Computer-aided Analysis Method Research Articles

Comparison of computer-aided and manual measurements in the evaluation of carpal alignment

The purpose of this study was to compare computer-aided analysis and different methods of manual measurements in the evaluation of carpal alignment. The radioscaphoid, radiolunate, radiocapitate and radiometacarpal angles were measured on cone-beam computed tomography (CT) scans of 30 healthy wrists by automated software (Disior Ltd.) and by hand surgeons using lateral radiographs reconstructed from the CT data. Hand surgeons were either given ( n = 6) or not given ( n = 7) prior instructions on how to perform the measurements. Inter- and intra-observer reliability of manual measurements ranged from good to excellent (intra-class correlation coefficients [ICC] 0.77–0.99), being highest in specialists with standardized methods and in reconstructed radiographs with bone overlap digitally removed. Computer-aided software provided excellent intra-observer reliability (ICC 0.94–1.00) consistently and values that were highly comparable (mean difference range 1°–7°) with the manual measurements made in optimal settings. Computer-aided software provides an accurate and repeatable method to measure carpal alignment in CT scans, minimizing observational errors.

Competitive intelligence empirical validation and application: Foundations for knowledge advancement and relevance to practice

The competitive intelligence (CI) construct must be scientifically defined, characterised, empirically validated and accurately measured to grow in science and business. This study aims at elevating the accuracy of the empirical validation of the CI construct suggested and confirmed by Madureira, Popovic and Castelli to serve as the scientific foundation for CI praxis. This construct is selected due to its unmatched recency, thoroughness, universality identified limitations of its empirical validation. We relied on a multistrand design of fully sequential with equivalent status qualitative and quantitative mix-methods followed by the triangulation of the findings and the development of the meta-inferences. Validity, reliability and applicability were tested using computer-aided text analysis and artificial intelligence methods based on 61 in-depth interviews with CI subject matter experts. Contributions to knowledge advancement and relevance to practice derive from the scientific-grade empirical construct validation, providing undisputed levels of accuracy, consistency, applicability, and triangulation of results. This study highlights three critical implications. First, the delimitation of the body of knowledge and recognition of the CI domain serve as the baseline for theory development. Second, the validated construct guarantees reproducibility, replicability and generalisability, laying the foundations for establishing CI science, practice and education. Third, creating a common language and shared understanding will drive the much-claimed definitional consensus. This study thus stands as a foundational pillar in supporting CI praxis in improving decision-making quality and the performance of organisations.

Açık Kalp Ameliyatı Olan Hastalarda Ses Analizi İle Ses Kalitesinin Değerlendirilmesi

Objective: In this study, we aimed to reveal the effect of open heart surgeries on acoustic sound quality and vocal range by using computer aided analysis method.
 
 Materials and Methods: Preoperative objective voice analysis was performed on 40 patients who were operated on in our clinic between 2020 and 2021. Measurements were repeated in the 2nd postoperative month. The results were compared statistically.
 
 Results: There was no significant difference between the groups according to the voice handicap index-10 (VHI-10) (p>0.050). The baseline frequency (F0) value was found to be statistically significantly higher in the postoperative period compared to the preoperative period (p=0.042). There was no statistically significant difference between groups in jitter %, shimmer % and harmonic noise ratio (HNR) values.
 
 Conclusion: Open heart surgery is an operation that can have a destructive effect on the respiratory system. The fact that the lungs, which are the source of voice energy, are affected, suggests that the voice quality will also be affected. While these effects usually regress in a short time, they can sometimes be permanent. This condition mostly affects people who use their voice in their profession. Therefore, detailed information about such a situation should be given to each patient and care should be taken to minimize the factors that may cause voice disorders.

Methods for Analyzing the Contents of Social Media for Health Care: Scoping Review.

Given the rapid development of social media, effective extraction and analysis of the contents of social media for health care have attracted widespread attention from health care providers. As far as we know, most of the reviews focus on the application of social media, and there is a lack of reviews that integrate the methods for analyzing social media information for health care. This scoping review aims to answer the following 4 questions: (1) What types of research have been used to investigate social media for health care, (2) what methods have been used to analyze the existing health information on social media, (3) what indicators should be applied to collect and evaluate the characteristics of methods for analyzing the contents of social media for health care, and (4) what are the current problems and development directions of methods used to analyze the contents of social media for health care? A scoping review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was conducted. We searched PubMed, the Web of Science, EMBASE, the Cumulative Index to Nursing and Allied Health Literature, and the Cochrane Library for the period from 2010 to May 2023 for primary studies focusing on social media and health care. Two independent reviewers screened eligible studies against inclusion criteria. A narrative synthesis of the included studies was conducted. Of 16,161 identified citations, 134 (0.8%) studies were included in this review. These included 67 (50.0%) qualitative designs, 43 (32.1%) quantitative designs, and 24 (17.9%) mixed methods designs. The applied research methods were classified based on the following aspects: (1) manual analysis methods (content analysis methodology, grounded theory, ethnography, classification analysis, thematic analysis, and scoring tables) and computer-aided analysis methods (latent Dirichlet allocation, support vector machine, probabilistic clustering, image analysis, topic modeling, sentiment analysis, and other natural language processing technologies), (2) categories of research contents, and (3) health care areas (health practice, health services, and health education). Based on an extensive literature review, we investigated the methods for analyzing the contents of social media for health care to determine the main applications, differences, trends, and existing problems. We also discussed the implications for the future. Traditional content analysis is still the mainstream method for analyzing social media content, and future research may be combined with big data research. With the progress of computers, mobile phones, smartwatches, and other smart devices, social media information sources will become more diversified. Future research can combine new sources, such as pictures, videos, and physiological signals, with online social networking to adapt to the development trend of the internet. More medical information talents need to be trained in the future to better solve the problem of network information analysis. Overall, this scoping review can be useful for a large audience that includes researchers entering the field.

A new protocol for radio frequency heating of low-moisture, viscous sauces and its temperature uniformity optimisation

AbstractRadio frequency (RF) heating of agri-food, especially low moisture viscous sauces (LMVS), have obvious advantages. However, uneven heating is one main problem of RF heating technology that has to be solved. Due to the unclear heating mechanism and the difficulty to measure the three-dimensional temperature distribution in the heated object, computer-aided analysis method was adopted. Based on the RF heating numerical calculation model after experimental verification and the characteristics of polyetherimide (PEI) assisted RF heating of peanut butter (PB), this study proposed an improved method for an existing protocol. Meanwhile, parameters of the new protocol were optimised by the Multi-objective Global Optimisation (MGO) of its surrogate model. Results demonstrated that the best size of PEI block in the new protocol was Φ100 × 9.5 mm and the positional height was 12 mm. When the pasteurisation temperature Tp was set to 70 °C and the control temperature Tc was set to 75 °C, the temperature uniformity evaluation indices, Over-shoot Temperature Control Index (OTCI) and Targeted Penetration Depth (TPD), were 0.920% and 3.975 mm, respectively. Compared with 4.845% and 4.940 mm before improvement, the new protocol achieved significant optimisation and improved the temperature uniformity effectively. This also proved the feasibility of MGO method of surrogate model in relevant studies.

How do top management team characteristics affect digital orientation? Exploring the internal driving forces of firm digitalization

The top management team (TMT) plays a key role in the process of the firm digital transformation. However, few studies have focused on the impact of TMT characteristics on the digital orientation of firms. In this paper, we simultaneously explore the impact of the dispersion, aggregation, and background characteristics of TMT on the digital orientation of firms. Based on the upper echelons theory and strategic orientation theory, we propose that the diversity and average education level of TMT positively impact firms' digital orientation. The average age and tenure of TMT have a negative impact on the digital orientation of firms. The overseas and financial backgrounds of TMT members have a positive impact on the digital orientation of firms. Our hypothesis was tested using large-scale longitudinal data and computer-aided text analysis methods from Chinese listed companies. This paper provides useful supplements to early research on digital driving factors and digital orientation in emerging economies, and also provides more universal suggestions for digital practices in firms.

Serum interleukin-38 and -41 levels as candidate biomarkers in male infertility

BackgroundInterleukin (IL)-38 and IL-41 are novel cytokines, but their role in male infertility (MI) is unknown. The purpose of this study was to measure the levels of serum IL-38 and IL-41 in patients with MI and correlate these levels with semen indexes. MethodsEighty-two patients with MI and 45 healthy controls (HC) were recruited for this study. Semen parameters were detected using computer-aided sperm analysis, Papanicolaou staining, ELISA, flow cytometry, peroxidase staining and enzyme methods. Serum IL-38 and IL-41 levels were determined by ELISA. ResultsSerum IL-38 levels were decreased (P < 0.01) in patients with MI compared with HC. Serum IL-41 levels were significantly higher in patients with MI than in HC (P < 0.0001). In patients with MI, serum IL-38 levels were positively correlated with semen white blood cell counts (r = 0.29, P = 0.009), and there was a positive correlation between semen white blood cell counts and sperm concentration (r = 0.28, P = 0.0100) and seminal plasma elastase (r = 0.67, P < 0.0001). Receiver operating characteristic curve analysis showed that the area under the curve of IL-38 for diagnosing MI was 0.5637 (P > 0.05), and the area under the curve of IL-41 for diagnosing MI was 0.7646 (P < 0.0001). ConclusionsSerum IL-38 levels were significantly lower, and serum IL-41 levels were higher in patients with MI. These results suggest that IL-38 and IL-41 may be novel biomarkers for the diagnosis of MI.

Cornichon protein CNIH4 is not essential for mice gametogenesis and fertility

BackgroundCornichon is a functionally conserved transmembrane protein family that generally acts as a cargo-sorting receptor and cycles between the ER and the Golgi. Four Cornichon family members (CNIH1-4) have been identified. The key residues responsible for CNIH1-3 to bind to AMPA receptors are not conserved in CNIH4. Additionally, the function of CNIH1-3 in GPCR signaling is less established, while more established in case of CNIH4 protein that interact with GPCR and control their exportation. Many GPCRs are known for their essential roles in male and female gonad development. But whether CNIH4 plays a role in gametogenesis remains unknown. DesignMice carrying the Cnih4 knockout allele (Cnih4tm1a−/−) were generated by insertion of a LacZ reporter and a polyadenylation site after exon 1. Western blot, Immunofluorescence, computer-aided sperm analysis and other methods were used in the functional analysis. ResultsWe identified that both Cnih4tm1a−/− male and female mice have normal fertility. Though, the sperm count, morphology, and motility of Cnih4tm1a−/− mice were slightly impaired compared to those of wild-type mice, the testes to body weight ratio and testicular histology were similar to those in control mice. Histological examination of Cnih4tm1a−/− ovaries detected follicles from primordial to antral stages and the numbers of follicles at each stage were also comparable to wild-type controls. Normal fertility was noticed after six-month fertility tests. That was likely due to the compensatory role of Chin3, which significantly upregulated in the Cnih4tm1a−/− mice to preserve the fertility role. ConclusionDespite CNIH4 showing enriched expression in mouse germ cells, our genetic knockout studies demonstrated that CNIH4 is not essential for gametogenesis and fertility in mice although with a slight reduction in count, motility and morphology of sperm in male mice.

An artificial intelligence method for vessel detection in images of cardiac catheterization

Coronary artery disease (CAD) is one of the top ten leading causes of death in countries worldwide. There are several methods used by physicians to diagnose CAD. One common method is the use of X-ray angiogram (XRA) images. When employing a computer-aided automatic analysis method to locate blood vessels in XRA images, problems such as complex background noise, low contrast, and difficulty in separating blood vessels from the background are encountered, especially for blood vessels with a low contrast to the background noise. In this study, we used various image preprocessing methods to highlight blood vessels from complex backgrounds and different types of blood vessel, followed by the employment of four superpixel segmentation methods to partition an image into multiple segments, and finally the utilization of Weighted Voting to determine the best superpixel algorithm. A genetic algorithm was used to identify the best weights by which to determine the locations of blood vessels in images of cardiac catheterization. Our proposed method achieved an average F1-score of 73.4% in the analysis of five patients, which was better than the other superpixel algorithms tested. The results of this research will be helpful for future SYNTAX score analysis.

The search for alternatives to internal combustion: instantiation mechanisms of institutional logics among scientists and engineers

ABSTRACT While much of the institutional research has suggested and empirically demonstrated that institutional logics shape cognitive and behavioural patterns of actors, what still remains unclear is how scientists and engineers instantiate the conceptual elements of institutional logics in the context of the emergence of new technologies. We demonstrate the mechanisms through which scientists and engineers use the conceptual elements of multiple institutional logics in response to changes in external socio-economic and political conditions to justify their own research activities. Our context is the forty-year search for alternatives to internal combustion within a leading international conference on electric and hybrid electric vehicles (EVS). Combining Computer-Aided Text Analysis (CATA) and inductive methods, we identify four distinct instantiation mechanisms – contextualising, spanning, appropriating, and conflating – that scientists and engineers searching for a successful alternative to internal combustion used to instantiate the institutional logics within which they were embedded.

Using CATA and Machine Learning to Operationalize Old Constructs in New Ways: An Illustration Using U.S. Governors’ COVID-19 Press Briefings

Increased computing power and greater access to online data have led to rapid growth in the use of computer-aided text analysis (CATA) and machine learning methods. Using “big data”, researchers have not only advanced new streams of research, but also new research methodologies. Noting this trend and simultaneously recognizing the value of traditional research methods, we lay out a methodology that bridges the gap between old and new approaches to operationalize old constructs in new ways. With a combination of web scraping, CATA, and supervised machine learning, using labeled ground truth data (i.e., data with known inputs and outputs), we train a model to predict CIP (Charismatic-Ideological-Pragmatic) leadership styles from running text. To illustrate this method, we apply the model to classify U.S. state governors’ COVID-19 press briefings according to their CIP leadership style. In addition, we demonstrate content and convergent validity of the method.

A Method for Object Classification in Aerial/Satellite Images with Incorporating Geospatial Information

Aerial and satellite multispectral images are important source of intelligence information. However, the object classification accuracy in those images for reasons such as camouflage, use of decoys, and others often turns out to be insufficient. The objective of the study is to develop a method for computer-aided analysis of aerial and satellite multispectral images, which allows improving classification accuracy. This objective is achieved by incorporating geospatial information (topographic, geodetic, about land cover types) into the classification process. As a mathematical basis of the method is used subjective logic of A. Jøsang. The effectiveness of the proposed method has been demonstrated by computer modeling using ArcGIS ModelBuilder tools.

A Method for Object Classification in Aerial/Satellite Images with Incorporating Geospatial Information

Aerial and satellite multispectral images are important source of intelligence information. However, the object classification accuracy in those images for reasons such as camouflage, use of decoys, and others often turns out to be insufficient. The objective of the study is to develop a method for computer-aided analysis of aerial and satellite multispectral images, which allows improving classification accuracy. This objective is achieved by incorporating geospatial information (topographic, geodetic, about land cover types) into the classification process. As a mathematical basis of the method is used subjective logic of A. Jøsang. The effectiveness of the proposed method has been demonstrated by computer modeling using ArcGIS ModelBuilder tools.

Quantitative Nuclear Histomorphometry Predicts Molecular Subtype and Clinical Outcome in Medulloblastomas: Preliminary Findings

Molecular subtypes of medulloblastoma [Sonic Hedgehog (SHH), Wingless/INT (WNT), Group 3, and Group 4] are defined by common patterns of gene expression. These differential gene expression patterns appear to result in different histomorphology and prognosis. Quantitative histomorphometry is a well-known method of computer-aided pathology image analysis. The hypotheses we sought to examine in this preliminary proof of concept study were whether computer extracted nuclear morphological features of medulloblastomas from digitized tissue slide images could independently: (1) distinguish between molecularly determined subgroups and (2) identify patterns within these subgroups that correspond with clinical outcome. Our dataset was composed of 46 medulloblastoma patients: 16 SHH (5 dead, 11 survived), 3 WNT (0 dead, 3 survived), 12 Group 3 (4 dead, 8 survived), and 15 were Group 4 (5 dead, 10 survived). A watershed-based thresholding scheme was used to automatically identify individual nuclei within digitized whole slide hematoxylin and eosin tissue images. Quantitative histomorphometric features corresponding to the texture (variation in pixel intensity), shape (variations in size, roundness), and architectural rearrangement (distances between, and number of connected neighbors) of nuclei were subsequently extracted. These features were ranked using feature selection schemes and these top-ranked features were then used to train machine-learning classifiers via threefold cross-validation to separate patients based on: (1) molecular subtype and (2) disease-specific outcomes within the individual molecular subtype groups. SHH and WNT tumors were separated from Groups 3 and 4 tumors with a maximum area under the receiver operating characteristic curve (AUC) of 0.7, survival within Group 3 tumors was predicted with an AUC of 0.92, and Group 3 and 4 patients were separated into high- and low-risk groups with p = 0.002. Model prediction was quantitatively compared with age, stage, and histological subtype using univariate and multivariate Cox hazard ratio models. Age was the most statistically significant variable for predicting survival in Group 3 and 4 tumors, but model predictions had the highest hazard ratio value. Quantitative nuclear histomorphometry can be used to study medulloblastoma genetic expression phenotypes as it may distinguish meaningful features of disease pathology.

Delivery and evaluation of an e-Learning framework through computer-aided analysis of learners\u2019 reflection text in a teacher development course

This study aimed at proposing an e-Learning framework in school education. The proposed framework consisted of technology and pedagogy dimensions. The method of computer-aided analysis of learners’ reflection text was used to evaluate the pedagogical delivery of the proposed framework. A study involving 33 in-service teachers in a teacher development course was conducted to investigate the effectiveness of the pedagogical delivery. The computer-aided analysis of learners’ reflection text on “what is e-Learning” before and after the teaching of the course showed that learners deepened their understanding about the technology use and the importance of pedagogy in e-Learning, to consider more the component on theories/models/principles/strategies in pedagogical design and practices, emphasize more the reflection and discussion in learning and teaching activities, and also realize more the possibility of pedagogical decision-making using data collected from online learning. The questionnaire survey and focus group interview with learners also indicated that the pedagogical delivery of the e-Learning framework with the support from the computer-aided analysis of learners’ reflection text coupled with hierarchical visualization of analysis results was positively perceived. The research findings contribute pioneering insights into the use of a computer-aided approach for an accurate and efficient evaluation in teacher development courses on e-Learning.

A Study on the Influencing Mechanisms of Motivational Appeals on Financing Performance in Poverty Alleviation Crowdfunding

Poverty alleviation crowdfunding is a new way to achieve the targeted poverty alleviation under the “Internet +” context. Existing studies fail to disclose how the motivational appeals contained in the entrepreneurial narratives of poverty alleviation crowdfunding have impacts on their financing performance. Relying upon the cognitive evaluation theory, this paper puts forward a research model that depicts how motivational appeals influence financing performance. The research model is examined by the 640 actual poverty alleviation crowdfunding projects from the JD crowdfunding platform, revealing which motivational appeal is more helpful in impressing the backers and how to improve the project financing performance. This paper thus answers the following two research questions: (1) What motivational appeals are contained in entrepreneurial narratives? (2) How do these appeals have impacts on financing performance?The conclusions are offered as follows: Both the internal and external motivational appeals have various impacts on financing performance. More specifically, both altruistic appeals and reward appeals positively contribute to financing performance, social appeals have a negative impact, and risk disclosure has no significant effect. The results indicate that when participating in the pro-social projects such as poverty alleviation crowdfunding, backers have more complex motivations: They have the altruistic motivations to help others and the need to acquire material rewards; overall, they do not have many concerns on risks, and they do not leverage poverty alleviation crowdfunding projects for their social needs.The implications are that: First, the crowdfunders of poverty alleviation projects should focus on arousing backers’ altruistic motivations rather than their social motivations. They also should put an emphasis on rewards rather than risk disclosure. Second, platform providers and relevant government agencies should guide and train crowdfunders to use appropriate languages to publicize their poverty alleviation crowdfunding projects.The future directions are offered as follows: First, future studies can deepen and improve the results of this study by collecting other types of crowdfunding projects and by conducting more empirical tests based on the large sample data set. Second, they can also deeply analyze the reasons for the success or failure of crowdfunding projects (such as the sponsor’s passion). Emotional changes have a deep impact on people, and thus, emotional reactions may directly affect the individual’s attitude, leading to emotion-driven behavior. Therefore, emotion is an important mediating variable between crowdfunding projects and financing performance. Future research can try to analyze how crowdfunding projects arouse backers’ emotion to lead to the success of the project.This paper makes the following contributions: First, based on the cognitive evaluation theory, it not only provides a more complete explanatory framework for the participating behavior of poverty alleviation crowdfunding projects, but also deepens the application of this theory in this field. Second, with the computer-aided text analysis method, it points out the close relationship between entrepreneurial narratives and financing performance, which not only expands the entrepreneurial narrative research to the field of crowdfunding, but also makes a good complement to the extant research that focuses on information cues.

Using Text Analysis and Machine Learning to Classify U.S. Governors’ COVID-19 Press Briefings

Increased computing power and greater access to online data have led to rapid growth in the use of computer-aided text analysis (CATA) and machine learning methods. Using “Big Data”, researchers have not only advanced new streams of research, but also new research methodologies. Noting this trend, while simultaneously recognizing the value of traditional research methods, we lay out a methodology to bridge the gap between old and new approaches. With a combination of web scraping, CATA, and supervised machine learning, using ground truth data, we train a model to predict CIP (Charismatic-Ideological-Pragmatic) leadership styles from running text. To illustrate this method, we apply the model to classify U.S. state governors’ COVID-19 press briefings according to their CIP leadership style. In addition, we demonstrate content and convergent validity of the method.

Research on Optimization Design of Suzhou Sandalwood Fans Based on Level of Analysis of Female Aesthetic Images

This study constructs the hierarchical theoretical model of image design to realize more accurate aesthetic feature identification for females. The study mainly takes the scale, material and hollowed-out technique of Suzhou Sandalwood Fans as the carrier for the perception of products’ aesthetic image, then retrieves words of female perceptual image with factor analysis in SPSS and other computer-aided information analysis methods, and evaluates the weights of different aesthetic image factors to screen out case models with higher adaptability, thus improving the market acceptance of subsequent design schemes. Based on relevant Suzhou cultural elements, it carries out the detailed optimization design practice to verify the feasibility of this method.

Computer-aided analysis method of nitrogen pollution in an ecological river

Computer-aided analysis method of nitrogen pollution in an ecological river

Computer-aided assessment of the chemokine receptors CXCR3, CXCR4 and CXCR7 expression in gallbladder carcinoma.

Gallbladder carcinoma (GBC) is a vicious and invasive disease. The major challenge in the clinical treatment of GBC is the lack of a suitable prognosis method. Chemokine receptors such as CXCR3, CXCR4 and CXCR7 play vital roles in the process of tumour progression and metastasis. Their expression levels and distribution are proven to be indicative of the progression of GBC, but are hard to be decoded by conventional pathological methods, and therefore, not commonly used in the prognosis of GBC. In this study, we developed a computer‐aided image analysis method, which we used to quantitatively measure the expression levels of CXCR3, CXCR4 and CXCR7 in the nuclei and cytoplasm of glandular and interstitial cells from a cohort of 55 GBC patients. We found that CXCR3, CXCR4 and CXCR7 expressions are associated with the clinicopathological variables of GBC. Cytoplasmic CXCR3, nuclear CXCR7 and cytoplasmic CXCR7 were significant predictive factors of histology invasion, whereas cytoplasmic CXCR4 and nuclear CXCR4 were significantly correlated with T and N stage and were associated with the overall survival and disease‐free survival. These results suggest that the quantification and localisation of CXCR3, CXCR4 and CXCR7 expressions in different cell types should be considered using computer‐aided assessment to improve the accuracy of prognosis in GBC.