Demographic Determinants Influencing the Adoption of Genetic Testing for Cardiovascular Diseases in Japan　- Insights From a Large-Scale Online Survey.

Background: Genetic testing for cardiovascular diseases (CVD) is vital, but is underutilized in Japan due to limited insurance coverage, accessibility, and public disinterest. This study explores demographic factors influencing the decision to undergo CVD genetic testing. Methods and Results: We compared the CVD history and baseline demographics of Japanese adults who underwent genetic testing with those who did not, using an Internet survey. The regression model indicated that men, the young, married individuals, parents, and those with CVD, higher score for rationality, and lower quality of life were more inclined to undergo testing. Conclusions: Targeting strategies for CVD genetic testing could focus on these demographics.

Decision-making regarding social situations in people with intellectual disability at different stages of the decision-making process.

Decision-making capability is essential in fulfilling the need for autonomy of people with intellectual disability. In this study we aimed to examine decision-making capability regarding important social situations in people with intellectual disability at different stages of decision-making process. We studied 80 vocational school students with mild intellectual disability and 80 students of a similar age from mass vocation schools. We assessed decision-making with Important Life Decisions Task (ILDT). Students with intellectual disability obtained significantly lower scores than controls for each of the stories in ILDT as in each stage and overall final score in the decision-making process. The magnitude of difference in scores between groups varied in different stages of decision-making process. The most notable difficulties in decision-making regarding important social situations in people with intellectual disability are related to the evaluation of alternatives stage. Pattern of differences obtained in our study may be related to the content of decision-making problems.

Balancing the benefits of vaccination: An envy-free strategy.

The Covid-19 pandemic revealed the difficulties of vaccinating a population under the circumstances marked by urgency and limited availability of doses while balancing benefits associated with distinct guidelines satisfying specific ethical criteria. We offer a vaccination strategy that may be useful in this regard. It relies on the mathematical concept of envy-freeness. We consider finding balance by allocating the resource among individuals that seem heterogeneous concerning the direct and indirect benefits of vaccination, depending on age. The proposed strategy adapts a constructive approach in the literature based on Sperner's Lemma to point out an approximate division of doses guaranteeing that both benefits are optimized each time a batch becomes available. Applications using data about population age distributions from diverse countries suggest that, among other features, this strategy maintains the desired balance, throughout the entire vaccination period. We discuss complementary aspects of the method in the context of epidemiological models of age-stratified Susceptible - Infected - Recovered (SIR) type.

Machine Learning Model for Readmission Prediction of Patients With Heart Failure Based on Electronic Health Records: Protocol for a Quasi-Experimental Study for Impact Assessment.

BACKGROUND: Care for patients with heart failure (HF) causes a substantial load on health care systems where a prominent challenge is the elevated rate of readmissions within 30 days following initial discharge. Clinical professionals face high levels of uncertainty and subjectivity in the decision-making process on the optimal timing of discharge. Unwanted hospital stays generate costs and cause stress to patients and potentially have an impact on care outcomes. Recent studies have aimed to mitigate the uncertainty by developing and testing risk assessment tools and predictive models to identify patients at risk of readmission, often using novel methods such as machine learning (ML). OBJECTIVE: This study aims to investigate how a developed clinical decision support (CDS) tool alters the decision-making processes of health care professionals in the specific context of discharging patients with HF, and if so, in which ways. Additionally, the aim is to capture the experiences of health care practitioners as they engage with the system's outputs to analyze usability aspects and obtain insights related to future implementation. METHODS: A quasi-experimental design with randomized crossover assessment will be conducted with health care professionals on HF patients' scenarios in a region located in the South of Sweden. In total, 12 physicians and nurses will be randomized into control and test groups. The groups shall be provided with 20 scenarios of purposefully sampled patients. The clinicians will be asked to take decisions on the next action regarding a patient. The test group will be provided with the 10 scenarios containing patient data from electronic health records and an outcome from an ML-based CDS model on the risk level for readmission of the same patients. The control group will have 10 other scenarios without the CDS model output and containing only the patients' data from electronic medical records. The groups will switch roles for the next 10 scenarios. This study will collect data through interviews and observations. The key outcome measures are decision consistency, decision quality, work efficiency, perceived benefits of using the CDS model, reliability, validity, and confidence in the CDS model outcome, integrability in the routine workflow, ease of use, and intention to use. This study will be carried out in collaboration with Cambio Healthcare Systems. RESULTS: The project is part of the Center for Applied Intelligent Systems Research Health research profile, funded by the Knowledge Foundation (2021-2028). Ethical approval for this study was granted by the Swedish ethical review authority (2022-07287-02). The recruitment process of the clinicians and the patient scenario selection will start in September 2023 and last till March 2024. CONCLUSIONS: This study protocol will contribute to the development of future formative evaluation studies to test ML models with clinical professionals. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/52744.

Predictors of knowledge and knowledge gain after decision aid use among women with BRCA1/2 pathogenic variants.

OBJECTIVE: To identify factors contributing to baseline knowledge in women with BRCA1/2 pathogenic variants (PVs) and knowledge gain after decision aid (DA) use. METHODS: Women with PVs in BRCA1 or BRCA2 genes were randomly assigned to an intervention group (IG) receiving DAs or a control group (CG). Of the total sample, 417 completed the baseline survey and were included in this analysis. Two multiple regression analyses were conducted: baseline data on socio-demographic, medical, decision-related and psychological variables were used to identify predictors for (1) baseline knowledge within the total group and (2) knowledge gain within the IG after DA use three months post study inclusion. RESULTS: At baseline, higher education status, no breast cancer history, and lower decisional conflict related to higher knowledge within the total group. After DA use within the IG, higher baseline scores for decisional conflict predicted higher knowledge gain, and higher baseline scores for depression and intrusion predicted lower knowledge gain. CONCLUSIONS: This study identified predictors of baseline knowledge and knowledge gain after DA use in women with BRCA1/2 PVs. PRACTICE IMPLICATIONS: Awareness of facilitating and hindering factors on these women's knowledge can improve understanding of their health literacy and enable further targeted support interventions.

An Update Summary on the Learning Sciences Within an Ophthalmic Context.

Clinical reasoning, specifically diagnostic decision-making, has been a subject of fragmented literature since the 1970s, marked by diverse theories and conflicting perspectives. This article reviews the latest evidence in medical education, drawing from scientific literature, to offer ophthalmologists insights into optimal strategies for personal learning and the education of others. It explores the historical development of clinical reasoning theories, emphasising the challenges in understanding how doctors formulate diagnoses. The importance of clinical reasoning is underscored by its role in making accurate diagnoses and preventing diagnostic errors. The article delves into the dual process theory, distinguishing between type 1 and type 2 thinking and their implications for clinical decision-making. Cognitive load theory is introduced as a crucial aspect, highlighting the limited capacity of working memory and its impact on the diagnostic process. The zone of proximal development (ZPD) is explored as a framework for optimal learning environments, emphasising the importance of scaffolding and deliberate practice in skill development. The article discusses semantic competence, mental representation, and the interplay of different memory stores-semantic, episodic, and procedural-in enhancing diagnostic proficiency. Self-regulated learning (SRL) is introduced as a student-centric approach, emphasising goal setting, metacognition, and continuous improvement. Practical advice is provided for minimising cognitive errors in clinical reasoning, applying dual process theory, and considering cognitive load theory in teaching. The relevance of deliberate practice in ophthalmology, especially in a rapidly evolving field, is emphasised for continuous learning and staying updated with advancements. The article concludes by highlighting the importance of clinical supervisors in recognising and supporting trainees' self-regulated learning and understanding the principles of various teaching and learning theories. Ultimately, a profound comprehension of the science behind clinical reasoning is deemed fundamental for ophthalmologists to deliver high-quality, evidence-based care and foster critical thinking skills in the dynamic landscape of ophthalmology.

Parents' participation in collegial meetings to discuss withholding or withdrawing treatment for their newborn: Working to improve information-sharing.

AIM: The role of parents in decision-making concerning their child's end-of-life care is not clearly defined. Their participation is encouraged by ethical reflection, in particular by the CCNE (French National Ethics Advisory Committee), but laws are limited to imposing a duty to provide information to doctors. Decisions are taken at the end of a collegial meeting (CM) intended to better inform the child's referring physician (RP) who is in charge of the final decision following the French law. The aim of this study was to describe the support provided to bereaved families after they had been invited to attend a CM concerning their child, if they so wished. Additional aims were to determine the differences resulting from their acceptance or their refusal to participate as regards their perception of their child's history and as regards their grieving process. MATERIAL AND METHOD: We conducted a retrospective study of all CMs held between November 2016 and May 2021, drawing a distinction between proposals made or not made to parents and their decision to accept or refuse. RESULTS: In total, 49 CMs concerning 46 children were held during the study period. The proposal was not made to the parents in three cases; the parents chose to be present in 28 cases. The psychological follow-up (15/28 parents attending, 10/16 parents absent) illustrated that their presence enabled them to reflect on their child's death after having listened to and understood the reasons why it happened. They did not dispute the team's approach or decisions taken. CONCLUSION: It is possible to include parents in CMs if they so wish. It would appear more beneficial than merely providing them with the information required. Studies must be carried out to ensure potential long-term benefit.

Chain of Thought Utilization in Large Language Models and Application in Nephrology.

Chain-of-thought prompting enhances the abilities of large language models (LLMs) significantly. It not only makes these models more specific and context-aware but also impacts the wider field of artificial intelligence (AI). This approach broadens the usability of AI, increases its efficiency, and aligns it more closely with human thinking and decision-making processes. As we improve this method, it is set to become a key element in the future of AI, adding more purpose, precision, and ethical consideration to these technologies. In medicine, the chain-of-thought prompting is especially beneficial. Its capacity to handle complex information, its logical and sequential reasoning, and its suitability for ethically and context-sensitive situations make it an invaluable tool for healthcare professionals. Its role in enhancing medical care and research is expected to grow as we further develop and use this technique. Chain-of-thought prompting bridges the gap between AI's traditionally obscure decision-making process and the clear, accountable standards required in healthcare. It does this by emulating a reasoning style familiar to medical professionals, fitting well into their existing practices and ethical codes. While solving AI transparency is a complex challenge, the chain-of-thought approach is a significant step toward making AI more comprehensible and trustworthy in medicine. This review focuses on understanding the workings of LLMs, particularly how chain-of-thought prompting can be adapted for nephrology's unique requirements. It also aims to thoroughly examine the ethical aspects, clarity, and future possibilities, offering an in-depth view of the exciting convergence of these areas.

O-RADS MRI scoring system has the potential to reduce the frequency of avoidable adnexal surgery.

OBJECTIVE: To assess the potential impact of the O-RADS MRI score on the decision-making process for the management of adnexal masses. METHODS: EURAD database (prospective, European observational, multicenter study) was queried to identify asymptomatic women without history of infertility included between March 1st and March 31st 2018, with available surgical pathology or clinical findings at 2-year clinical follow-up. Blinded to final diagnosis, we stratified patients into five categories according to the O-RADS MRI score (absent i.e. non adnexal, benign, probably benign, indeterminate, probably malignant). Prospective management was compared to theoretical management according to the score established as following: those with presumed benign masses (scored O-RADS MRI 2 or 3) (follow-up recommended) and those with presumed malignant masses (scored O-RADS MRI 4 or 5) (surgery recommended). RESULTS: The accuracy of the score for assessing the origin of the mass was of 97.2 % (564/580, CI95% 0.96-0.98) and was of 92.0 % (484/526) for categorizing lesions with a negative predictive value of 98.1 % (415/423, CI95% 0.96-0.99). Theoretical management using the score would have spared surgery in 229 patients (87.1 %, 229/263) with benign lesions and malignancy would have been missed in 6 borderline and 2 invasive cases. In patients with a presumed benign mass using O-RADS MRI score, recommending surgery for lesions >= 100 mm would miss only 4/77 (4.8 %) malignant adnexal tumors instead of 8 (50 % decrease). CONCLUSION: The use of O-RADS MRI scoring system could drastically reduce the number of asymptomatic patients undergoing avoidable surgery.

The trajectory of very old critically ill patients.

The demographic shift, together with financial constraint, justify a re-evaluation of the trajectory of care of very old critically ill patients (VIP), defined as older than 80 years. We must avoid over- as well as under-utilisation of critical care interventions in this patient group and ensure the inclusion of health care professionals, the patient and their caregivers in the decision process. This new integrative approach mobilises expertise at each step of the process beginning prior to intensive care unit (ICU) admission and extending to long-term follow-up. In this review, several international experts have contributed to provide recommendations that can be universally applied. Our aim is to define a minimum core dataset of information to be shared and discussed prior to ICU admission and to facilitate the shared-decision-making process with the patient and their caregivers, throughout the patient journey. Documentation of uncertainty may contribute to a tailored level of care and ultimately to discussions around possible limitations of life sustaining treatments. The goal of ICU care is not only to avoid death, but more importantly to maintain an acceptable quality of life and functional autonomy after hospital discharge. Societal consideration is important to highlight, together with alternatives to ICU admission. We discuss challenges for the future and potential areas of research. In summary, this review provides a state-of-the-art current overview and aims to outline future directions to address the challenges in the treatment of VIP.

[The SCATTER project: computer-based simulation in the strategic transfer of intensive care patients]. / Das SCATTER-Projekt: Computerbasierte Simulation zur Unterstützung bei der strategischen Verlegung von Intensivpatienten.

BACKGROUND: The need for a concept for the nationwide strategic transfer of critical care patients in Germany was highlighted during the COVID-19 (coronavirus disease 2019) pandemic. Despite the cloverleaf concept developed specifically for this purpose, the transfer of large numbers of critical care patients represents a major challenge. With the help of a computer simulation, the SCATTER research project uses a fictitious example to test, develop, and recommend transfer strategies. METHOD: The simulation was programmed after collecting procedural and structural data on critical care transports within Germany. The simulation allows altering various parameters and testing different transfer scenarios. In a fictitious scenario, nationwide transfers starting from Schleswig-Holstein were simulated and evaluated using predetermined criteria. RESULTS: In the case of ground-based transfers, it became apparent that, depending on the selected target region, not all patients could be transferred due to the limited range of ground-based vehicles. Although a higher number of patients can be transferred by air, this is associated with additional gurney changes and potential risk to the patient. A distance-dependent transport strategy led to the identical results as purely air-bound transport, since air-bound transport was always chosen due to the long distances. DISCUSSION: The simulation can be used to develop recommendations and to draw important conclusions from different transfer strategies.

Making recommendations to subsidize new health technologies in Australia: A qualitative study of decision-makers' perspectives on committee processes.

OBJECTIVES: To explore experiences of, and perspectives on, health technology assessment (HTA) processes used to produce recommendations about subsidizing new medicines, and medical technologies in Australia, from the perspectives of those experienced in these processes. METHODS: Semi-structured interviews with a diverse group of 18 informants currently or previously members of the Pharmaceutical Benefits Advisory Committee (PBAC) or the Medical Services Advisory Committee (MSAC). Participants were interviewed September 2021-February 2022. Transcripts were analyzed using reflexive thematic analysis. RESULTS: 3 major themes were identified: contrasting technical and decision-making stages, resisting reductionist approaches, and navigating decision-making trade-offs. Participants discussed the complexities of the evaluative HTA process, especially when considering uncertainty in the evidence. As part of the current process, a deliberative decision-making stage was considered essential, allowing a flexible approach to decision making to consider factors beyond strength and quality of quantifiable data in the technical evaluation. Participants acknowledged these less-quantifiable factors were sometimes considered implicitly or were difficult to describe and this, paired with commercial in confidence requirements, presented challenges with respect to the desire to increase transparency. CONCLUSION (S): As HTA processes for new medicines and medical technologies in Australia continue to be reviewed, the balance between retaining flexibility during deliberation, confidentiality for sponsors and the public's desire for greater transparency may be a fruitful area for continuing research.

Parental perspectives on the decision-making process on transport mode choice in adolescents: a qualitative study with mothers and fathers.

Objective: The present study aims to understand the familial decision-making process on transport mode choice in adolescents with a focus on the parental perspective within this process. Background: Active travel contributes to adolescents' overall physical activity and its positive health effects. Based on the social-learning theory, especially parents are assigned a central role for adolescents' travel behavior. The aim of the present study was to examine how parents are involved in the decision-making process on transport mode choice in adolescents. Method: The study is part of the cross-sectional mixed-methods ARRIVE study which includes semi-structured interviews with mothers (n = 12) and fathers (n = 7) of 11- to 14-year-old German adolescents. The interviews focused on travel behavior in adolescents and the decision-making process on transport mode choice from the parental perspective. All interviews were analyzed inductively using Thematic Analysis. Results: Our study revealed that parents do not primarily decide for or against active travel in adolescents, but are mostly involved in the decision-making process, especially in case of a deviation from the main transport mode. Different forms of parental involvement in the decision-making process were identified. Some parents acted as main decision makers which is the highest form of involvement while others gave their children complete freedom of choose a transport mode for themselves. These parents accepted their child's choice fully which shows a low involvement in the decision-making process. Conclusion: The results provide a deeper understanding of the familial decision-making process on travel behavior in adolescents. The results indicate an occasionally parental involvement in the decision-making process on the mainly used transport mode by adolescents, and that mothers and fathers are always involved when deviating from the main mode. Implications: Further research should investigate changes in travel behavior from childhood to young adulthood to understand long-term travel decisions in families. Due to the findings that parents are often involved in the decision-making process on transport mode choice and that they mainly reported safety concerns as barriers to their children's active travel, further research should focus especially on the social and physical environment of adolescents.

Development of a liver graft assessment expert machine-learning system: when the artificial intelligence helps liver transplant surgeons.

Background: The complex process of liver graft assessment is one point for improvement in liver transplantation. The main objective of this study is to develop a tool that supports the surgeon who is responsible for liver donation in the decision-making process whether to accept a graft or not using the initial variables available to it. Material and method: Liver graft samples candidate for liver transplantation after donor brain death were studied. All of them were evaluated "in situ" for transplantation, and those discarded after the "in situ" evaluation were considered as no transplantable liver grafts, while those grafts transplanted after "in situ" evaluation were considered as transplantable liver grafts. First, a single-center, retrospective and cohort study identifying the risk factors associated with the no transplantable group was performed. Then, a prediction model decision support system based on machine learning, and using a tree ensemble boosting classifier that is capable of helping to decide whether to accept or decline a donor liver graft, was developed. Results: A total of 350 liver grafts that were evaluated for liver transplantation were studied. Steatosis was the most frequent reason for classifying grafts as no transplantable, and the main risk factors identified in the univariant study were age, dyslipidemia, personal medical history, personal surgical history, bilirubinemia, and the result of previous liver ultrasound (p < 0.05). When studying the developed model, we observe that the best performance reordering in terms of accuracy corresponds to 76.29% with an area under the curve of 0.79. Furthermore, the model provides a classification together with a confidence index of reliability, for most cases in our data, with the probability of success in the prediction being above 0.85. Conclusion: The tool presented in this study obtains a high accuracy in predicting whether a liver graft will be transplanted or deemed non-transplantable based on the initial variables assigned to it. The inherent capacity for improvement in the system causes the rate of correct predictions to increase as new data are entered. Therefore, we believe it is a tool that can help optimize the graft pool for liver transplantation.

To eat, or not to eat: a phantom decoy affects information-gathering behavior by a free-ranging mammalian herbivore.

When foraging, making appropriate food choices is crucial to an animal's fitness. Classic foraging ecology theories assume animals choose food of greatest benefit based on their absolute value across multiple dimensions. Consequently, poorer options are considered irrelevant alternatives that should not influence decision-making among better options. But heuristic studies demonstrate that irrelevant alternatives (termed decoys) can influence the decisions of some animals, indicating they use a relative rather than absolute evaluation system. Our aim was to test whether a decoy influenced the decision-making process-that is, information-gathering and food choice-of a free-ranging mammalian herbivore. We tested swamp wallabies, Wallabia bicolor, comparing their behavior toward, and choice of, two available food options over time in the absence or presence of the decoy. We used a phantom decoy-unavailable option-and ran two trials in different locations and seasons. Binary preferences (decoy absent) for the two available food options differed between trials. Irrespective of this difference, across both trials the presence of the decoy resulted in animals more likely to overtly investigate available food options. But, the decoy only shifted food choice, weakly, in one trial. Our results indicate that the decoy influenced the information-gathering behavior during decision-making, providing the first evidence that decoys can affect decision-making process of free-ranging mammalian herbivores in an ecologically realistic context. It is premature to say these findings confirm the use of relative evaluation systems. Whether the foraging outcome is more strongly affected by other decoys, food dimensions, or ecological contexts, is yet to be determined.

A Graph Neural Network Model with a Transparent Decision-Making Process Defines the Applicability Domain for Environmental Estrogen Screening.

The application of deep learning (DL) models for screening environmental estrogens (EEs) for the sound management of chemicals has garnered significant attention. However, the currently available DL model for screening EEs lacks both a transparent decision-making process and effective applicability domain (AD) characterization, making the reliability of its prediction results uncertain and limiting its practical applications. To address this issue, a graph neural network (GNN) model was developed to screen EEs, achieving accuracy rates of 88.9% and 92.5% on the internal and external test sets, respectively. The decision-making process of the GNN model was explored through the network-like similarity graphs (NSGs) based on the model features (FT). We discovered that the accuracy of the predictions is dependent on the feature distribution of compounds in NSGs. An AD characterization method called ADFT was proposed, which excludes predictions falling outside of the model's prediction range, leading to a 15% improvement in the F1 score of the GNN model. The GNN model with the AD method may serve as an efficient tool for screening EEs, identifying 800 potential EEs in the Inventory of Existing Chemical Substances of China. Additionally, this study offers new insights into comprehending the decision-making process of DL models.

The quality of German - language patient decision aids for oncological patients on the internet.

BACKGROUND: Previous studies have already shown that decision aids are a suitable tool for patient decision-making. The aim of this work is to conduct an online search for freely available, German-language patient decision aids (PDAs) for cancer patients, followed by an assessment of their quality. For this purpose, a rating tool that is as manageable as possible was developed on the basis of already existing quality criteria. METHODS: A simulated patient online search was conducted via the four most frequently used search engines in Germany. A quality assessment tool was created utilizing international and national guidelines, with a focus on practicality and manageability. Subsequently, the identified PDAs were rated by 4 raters based on the rating tool. RESULTS: The number of German-language oncology PDAs is low (n = 22 of 200 URLs) with limited variability regarding rare cancers. Most originate from non-profit organizations. The overall quality is low, as indicated by an average of 57.52% of the maximum evaluation points of the developed quality assessment tool. Reference values used to assess quality were related to e.g. support/effectiveness, adaptation, layout, etc. No qualitative differences were found regarding different publishers. Quality differed between PDAs of different length, with longer PDAs achieving better results. CONCLUSION: Overall, the supply and quality of German-language PDAs is not satisfactory. The assessment tool created in this study provides a solid, but more manageable basis, for developing and identifying high-quality PDAs. PRACTICE IMPLICATIONS: PDAs should be increasingly used by physicians in practice. For this, a quick qualitative assessment of PDAs in everyday life must be possible. Future research has to investigate especially the aspect of the length of a PDA in more detail.

Complex spherical fuzzy Aczel Alsina aggregation operators and their application in assessment of electric cars.

The multi-criteria decision-making (MCDM) tool is a robust decision-making technique utilized in several fields like networking, risk management, digital analysis, cybercrime investigation, artificial intelligence, waste management enterprises and many other selection criteria. Complex SFS (CSFS) is a new edition of the spherical fuzzy set (SFS) that offers substantial information about any item in terms of amplitude and phase terms in a wider range of real terms. Complex SFS (CSFS) can be an extension of the spherical fuzzy set (SFS). The Aczel-Alsina aggregation tools are more appropriate aggregation operators (AOs), and they are used to conquer the impact of inconsistent and uncertain data. In this paper, we reveal some new approaches based on Aczel-Alsina aggregation tools under consideration of Complex Spherical Fuzzy (CSF) information. These new approaches include the CSF Aczel-Alsina weighted average (CSFAWA) operator, and the CSF Aczel-Alsina ordered weighted average (CSFOWA) operator. In addition to this, we also introduce a list of novel techniques by making use of the theory of Aczel-Alsina aggregation tools such as CSF Aczel-Alsina weighted geometric (CSFAWG) and CSF Aczel-Alsina ordered weighted geometric (CSFOWG) operators. To demonstrate the resilience and efficacy of the approaches that have been mentioned, we will examine a few exceptional examples and remarkable properties of the methodology that we have devised. In addition, a characterization is provided for an approach to the MCDM issue using the CPF information system. We use the example of electric automobiles as a case study to illustrate the uniformity and dependability of the methodology that we have established. This example was chosen because of the high cost of fuel and the present economic challenges that are being encountered by families in the middle class. An empirical case study is also constructed to determine an electric car that is desirable based on the techniques that we have proposed. To evaluate the correctness and superiority of the established strategies, we compare the outcomes of previously used techniques with the AOs currently being provided.