Set Of Experts Research Articles

Some Similarity Measures on Generalized Interval-Valued Intuitionistic Fuzzy Soft Expert Sets and Their Applications in Medical Diagnosis

In recent years, the application of fuzzy sets has gained significant attraction in various fields, including medical diagnosis, due to their ability to manage uncertainties and imprecise information. This paper focuses on the comparative analysis of similarity measures within the realm of Generalized Interval-Valued Intuitionistic Fuzzy Soft Expert Sets (GIVIFSESs) and explores their application in the domain of medical diagnosis. Most of the important topics in fuzzy set theory are the similarity measures between the generalizations of fuzzy set theory. Similarity measures are a crucial tool which was used in data science. In this process, we measure how much the data sets are related and comparable. Measures of similarity give a numerical value that reveals the strength of associations between sets or sets of variables. In this paper, we initiate a new concept of generalized interval-valued intuitionistic fuzzy soft expert sets and their fundamental operations. This new concept is more flexible than existing concepts based on their algebraic definition. Unlike fuzzy sets, the concept of generalized interval-valued intuitionistic fuzzy soft expert sets is characterized by a degree of membership and degree of non-membership along with fuzzy set theory. The proposed methodology is validated through an empirical application in medical diagnosis, where (GIV-IFSESs) are employed to model the uncertainty and imprecision inherent in expert assessments. The selected similarity measures are then applied to quantify the degree of resemblance between different medical cases, facilitating a more informed decision-making process. We introduce several types of similarity measures on generalized interval-valued intuitionistic fuzzy soft expert sets. We also discuss a similarity measure of Type-I, Type-II, and Type-III for two (GIVIFSESs) and its application in medical diagnosis problems.

Implications of age and sex on the diagnostic yield of sudden arrhythmic death syndrome

Abstract Introduction Sudden arrhythmic death syndrome (SADS) refers to an unexplained sudden death with a negative autopsy. An inherited cardiac condition (ICC) may be diagnosed through familial clinical evaluation (FE) or post-mortem genetic testing (molecular autopsy [MA]) or both. We aimed to investigate the impact of age and sex of SADS decedents on the diagnostic yield and aetiology to facilitate a targeted approach to management. Methods Consecutive referrals to a single centre for FE only, MA only or both, following a SADS death were included. First-degree family members underwent comprehensive FE. A panel of 36 cardiac genes was sequenced for MA. A post-mortem diagnosis could be obtained by either FE, MA or both. A Bayesian framework for analysis was performed to identify associations. Results Seven-hundred-and-sixty SADS decedents (66% male; mean age 31±12 years) were investigated. The overall diagnostic yield for an ICC was 37% (32-42%) and 9% (6-12%) for FE and MA cohorts, respectively. In a subset where both MA and FE were performed the diagnostic yield was 45% (38-61%). For each year increase in age, the relative risk of an FE diagnosis of long QT syndrome (LQTS) or Catecholaminergic Polymorphic Ventricular Tachycardia (CPVT) versus remaining unexplained declined by 5.6% (RR 0.94 [0.91-0.98]) and by 11% (RR 0.89 [0.81-0.97]), respectively. Females were more likely to have a diagnosis compared with males by both FE (40% [34-45%] vs 36% [31-41%]) and MA (15% [10-21%] vs 6% [3-8%]). Females (8.1% [4.1-13.4%)], were more likely to be diagnosed with LQTS than males (1.2% [0.2-2.7%]) in the MA cohort. Conclusions After a SADS death, the diagnostic yield of comprehensive FE, MA or both in an expert setting can be up to 45%. Younger age of death is associated with greater likelihood of LQTS and CPVT diagnosis with the highest yield in children and adolescents. Female sex in SADS decedents is associated with a higher yield of LQTS in MA. These data highlight the relative utility of FE and MA depending on age and sex for determining underlying diagnoses following SADS deaths.

Cross-sectoral interventions to promote health-supportive urban environments

Abstract Background As dealing with the complexity of urban living conditions becomes more and more evident and urgent, it is fundamental to promote cross-sectoral interventions that allow cities to become more inclusive and supportive of health. The Emilia-Romagna region, Italy, has promoted a participatory initiative to structurally integrate health into urban planning tools, identifying a framework of tailored urban indicators linked to locally perceived population health issues. Methods Through internal discussion and systematic literature research, a set of urban planners, epidemiologists, and public health experts from regional offices, local health services, universities, and environmental protection agencies identified the urban and health dimensions most suitable for embedding population health into city planning. The result was summarised in a preliminary working paper, which included a matrix of associations between urban features and health dimensions framed according to the DPSEEA framework. Its applicability was then tested in a participatory process (March-May 2024) involving urban planners and public health departments of 7 different sized municipalities. Results A group of epidemiologists identified local-level computable indicators for the health dimensions already included in the matrix or added at request. Each municipality focused on specific topics based on local priorities: 3 groups assessing their already-approved urban plans and looking for computable urban indicators; the others integrating their under-construction plans with local health indicators. Conclusions The need for professional contamination and cross-sectoral interventions is significant. Epidemiological support is pivotal in integrating different professional languages and reading health data. The outputs of this experience will contribute to a technical document outlining how to incorporate health promotion into urban planning tools and practice while actively considering the local context. Key messages • Although the development of a common vocabulary can be difficult, multidisciplinary collaboration is essential in promoting a model for integrating health promotion into urban planning. • Local municipalities’ involvement in the experimentation can improve the model’s applicability by taking into account territorial specificities.

Key data: Children and families’ experiences of the SEND system

Expert sets out the key principles that planned Young Futures Hubs must adopt to be successful

How hubs can tackle violence

Expert sets out the key principles that planned Young Futures Hubs must adopt to be successful

5 principles of good SEND transition support

Expert sets out the key principles that planned Young Futures Hubs must adopt to be successful

Representation Learning for Sequential Volumetric Design Tasks

Abstract Volumetric design, also called massing design, is the first and critical step in professional building design which is sequential in nature. As the volumetric design process is complex, the underlying sequential design process en- codes valuable information for designers. Many efforts have been made to automatically generate reasonable volumetric designs, but the quality of the generated design solutions varies, and evaluating a design solution requires either a prohibitively comprehensive set of metrics or expensive human expertise. While previous approaches focused on learning only the final design instead of sequential design tasks, we propose to encode the design knowledge from a collection of expert or high-performing design sequences and extract useful representations using transformer-based models. Later we propose to utilize the learned representations for crucial downstream applications such as design preference evaluation and procedural design generation. We develop the preference model by estimating the density of the learned representations whereas we train an autoregressive transformer model for sequential design generation. We demonstrate our ideas by leveraging a novel dataset of thousands of sequential volumetric designs. Our preference model can compare two arbitrarily given design sequences and is almost 90% accurate in evaluation against random design sequences. Our autoregressive model is also capable of autocompleting a volumetric design sequence from a partial design sequence.

Сравнение схожести интеллект-карт в задачах маркетингового анализа

High competition requires new methods, tools, and technologies for implementing marketing efforts. Mind maps represent marketing information in a compact way, which facilitates classification and visualization of the marketing phenomenon under analysis. The method of text analysis can be applied to marketing research because mind maps that represent marketing information are a structured text; such an approach makes it possible to subject mind maps to linguistic processing. This research combined the conventional semantic analysis with comparing mind maps as a method of semantic-graph analysis. Initial marketing data were converted into a structured graph of lexical units, which were them compared pairwise to calculate similarity, taking into account the structural-multiple approach. The methods of semantic text analysis proved applicable to marketing data and effective in extracting additional information from a set of heterogeneous sources or different experts. Text analysis tools demonstrated a good potential for broadening the rage of marketing research methods.

Time-series bidirectional adjustable N-soft expert MABAC method and its application for multi-attribute group decision-making

In hybrid models of soft expert sets, experts express only agreed or disagreed opinions about existing grades. This paper proposes a time-series bidirectional adjustable N-soft expert set model to address the shortcomings of existing models that cannot adjust existing grades to a more reasonable state or describe decision problems involving different times. Firstly, this model can explain the experts’ uncertain opinions and make positive or negative adjustments about existing grades. Secondly, the model contains information about time, describes dynamic multi-attribute group decision-making problems and explores objects’ changes and developments over time. And some related operations and propositions are derived. In addition, a new method called the bidirectional adjustable N-soft expert MABAC (multi-attributive border approximation area comparison) is proposed. On the one hand, the proposed method uses deviation maximizing and exponential decay methods to determine the time weights, ensuring the reliability of the time weights. On the other hand, it ranks objects based on their distances from an approximate boundary region, limiting the unconditional compensation among attribute values. Finally, this paper presents an example to verify its effectiveness and reliability by results analysis, sensitivity analysis, and comparison analysis.

Effect of computer aided detection device on the adenoma detection rate and serrated detection rate among trainee fellows.

The utilization of artificial intelligence (AI) with computer-aided detection (CADe) has the potential to increase the adenoma detection rate (ADR) by up to 30% in expert settings and specialized centers. The impact of CADe on serrated polyp detection rates (SDR) and academic trainees ADR & SDR remains underexplored. We aim to investigate the effect of CADe on ADR and SDR at an academic center with various levels of providers' experience. A single-center retrospective analysis was conducted on asymptomatic patients between the ages of 45 and 75 who underwent screening colonoscopy. Colonoscopy reports were reviewed for 3 months prior to the introduction of GI Genius™ (Medtronic, USA) and 3 months after its implementation. The primary outcome was ADR and SDR with and without CADe. Totally 658 colonoscopies were eligible for analysis. CADe resulted in statistically significant improvement in SDR from 8.92% to 14.1% (P = 0.037). The (ADR + SDR) with CADe and without CADe was 58% and 55.1%, respectively (P = 0.46). Average colonoscopy (CSC) withdrawal time was 17.33 min (SD 10) with the device compared with 17.35 min (SD 9) without the device (P = 0.98). In this study, GI Genius™ was associated with a statistically significant increase in SDR alone, but not in ADR or (ADR + SDR), likely secondary to the more elusive nature of serrated polyps compared to adenomatous polyps. The use of CADe did not affect withdrawal time.

A new global hybrid map of annual herbaceous cropland at a 500 m resolution for the year 2019

Abstract The global spatial extent of croplands is a crucial input to global and regional agricultural monitoring and modeling systems. Although many new remotely-sensed products are now appearing due to recent advances in the spatial and temporal resolution of satellite sensors, there are still issues with these products that are related to the definition of cropland used and the accuracies of these maps, particularly when examined spatially. To address the needs of the agricultural monitoring community, here we have created a hybrid map of global cropland extent at a 500 m resolution by fusing two of the latest high resolution remotely-sensed cropland products: the European Space Agency’s WorldCereal and the cropland layer from the University of Maryland. We aggregated the two products to a common resolution of 500 m to produce percentage cropland and compared them spatially, calculating two kinds of disagreement: density disagreement, where the two maps differ by more than 80%, and absence-presence of cropland disagreement, where one map indicates the presence of cropland while the other does not. Based on these disagreements, we selected continuous areas of disagreement, referred to in the paper as hotspots of disagreement, for manual correction by experts using the Geo-Wiki land cover application. The hybrid map was then validated using a stratified random sample based on the disagreement layer, where the sample was visually interpreted by a different set of experts using Geo-Wiki. The results show that the hybrid product improves upon the overall accuracy statistics in the areas where the underlying cropland layer from the University of Maryland was improved with the WorldCereal product, but more importantly, it represents an improved spatially explicit cropland mask for early warning and food security assessment purposes.

European Neuroendocrine Tumor Society (ENETS) 2024 guidance paper for the management of well-differentiated small intestine neuroendocrine tumours.

Both the incidence and prevalence of well-differentiated neuroendocrine tumours from the small intestine (Si-NET) are gradually increasing. Most patients have non-functioning tumours with subtle GI symptoms and tumours are often discovered incidentally by endoscopy or at advanced disease stages by imaging depicting mesenteric lymph node and /or liver metastases while around 30% of the patients present with symptoms of the carcinoid syndrome. Adequate biochemical assessment and staging including functional imaging is crucial for treatment-related decision-making that should take place in an expert multidisciplinary team setting. Preferably, patients should be referred to specialised ENETS Centres of Excellence or centres of high expertise in the field. This guidance paper provides the current evidence and best knowledge for the management of Si-NET grade (G) 1-3 following 10 key questions of practical relevance for the diagnostic and therapeutic decision making.

Online Learning With Uncertain Feedback Graphs.

Online learning with expert advice is widely used in various machine learning tasks. It considers the problem where a learner chooses one from a set of experts to take advice and make a decision. In many learning problems, experts may be related, henceforth the learner can observe the losses associated with a subset of experts that are related to the chosen one. In this context, the relationship among experts can be captured by a feedback graph, which can be used to assist the learner's decision-making. However, in practice, the nominal feedback graph often entails uncertainties, which renders it impossible to reveal the actual relationship among experts. To cope with this challenge, the present work studies various cases of potential uncertainties and develops novel online learning algorithms to deal with uncertainties while making use of the uncertain feedback graph. The proposed algorithms are proved to enjoy sublinear regret under mild conditions. Experiments on real datasets are presented to demonstrate the effectiveness of the novel algorithms.

Toward a community-driven approach to urban data-driven governance

Drawing from communication infrastructure theory, I propose a methodological and analytical intervention for the smart city and related initiatives: a community-driven approach to urban data-driven governance. This approach contends that data-related actors increasingly act as key storytelling agents within urban governance, given the rise of datafication. Moreover, it emphasizes the importance of an alternative storytelling network, positing the local storytelling network as a key—yet often minimally visible—set of experts and storytellers that can activate data-driven change and overcome extant gaps in dominant, “limited” versions of the smart city. As such, I spotlight two counterdata projects as prototypes for this intervention. In all, I argue it is imperative that urban governance explores this framework to incorporate, and design with, a wider range of local actors and knowledge in mind: not only to address critiques but, more so, to build more inclusive models in the public interest.

UK net-zero policy design – from optimisation to robustness

The need to deal with the deep uncertainty and system complexity associated to Net-Zero pathways, especially those relying on emergent greenhouse gas removal (GGR) technologies, has resulted in a growing body of literature on alternative decision-support approaches. Exploratory modelling, and specifically Robust Decision Making (RDM), are potential approaches capable of addressing these challenges: by exploring a wide range of conceivable futures, they explicitly embrace deep uncertainties while seeking to reduce system vulnerabilities. However, though RDM methods have been well documented, there is little insight as to how such approach might be integrated into Net-Zero policy design processes. By means of a workshop (n=17) and interviews (n=13) with the UK climate policy and energy modelling communities, this contribution provides insights into the role and potential of RDM in explicitly dealing with the deep uncertainties that pervade in the establishment of a 60–100 MtCO2 UK GGR sector within three decades. The consultation process revealed that there is an appetite from the decision-making and analytical communities in integrating exploratory modelling concepts into UK policy design processes. It is recommended that to bridge the gap between theoretical RDM constructs and their broader adoption, the analytical process should include a broader set of disciplines and expertise. Specifically for the modelling community, this work suggests that in-use computational models should be adapted, rather than new tools developed. Key challenges also arise from the time and resources required, suggesting small scale place-based pilots could promote the acceptability and foster the adoption of the RDM methodology.

SAMI: an M-Health application to telemonitor intelligibility and speech disorder severity in head and neck cancers.

Perceptual measures, such as intelligibility and speech disorder severity, are widely used in the clinical assessment of speech disorders in patients treated for oral or oropharyngeal cancer. Despite their widespread usage, these measures are known to be subjective and hard to reproduce. Therefore, an M-Health assessment based on an automatic prediction has been seen as a more robust and reliable alternative. Despite recent progress, these automatic approaches still remain somewhat theoretical, and a need to implement them in real clinical practice rises. Hence, in the present work we introduce SAMI, a clinical mobile application used to predict speech intelligibility and disorder severity as well as to monitor patient progress on these measures over time. The first part of this work illustrates the design and development of the systems supported by SAMI. Here, we show how deep neural speaker embeddings are used to automatically regress speech disorder measurements (intelligibility and severity), as well as the training and validation of the system on a French corpus of head and neck cancer. Furthermore, we also test our model on a secondary corpus recorded in real clinical conditions. The second part details the results obtained from the deployment of our system in a real clinical environment, over the course of several weeks. In this section, the results obtained with SAMI are compared to an a posteriori perceptual evaluation, conducted by a set of experts on the new recorded data. The comparison suggests a high correlation and a low error between the perceptual and automatic evaluations, validating the clinical usage of the proposed application.

DEVELOPMENT OF «SCIENCE OF SELF-IMPROVEMENT» AT THE INTERNET THROUGH THE PRISM OF ECONOMIC SECURITY OF THE INDIVIDUAL

The WEB.2.0 era, which opened up almost universal access to the Internet for every person, entailed the formation of a gigantic set of self-proclaimed experts in various branches of knowledge. During the epidemic, the amount of time spent using the Internet and Internet applications significantly increased, which was a kind of klondike, and served as an incentive for the development of the «science of self-improvement», the promotion of methods based on human emotions of fears, the desire for speedy enrichment, healing, improvement. The article presents the positive and negative aspects of social media. Based on his own observations, the author compiled a brief description of persons who actively manifest themselves in the Internet space (bloggers, coaches, coaches), in the context of ensuring the economic security of the individual, and also presents a typical algorithm of actions of persons who implement trainings, marathons and courses in the Internet space, regardless of the field of educational activities

Constructing and validating authentic assessments: the case of a new technology-based assessment of economic literacy

BackgroundAuthentic situations are considered a source of learning due to their real world relevance. This can encourage learners to acquire new knowledge. Increasing digitisation and associated resources, such as professional development opportunities for teachers, technology tools, or digital equipment for schools enable the development and implementation of authentic assessments. The basic academic principles for acquiring economic literacy are already provided in lower secondary school. This article examines, using the example of a new authentic technology-based assessment (TBA)—Economic Literacy—Assessing the Status Quo in Grade 8 (ECON 2022) -, the processes involved in constructing a TBA. The purpose is to develop a curricular valid measurement instrument for surveying the current state of economic literacy in the 8th grade of a German federal state. This study explores which economic competencies students—typically between 14 and 15 years of age—possess in Grade 8, and what level of competence can therefore be expected of them at the beginning of a vocational training programme. The assessment is geared toward the curriculum of the subject of economics and is based on a domain model. This article presents the background and construction process for the development of ECON 2022 as a TBA.MethodsTo check the validity of test construction with a focus on the implementation of the authentic assessment and an analysis of difficulty-generating characteristics, the ECON 2022 test items were validated with an expert survey (N = 25). The two-stage data analysis comprised a descriptive quantifying analysis of the rating from the difficulty-generating characteristics specificity, cognitive demand and modelling and the design criterion authenticity. A set of experts rated the criteria. The expert survey was then compared with a previously conducted rating by the research team. The analysis of free-text comments on individual items was carried out discursively and qualitatively by the research team. Both sources of information were used to adapt the test items to measured item difficulties from the field test. For this purpose, items of great difficulty were changed to slightly easier items. In this context, the paper focuses on two central research questions: - How does the authenticity of a test environment relate to difficulty-generating criteria at item level? - Does the authenticity of a test environment have an impact on test results?ResultsResults are as follows. (1) The ECON 2022 assessment offers an example of a test design in which the use of TBAs can support innovative and interactive item development. (2) Using the ECON 2022 assessment enabled the implementation of an assessment of economic literacy using authentic situations and the mapping of different facets of economic competence. (3) The validation study showed that the actual item difficulty did not correlate significantly with the authenticity of the assessment, and authenticity thus did not contribute to item difficulty.ConclusionThe results of the study show that we were successful in developing an authentic TBA in ECON 2022. ECON 2022 allows us to examine economic literacy in schools with a high degree of curricular validity and relevance and to analyse what level of competence and knowledge can be expected of students when they enter a vocational training occupation.

The role of multidisciplinary MS care teams in supporting lifestyle behaviour changes to optimise brain health among people living with MS: A qualitative exploration of clinician perspectives.

Healthcare professionals have an important role in advocating for the adoption of a brain-healthy lifestyle for optimal multiple sclerosis (MS) care. Nonetheless, studies to date have mainly focussed on the consumer perspective. Herein, we aimed to explore the current practices of how healthcare professionals support protective, lifestyle-related behaviour changes to optimise brain health among people living with MS (plwMS), and their perspectives of professional roles. Australian healthcare professionals were recruited via study advertisements, purposive and snowball sampling, to participate in an online, semi-structured and audio-recorded interview. Clinicians were eligible if they had a minimum of a tertiary Bachelor's degree and 12-months experience working with plwMS, access to the Internet and sufficient time to participant. An inductive, data-driven form of reflexive thematic analysis was undertaken before thematic categorisation of the quotes from transcripts. Data analysis was guided by the methods of Braun and Clark and the study's underpinnings drew on the constructs of the Social Cognitive Theory (SCT). Six physicians, 10 MS nurses, 18 allied health professionals, one exercise therapist and one alternative therapist were interviewed. Three primary themes encompassing the perceived role of healthcare professionals in supporting a brain-healthy lifestyle were identified: (1) the empowering role, (2) collaborative role and (3) communicative role. External factors/forces including time constraints, professional expertise, training and skill set, power dynamics, consumer readiness, health literacy, self-efficacy and motivation are at play, and affect how/when healthcare professionals may support behaviour change to optimise lifelong brain health for plwMS. Healthcare professionals recognise their critical role in encouraging and supporting the adoption of a brain-healthy lifestyle to optimise lifelong brain health for plwMS. However, discord is evident when they underestimate the complexity of translating knowledge of lifestyle-related behaviour change(s) into action. Greater awareness must be made in recognising and addressing the bidirectionality of external factors such as those in the SCT, that may influence how behaviour change occurs. Healthcare professionals volunteered to be interviewed as part of the data collection phase of this study.

Is blue light imaging without magnification satisfactory as screening for esophageal squamous cell carcinoma? Post-hoc analysis of multicenter randomized controlled trial.

Narrow light observation is currently recommended as an alternative to Lugol chromoendoscopy (LCE) to detect esophageal squamous cell carcinoma (ESCC). Studies revealed little difference in sensitivity between the two modalities in expert settings; however, these included small numbers of cases. We aimed to determine whether blue light imaging (BLI) without magnification is satisfactory for preventing misses of ESCC. This was a post-hoc analysis of a multicenter randomized controlled trial targeting patients at high risk of ESCC in expert settings. In this study, BLI without magnification followed by LCE was performed. The evaluation parameters included: (i) the diagnostic abilities of ESCC; (ii) the endoscopic characteristics of lesions with diagnostic differences between the two modalities; and (iii) the color difference between cancerous and noncancerous areas in BLI and LCE. This study identified ESCC in 49 of 699 cases. Of these cases, nine (18.4%) were missed by BLI but detected by LCE. In per-patient analysis, the sensitivity of BLI was lower than that of LCE following BLI (83.7% vs. 100.0%; P = 0.013), whereas the specificity and accuracy of BLI were higher (88.2% vs. 81.2%; P < 0.001 and 87.8% vs. 82.5%; P < 0.001, respectively). No significant endoscopic characteristics were identified, but the color difference was lower in BLI than in LCE (21.4 vs. 25.1; P = 0.003). LCE following BLI outperformed BLI in terms of sensitivity in patients with high-risk ESCC. Therefore, LCE, in addition to BLI, would still be required in screening esophagogastroduodenoscopy even by expert endoscopists.