Decision Support - Science topic

An active purpose of financial organizations is to preserve existing customers and accomplish imminent long-term ones. Bank marketing campaigns often depend on huge electronic data from a plethora of customers. Given the enormous and ever-growing data, it is not feasible for human analysts to procure interesting information and derive inferences fo...

This paper reviews challenges of relevance to the future development of Arctic sustainable shipping by considering future demands for vessel types, available alternative energy sources, and novel technologies. Results reveal the need to extend existing concept ship design methods to account for the holistic yet sustainable design of Arctic vessels....

Phosphorus (P) is a finite resource, and its environmental fate and transport is complex. With fertilizer prices expected to remain high for years and disruption to supply chains, there is a pressing need to recover and reuse P (primarily as fertilizer). Whether recovery is to occur from urban systems (e.g., human urine), agricultural soil (e.g., l...

Clinical decision support tools (DSTs), powered by Artificial Intelligence (AI), promise to improve clinicians' diagnostic and treatment decision-making. However, no AI model is always correct. DSTs must enable clinicians to validate each AI suggestion, convincing them to take the correct suggestions while rejecting its errors. While prior work oft...

Growing demand for renewable energy has resulted in expansion of energy infrastructure across sagebrush ecosystems of western North America. Geothermal power is an increasingly popular renewable energy source, especially within remote areas, but little is known about the impacts it may have on local wildlife populations. Investigations are warrante...

Background: Complex anterior skull base defects produced by resection of mass lesions vary in size and configuration and may be extensive. We analyzed the largest single-center series of midline craniofacial lesions extending intra- and extracranially. The study aims at the development of a predictive model for preoperative measurement of the risk...

Recent advances in machine learning may be leveraged by researchers in the context of agent-based modelling. With the help of surrogate models, machine learned models based on samples of a more complex agent-based model, computationally expensive evaluation methods such as sensitivity analysis and calibration may be supported and sped up. To explor...

Surgical scene understanding is a key prerequisite for contextaware decision support in the operating room. While deep learning-based approaches have already reached or even surpassed human performance in various fields, the task of surgical action recognition remains a major challenge. With this contribution, we are the first to investigate the co...

Automated truck platooning has become an increasingly popular research subject, and its applicability to highways is considered one of the earliest possible landing scenarios for automated driving. However, there is a lack of research regarding the combination of truck platooning technology and truck lane management strategy on multilane highways i...

Accurately determining the molecular subtypes of breast cancer is important for the prognosis of breast cancer patients and can guide treatment selection. In this study, we develop a deep learning-based model for predicting the molecular subtypes of breast cancer directly from the diagnostic mammography and ultrasound images. Multi-modal deep learn...

Envisaging an adequate IT/IS solution that can mitigate the employability problems is imperative because nowadays there is a high rate of unemployed graduates. Thus, the main goal of this systematic literature review (SLR) was to explore the application of data mining techniques in modeling employability and see how those techniques have been appli...

In today’s uncertain and competitive market, where manufacturing enterprises are subjected to increasingly shortened product lifecycles and frequent volume changes, reconfigurable manufacturing system (RMS) applications play significant roles in the success of the manufacturing industry. Despite the advantages offered by RMSs, achieving high effici...

Acute myeloid leukemia (AML) is a deadly hematological malignancy. Cellular morphology detection of bone marrow smears based on the French–American–British (FAB) classification system remains an essential criterion in the diagnosis of hematological malignancies. However, the diagnosis and discrimination of distinct FAB subtypes of AML obtained from...

Digital twins can facilitate high-fidelity representations of container terminals by applying various technologies and methods to better measure, understand, and improve operations. In this paper, a decision support system (DSS) based on digital twin and big data technologies is designed to demonstrate how real-time monitoring and an integrated dec...

Land-use changes remain a major source of terrestrial ecosystem carbon stock (TECS) change. However, existing studies estimating TECS change caused by land-use changes, considering the mixed land-use structure and its continuous structural changes in the land-use change model, are still absent. Our study first analyzed land-use changes during the y...

To deal with the uncertainty and ensure the sustainability of the manufacturing industry, we designed a multi criteria decision-making technique based on a list of unique operators for single-valued neutrosophic hesitant fuzzy rough (SV-NHFR) environments with a high confidence level. We show that, in contrast to the neutrosophic rough average and...

Efficient natural resource management prevents and reduces negative impacts, such as environmental damage, misappropriation of resources, and conflicts; several strategies can be leveraged to conserve, protect, and enhance natural resources. Multicriteria decision analysis (MCDA) is useful in providing solutions to addressing decision-choice proble...

Background: Intelligent artificial agents ('agents') have emerged in various domains of human society (healthcare, legal, social). Since using intelligent agents can lead to biases, a common proposed solution is to keep the human in the loop. Will this be enough to ensure unbiased decision making? Methods: To address this question, an experiment...

Extreme rainfall events cause diverse loss of life and economic losses. These disasters include flooding, landslides, and erosion. For these intense rainfall events, one can statistically estimate the time when a given rainfall volume will occur. Initially, this work estimated rainfall volumes for the mountainous region of Rio de Janeiro, and the f...

Solar photovoltaic (PV) irrigation is increasingly used in agriculture, driven by its low operation cost and virtually zero emissions, providing electricity access in rural areas. However, the high investment cost requires an optimal design. The objective of this work was to develop a user-friendly tool to optimally size a PV generator that satisfi...

Urban plazas provide opportunities for children to play, learn and explore. In particular, public art in urban plazas can be a medium to absorb more children. This research has developed the Inclusive Urban Plaza Design (IUPD) assessment tool, which complies with the principles and features of urban plaza design based on the children’s preferences,...

Nowadays, supermarkets and retail stores all use software systems with databases to store customer transactions. Over time, the volume of data is also increasing and it contributes a lot of hidden value in this data warehouse, mining data from historical transactions will find out the buying patterns and behavior of consumers, which can assist in i...

Background Identification of high-risk patients and individualized decision support based on objective criteria for rapid discharge after transcatheter aortic valve implantation (TAVI) are key requirements in the context of contemporary TAVI treatment. This study aimed to predict 30-day mortality following TAVI based on machine learning (ML) using...

Water scarcity and droughts are an increasing issue in many parts of the world. In the context of urban water systems, the transition to circularity may imply wastewater treatment and reuse. Planning and assessment of water reuse projects require decision-makers evaluating the cost and benefits of alternative scenarios. Manual or semi-automatic app...

Deep learning has achieved remarkably positive results and impacts on medical diagnostics in recent years. Due to its use in several proposals, deep learning has reached sufficient accuracy to implement; however, the algorithms are black boxes that are hard to understand, and model decisions are often made without reason or explanation. To reduce t...

Reforming systems in any sector is a complex task. There is a need to continually assess the changing landscape and, most importantly, the underlying momentum and direction of movement of the existing system before recommending changes that can, at best, hope to gently modulate that movement in the hope that over a period of time it moves closer an...

Introduction Despite the availability of effective, subsidised hepatitis B treatment, linkage to care and treatment rates remain very low globally. In Australia, specially trained primary care physicians (general practitioner, GPs) can prescribe hepatitis B treatment, however, most hepatitis B care occurs in specialist clinics. Increasing hepatitis...

The ability to explain why a machine learning model arrives at a particular prediction is crucial when used as decision support by human operators of critical systems. The provided explanations must be provably correct, and preferably without redundant information, called minimal explanations. In this paper, we aim at finding explanations for predi...

Dermatological conditions are a relevant health problem. Machine learning (ML) models are increasingly being applied to dermatology as a diagnostic decision support tool using image analysis, especially for skin cancer detection and disease classification. The objective of this study was to perform a prospective validation of an image analysis ML m...

Purpose of Review Standard DCIS management consists of surgery with consideration of adjuvant radiation and endocrine therapy. However, widespread recognition of the overdiagnosis and overtreatment burden in DCIS has led to a reevaluation of this standard. The purpose of this review is to summarize the foundational clinical trials in DCIS and to di...

Explainable AI is deemed essential for clinical applications as it allows rationalizing model predictions, helping to build trust between clinicians and automated decision support tools. We developed an inherently explainable AI model for the classification of acute myeloid leukemia subtypes from blood smears and found that high-attention cells ide...

Abstract Machine learning (ML) has been used in agricultural production as a decision support tool to get insights, monitor crops, and equip farmers with vital information on crop variety selection and field management throughout the crop growth cycle. Several approaches to machine learning have been used to help predict agricultural yields. This l...

Purpose: Currently, the choice of contralateral prophylactic mastectomy (CPM) for breast cancer patients is variable and controversial. Breast cancer patients must make complex and rapid decisions based on the benefits and risks of CPM. Although there are many qualitative studies on the decision-making experiences of breast cancer patients, there...

Cities are increasingly looking to become smarter and more resilient. Also, the use of computer vision takes a considerable place in the panoply of techniques and algorithms necessary for the 3D reconstruction of urban built environments. The models thus obtained make it possible to feed the logic of decision support and urban services thanks to th...

It is important to develop sustainable processes in materials science and manufacturing that are environmentally friendly. AI can play a significant role in decision support here as evident from our earlier research leading to tools developed using our proposed machine learning based approaches. Such tools served the purpose of computational estima...

Hybrid uncertainty based models are more useful than the individual components. Earlier soft sets and intuitionistic fuzzy sets were combined to form intuitionistic fuzzy soft sets (IFSS) which are rich potentials for solving decision-making problems. Dan et al. (2020) introduced the concept of an intuitionistic type 2 fuzzy set (IT2FS), which is a...

With data-driven optimization, this study investigates the sellers’ inventory replenishment and financial decisions, and lenders’ interest rate decisions in online retailing platforms. Moreover, we focus on the annual large-scale promotion, which requires massive capital in a short period. While scholars studying the data-driven inventory replenish...

Data from agency‐based inventory programs could be very useful for local fishery management if appropriately summarized and served, but data are often accessible to few. Fundamental management questions at regional and local scales center around resource status and trends, highlighting the need for decision support tools operating at multiple scale...

The paper describes the marketing mix modeling results for companies in nonfood retailing. The main objectives of the research are to demonstrate the viable way of making effective recommendations for optimizing the media strategy by modeling offline and online traffic to the stores based on econometric modeling and to develop a decision support sy...

Background The utility of routine extensive molecular profiling of pediatric tumors is a matter of debate due to the high number of genetic alterations of unknown significance or low evidence and the lack of standardized and personalized decision support methods. Digital drug assignment (DDA) is a novel computational method to prioritize treatment...

1 Поволжский государственный университет телекоммуникаций и информатики Аннотация Представлена оригинальная информационная система «ферма данных». Сегодня успешное применение алгоритмов искусственного интеллекта, прежде всего глубокого обучения на основе нейронных сетей (deep learning), практически полностью зависит от наличия данных. И чем больше...

The failure of sewage and drainage systems in Sub-Saharan African cities is frequent and can be considered as a critical issue, both from an environmental standpoint and in terms of associated maintenance costs. This study analyzes the state of the sanitation systems, the elements behind the failures, the environmental concepts used to classify the...

Background: In proteomics, the interpretation of mass spectra representing peptides carrying multiple complex modifications is still challenging, currently limited by the number of potential modifications considered in a single analysis and the need to know them in advance. Further developments must be done in the field to help the scientific commu...

This study aims to develop a decision support tool for patients and surgeons dealing with the uncertainty of surgical outcomes and the expectations of both parties for treating symptomatic lumbar disc herniation (LDH). The study uses a mixed-methods approach with Markov Chains (MC) and Analytic Hierarchy Process (AHP) to predict future health state...

Purpose. To evaluate patient perceptions of a Web-based decision aid for the treatment of localized prostate cancer. Methods. We assessed patient perceptions of a multicomponent, Web-based decision aid with a preference elicitation/values clarification exercise using adaptive conjoint analysis, the generation of a summary report, and provision of i...

While the development of prognostic models is nowadays rather feasible, the implementation and validation thereof can still create many challenges. One of the main challenges is the lack of high-quality input data like operational data, environmental data, maintenance data and the limited amount of degradation or failure data. The uncertainty in th...

This study explores the potential of computational decision support to enhance social exchange and interactions by leveraging human strengths with formal procedures. The study aims to determine whether mathematical post-negotiation procedures can improve negotiation outcomes and overcome the limitations of human-only approaches in situations of pow...

Objective Electronic health record (EHR)-based shared decision-making (SDM) and clinical decision support (CDS) systems can improve cardiovascular disease (CVD) care quality and risk factor management. Use of the CV Wizard system showed a beneficial effect on high-risk community health center (CHC) patients’ CVD risk within an effectiveness trial,...

This study aims to assess the impact of global warming on winter wheat cultivation under different rotation systems with potato, maize or oilseed rape over a six-year period in the region of Galicia, Spain, to identify the rotation system most favorable from a climate change perspective. An attributional life cycle assessment (ALCA) with economic a...

Considering the rapid pace of global urbanization especially in emerging economies of the global South, this article addresses governance approaches for the sustainable development of cities which seek to transform into smart cities. It focuses on leapfrogging as a governance concept for cities thriving towards sustainable development and describes...

European forest ecosystems are increasingly exposed to stressors such as storm, drought episodes and mass attack of forest insect pests. Sustainable forest management requires a fundamental understanding of causal relationships between forest structures and the occurrence of disturbance events, as well as a well-functioning transfer of scientific k...

In this paper, we proposed a decision support tool for recruiters to improve their hiring decisions of suitable candidates for such a vacancy post. For this purpose, we proposed the use of the Artificial Neural Network (ANN) method from Artificial Intelligence (AI), thus we used real data from a semi-public recruitment agency in Morocco. However, f...

Teaching compendium developed for course 42879 Decision Support & Strategic Assessment at the Technical University of Denmark (DTU)

Aerobic rice cultivation offers the potential to reduce irrigated water use. A multitude of challenges, such as cold sterility, drought stress, and labor shortages, limit its adoption in temperate rice-growing regions. Increasing the duration and extent of soil moisture tension between irrigation events has been demonstrated to slow crop developmen...

Tsunamis are a perilous natural phenomenon endangering growing coastal populations and tourists in many seaside resorts. Failures in responding to recent tsunami events stresses the importance of further research in building a robust tsunami warning system, especially in the “last mile” component. The lack of detail, unification and standardisation...

Canopy chlorophyll content (CCC) is closely related to crop nitrogen status, crop growth and productivity, detection of diseases and pests, and final yield. Thus, accurate monitoring of chlorophyll content in crops is of great significance for decision support in precision agriculture. In this study, winter wheat in the Guanzhong Plain area of the...

Across the Midwest region of the United States, agriculturalists make decisions on a variety of timescales, ranging from daily to weekly, monthly, and seasonally. Ever-improving forecasts and decision support tools could assist the decision-making process, particularly in the context of a changing and increasingly variable climate. To be usable, ho...

Introduction Traumatic brain injury (TBI) is a major global health burden that results in disability and loss of health. Identifying those patients who require specialist neuroscience care can be challenging due to the low accuracy of existing prehospital trauma triage tools. Despite the widespread use of decision aids to ‘rule out’ TBI in hospital...

The significant increases in the various technologies that are available to field-level law enforcement personnel either currently or as deployments are projected over the next few years have created very promising opportunities for improved effectiveness in their completion of their assigned preliminary investigations of serious crimes. Currently,...

The objective of a policy will be achieved if the policy targets are well-defined. However, it often happens that the policy targets do not utilise the public policies given optimally. Therefore, it is essential to predict the targeted group that will utilise the policy provided so that the policy implementation can be more efficient. This study us...

Forest-based scenic spots have received widespread attention for their landscape aesthetics and ecological value, but the rapid growth of tourism and landscape exploitation make it challenging to balance human recreational needs, landscape quality, and ecological stability. This study aimed to evaluate, quantify, and grade landscape quality from th...

With the advent of SARS-CoV-2, several studies have shown that there is a higher mortality rate in patients with diabetes and, in some cases, it is one of the side effects of overcoming the disease. However, there is no clinical decision support tool or specific treatment protocols for these patients. To tackle this issue, in this paper we present...

Early detection and diagnosis of oral cancer are critical for a better prognosis, but accurate and automatic identification is difficult using the available technologies. Optical coherence tomography (OCT) can be used as diagnostic aid due to the advantages of high resolution and non-invasion. We aim to evaluate deep-learning-based algorithms for O...

Marine oil spills have been of tremendous concern due to their adverse impact on economic and ecological systems. Major oil spills triggered worldwide consciousness of marine spill response. In past decades, significant advances have been made in diverse aspects including prevention and preparedness, spill response and cleanup options, modelling of...

The dwindling and scarcity of fossil energy sources is the basis of the energy transition, where renewable resources are increasingly valued. The purpose of the cogeneration system studied in this article is to recover the residual heat from the gases coming out of the chimneys of the cement kilns, to produce at the same time the electricity and th...