electron counting detector coupled to an energy filter. The SOS pipeline thus emerges as a comprehensive and efficient solution, further democratizing access to cryo-EM research.

Evaluation of Reliability and Financial Feasibility of Various EV Charging Station Layouts

As the popularity of electric vehicles (EVs) continues to rise, companies are increasingly focusing on expanding charging infrastructure to meet growing consumer demand. Despite attempts to design charging stations that align with distribution system requirements, ensuring reliable performance for EV charging ports remains a complex challenge. To address this issue, a unique design featuring 56 ports, comprising both uniform and non-uniform arrangements, has been introduced. These configurations underwent testing across distribution systems ranging from 50 to 500 kW. Reliability assessments were carried out using established standards for failure rate estimation and Monte Carlo simulations to evaluate port probability functions in terms of failure rate and reliability. By scrutinizing the failure rates of individual ports, a systematic evaluation method was established to gauge the overall performance of the charging station. The failure rate of the proposed 56-ported charging station was further assessed using the binomial distribution method. Also, cost estimation procedures were developed, taking into account the maintenance costs associated with the failure and success rates of individual ports for the proposed design. The research findings suggest that by enhancing port arrangement reliability and improving voltage stability, it is possible to achieve lower failure rates and maintenance costs, thereby enhancing overall system performance

Abstract 6185: Generative AI for virtual HE-staining of whole slide images of unstained breast cancer tissue

Abstract Introduction Hematoxylin and eosin (HE) is the standard stain used in histology to make tissue visible to the human eye by highlighting certain cellular and tissue structures, and it is a technique that is widely used in the diagnosis of cancer and other pathologies. Chemical staining, however, is irreversible, making the tissue unusable for subsequent measurements, such as spatial transcriptomics. Here we utilize generative AI method based on pix2pix image-to-image translation to generate virtual HE-staining for whole slide images (WSIs) acquired of unstained tissue with brightfield microscopy and perform a thorough histological evaluation for the feasibility in breast cancer diagnostics. Materials and Methods We optimized sample preparation and imaging setup for virtual staining purposes, and developed a custom generative adversarial network architecture for learning the virtual staining from paires samples of unstained and H&amp;E stained tissue. Here, we focus on the utility of virtual staining in breast cancer diagnostics, using a set of breast cancer samples for acquiring whole slide images from unstained tissue before H&amp;E staining and from reference H&amp;E stained tissue after chemical staining. Hold-out set of sample pairs are left for validation, allowing us to evaluate the virtual staining performance for a vast array of tissue components and to examine the potential shortcomings in staining reproduction. We use a comprehensive set of quantitative metrics both on pixel and object level to evaluate virtual staining quality. In addition, we perform thorough visual evaluation of histological feasibility by histology experts to examine the computational staining. Results We demonstrate that by careful optimization of both sample preparation and imaging workflow, as well as the computational methods, generative adversarial networks can be used for virtual staining of whole slide images of breast cancer tissue acquired from unstained tissue using regular bright field microscopy. We analyzed the virtual staining performance quantitatively and visually, and highlight the potential of the method through successful cases and demonstrate the applicability in breast cancer diagnostics, as well as discuss the challenges and shortcomings of virtual staining for clinical samples. Conclusions We demonstrate the potential of virtual HE staining for clinical histopathology of breast cancer tissue. Notably, our virtual staining based on generative AI shows promise towards more sustainable and streamlined sample processing and staining process in digital pathology. Citation Format: Leena Latonen, Umair Khan, Sonja Koivukoski, Johan Hartman, Pekka Ruusuvuori. Generative AI for virtual HE-staining of whole slide images of unstained breast cancer tissue [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6185.

A Pilot Feasibility Evaluation of a Heart Rate Variability Biofeedback App to Improve Self-Care in COVID-19 Healthcare Workers.

COVID-19 exacerbated burnout and mental health concerns among the healthcare workforce. Due to high work stress, demanding schedules made attuned eating behaviors a particularly challenging aspect of self-care for healthcare workers. This study aimed to examine the feasibility and acceptability of a heart rate variability biofeedback (HRVB) mobile app for improving well-being among healthcare workers reporting elevated disordered eating during COVID-19. We conducted a mixed methods pre-mid-post single-arm pilot feasibility trial (ClinicalTrials.gov NCT04921228). Deductive content analysis of participants' commentary generated qualitative themes. Linear mixed models were used to examine changes in pre- mid- to post-assessment scores on well-being outcomes. We consented 28 healthcare workers (25/89% female; 23/82% Non-Hispanic White; 22/79% nurses) to use and evaluate an HRVB mobile app. Of these, 25/89% fully enrolled by attending the app and device training; 23/82% were engaged in all elements of the protocol. Thirteen (52%) completed at least 10 min of HRVB on two-thirds or more study days. Most participants (18/75%) reported being likely or extremely likely to continue HRVB. Common barriers to engagement were busy schedules, fatigue, and technology difficulties. However, participants felt that HRVB helped them relax and connect better to their body's signals and experiences. Results suggested preliminary evidence of efficacy for improving interoceptive sensibility, mindful self-care, body appreciation, intuitive eating, stress, resilience, and disordered eating. HRVB has potential as a low-cost adjunct tool for enhancing well-being in healthcare workers through positively connecting to the body, especially during times of increased stress when attuned eating behavior becomes difficult to uphold.

Double-branched stent graft and four-stage deployment in total arch repair: safety and feasibility evaluation in porcine models.

The primary objective of this research was to evaluate the safety and feasibility of an innovative double-branched stent graft system employing four-stage deployment technology for aortic arch repair in porcine models. The double-branched stent graft system consisted of a proximal polyester artificial blood vessel, the main and double-branched stent grafts, and a delivery system. We utilized 12 healthy pigs as experimental animals (6 per group) in this study. Post-implantation, samples were collected at 90 and 180 days of follow-up. Preoperative, postoperative imaging, and intraoperative arterial blood gas analyses were performed. After euthanasia, the implanted product, surrounding tissue, and major organs were collected for pathological analysis. The technical success rate of stent graft implantation was 100% (12/12). All animals survived to the experimental end-point. Perioperative assessments showed intact stent grafts, and imaging features at the end of the follow-up revealed neither endoleak nor device migration. No major adverse cardiovascular events were observed in the postoperative follow-up. Pathological examination confirmed satisfactory biocompatibility of the stent graft. This innovative double-branched stent graft system with four-stage deployment technology was affirmed as a safe and feasible option for aortic arch repair in accordance with our preclinical evaluation with porcine models.

Thermodynamic feasibility evaluation of an innovative multigeneration system using biogas dry reforming integrated with a CCHP-desalination process

This work investigates a new method for developing systems that use a creative heat integration process that provides heating, cooling, fresh water and power. Specifically, the suggested framework operates by syngas obtained through the dry reforming process of biogas. Environmental considerations and decrease in thermodynamic irreversibility are main features of suggested system. The energy, exergy-related, environmental, and thermoeconomic properties of the suggested system are evaluated after it has been simulated using the Aspen HYSYS software. Results indicate 99,775.5 kW of net power, 10,880 kW of cooling power, and 141,800 kW of heating power. Also, the multigeneration scenario exhibits energy and exergy efficiencies of 58.06 % and 36.0 %, respectively. From the exergetic point of view, total exergy destruction rate is found at 493479 kW. The results of the environmental assessment show that the structure emits 0.27 kg of carbon dioxide per kWh while it is operating in the multigeneration mode. This value is contrasted with a reduction of 34.15 % in heat generation and a decrease of 69.11 % in power generation modes. According to the economic study, when the system functions under multigeneration conditions, the total equipment cost and the levelized cost of products are obtained at 59,536,233 $ and 0.029 $/kWh.

Quantifying BIM investment value: a systematic review

Purpose Perceived benefits of building information modelling (BIM) have been discussed for some time, but cost–benefit benchmarking has been inconsistent. The purpose of this paper is to investigate BIM feasibility and evaluate investment worth to elucidate and develop the current understanding of BIM merit. The aim of the study is to propose a research agenda towards a more holistic perspective of BIM use incorporating quantifying investment return. Design/methodology/approach An in-depth examination of research patterns has been conducted to identify challenges in the assessment of the investment value and return on investment (ROI) for BIM in the construction industry. A total of 75 research articles were considered for the final literature review. An evaluation of the literature is conducted using a combination of bibliometric analysis and systematic reviews. Findings This study, which analysed 75 articles, unveils key findings in quantifying BIM benefits, primarily through ROI calculation. Two major research gaps are identified: the absence of a standardized BIM ROI method and insufficient exploration of intangible benefits. Research focus varies across phases, emphasizing design and construction integration and exploring post-construction phases. The study categorizes quantifiable factors, including productivity, changes and rework reduction, requests for information reduction, schedule efficiency, safety, environmental sustainability and operations and facility management. These findings offer vital insights for researchers and practitioners, enhancing understanding of ’BIM’s financial benefits and signalling areas for further exploration in construction. Originality/value The ’study’s outcomes offer the latest insights for researchers and practitioners to create effective approaches for quantifying ’BIM’s financial benefits. Additionally, the proposed research agenda aims to improve the current limited understanding of BIM feasibility and investment worth evaluation. Results of the study could assist practitioners in overcoming limitations associated with BIM investment and economic evaluations in the construction industry.

Protocol: Prospective evaluation of feasibility, added value and satisfaction of remote digital self-assessment for mild cognitive impairment in routine care with the neotivCare app

IntroductionTimely diagnosis of mild cognitive impairment (MCI) in Alzheimer’s disease is crucial for early interventions, but its implementation is often challenging due to the complexity and time burden of required...

GC-CDSS: Personalized gastric cancer treatment recommendations system based on knowledge graph

BackgroundGastric cancer (GC) is one of the most common malignant tumors in the world, posing a serious threat to human health. Currently, gastric cancer treatment strategies emphasize a multidisciplinary team (MDT) consultation approach. However, there are numerous treatment guidelines and insights from clinical trials. The application of AI-based Clinical Decision Support System (CDSS) in tumor diagnosis and screening is increasing rapidly. ObjectiveThe purpose of this study is to (1) summarize the treatment decision process for GC according to the treatment guidelines in China, and then create a knowledge graph (KG) for GC, (2) based on aforementioned KG, built a CDSS and conducted an initial feasibility evaluation for the current system. MethodsFirstly, we summarized the decision-making process for treatment of GC. Then, we extracted relevant decision nodes and relationships and utilized Neo4j to create the KG. After obtaining the initial node features for building the graph embedding model, graph embedding algorithm, such as Node2Vec and GraphSAGE, were used to construct the GC-CDSS. At last, a retrospective cohort study was used to compare the consistency between GC-CDSS and MDT in treatment decision making. ResultsIn current study, we introduce a GC-CDSS, which is constructed based on Chinese GC treatment guidelines knowledge graph (KG). In the KG, we define four types of nodes and four types of relationships, and it comprise a total of 207 nodes and 300 relationships. Regarding GC-CDSS, the system is capable of providing dynamic and personalized diagnostic and treatment recommendations based on the patient's condition. Furthermore, a retrospective cohort study is conducted to compare GC-CDSS recommendations with those of the MDT group, the overall consistency rate of treatment recommendations between the auxiliary decision system and MDT team is 92.96%. ConclusionsWe construct a GC treatment support system, GC-CDSS, based on KG. The GC-CDSS may help oncologists make treatment decisions more efficient and promote standardization in primary healthcare settings.

Sexual quality of life and postoperative deep dyspareunia after vNOTES benign adnexal procedures.

This study aimed to investigate the impact of vNOTES on postoperative sexual dysfunction in patients undergoing adnexal procedures. We analyzed data from patients who underwent vNOTES adnexal surgeries for benign conditions between May 2020 and May 2023. The primary outcome was the presence of new postoperative deep dyspareunia (DD) or other sexual dysfunctions, which were assessed through a phone survey conducted 6 to 24 months after surgery. Secondary outcomes included surgical feasibility, operative times, complications rate, and postoperative pain evaluation. We included 103 patients for primary and secondary outcomes and 111 patients for secondary outcomes analysis only. Newly postoperative DD was reported by three patients (2.9%), remained present at 12 postoperative months in one case (1.0%), and spontaneously disappeared in two cases (1.9%) after four and 10 postoperative months, respectively. In the remaining 100 patients (97.1%), no new DD or other sexual function disorders were reported after surgery. vNOTES procedures were successfully performed in all cases, with a mean operative time of 38.2 ± 19.6 min and a conversion rate to conventional laparoscopy of 0.9%. No significant complication was observed. This study suggests a very limited risk of developing postoperative sexual dysfunction after vNOTES benign adnexal procedures.