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Evaluating Perceived Workload, Usability and Usefulness of Artificial Intelligence Systems in Low-Resource Settings: Semi-automated Classification and Detection of Community Acquired Pneumonia 3rd

Evaluating Perceived Workload, Usability and Usefulness of...

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3rd International Workshop on Applications of Medical Artificial Intelligence, AMAI 2024 held in conjunction with the 27th International Conference on Medical Image Computing and computer Assisted Intervention, MICCAI 2024

作者： Muzumala, Malaizyo G. Zulu, Ernest O. Chibuta, Peter Nyirenda, Mayumbo Phiri, Lighton Department of Computer Science University of Zambia Lusaka Zambia Department of Radiology University Teaching Hospitals Lusaka Zambia Department of Library and Information Science University of Zambia Lusaka Zambia

ISBN: (纸本)9783031820069

The use of Artificial Intelligence (AI) techniques in radiological workflows is increasingly becoming mainstream. However, the uptake of AI techniques is still low in low-resource settings such as the Global South. This paper presents a study conducted in a setting with low AI uptake, to determine the impact of AI on Radiologists’ workload when interpreting medical images. Two (2) AI models-a classification model and detection model indicating potential areas of interest-were implemented to facilitate the semi-automated interpretation of medical images for Pneumonia. In addition, a Web-based DICOM Viewer was implemented to interface the AI models. To determine the appropriate model configuration, two (2) experts-a Radiologist and Radiology Resident-participated in a focus group discussion aimed at determining how the AI models could facilitate interpretation processes. A comparative controlled experiment was subsequently conducted with 12 Radiology Residents at a large University teaching Hospital, to assess the impact of AI on the workload and its perceived usefulness. NASA Task Load Index (TLX) and Technology Acceptance Model (TAM) 2 questionnaires were employed to measure the workload and usefulness. The results indicate that the perceived workload is significantly less when using the AI solution, with an overall NASA-TLX score of 1.86. Furthermore, the perceived usefulness of the AI solution is demonstrated through the positive responses for all the eight TAM 2 constructs. This study experimentally demonstrates the potential of utilising AI for the semi-automated interpretation of medical images in low-resource settings. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Digital Imaging and Communications in Medicine (DICOM)

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MGCNet: A Multi-Scale Gated Convolutional Network for SST Remote Sensing Image Inpainting

MGCNet: A Multi-Scale Gated Convolutional Network for SST Re...

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2024 International Conference on Measurement, Communication, and Virtual Reality, MCVR 2024

作者： Zhai, Hanlin Xie, Cui Dong, Junyu Chang, Xiaofeng School of Computer Science and Technology Ocean University of China Qingdao China Basic Teaching Center Ocean University of China Qingdao China

ISBN: (纸本)9781510691773

Existing image inpainting methods are prone to boundary artifacts and texture distortion when dealing with cloud cover in sea surface temperature (SST) satellite remote sensing images. To solve the above problems, this paper proposes a multi-scale gated convolution network (MGCNet) for high- quality SST image inpainting. The backbone of the network is composed of eight multi-scale gated convolution (MGC) blocks, each of which can realize the feature learning at different scales of the image. Building upon this network, an expandable feature enhancement (EFE) module is designed to enhance the perception of crucial features such as temperature gradients and land-sea boundaries through convolution-based feature expansion. A location attention (LA) module is also designed to learn the correlation between local sea temperature and specific sea location by coding the whole target sea area in pixel-based 2D position, especially to capture the distribution of local sea temperature that is higher or lower than the normal due to specific monsoon or ocean current. We conducted experiments on the European Centre for Medium-Range Weather Forecasts (ECMWF) SST remote sensing daily reanalysis dataset for the South China Sea and the Gulf of Mexico regions. Experimental results show that our method has better inpainting effect compared with the mainstream T-former, MISF, CTSDG, PiiGAN and so on. © 2025 SPIE.

关键词： Photointerpretation

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Febrile disease modeling and diagnosis system for optimizing medical decisions in resource-scarce settings

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Clinical eHealth 2024年第1期7卷 52-76页

作者： Asuquo, Daniel Attai, Kingsley Obot, Okure Ekpenyong, Moses Akwaowo, Christie Arnold, Kiirya Uzoka, Faith-Michael Department of Computer Science Faculty of Science University of Uyo Nigeria Department of Mathematics & Computer Science Ritman University Nigeria University of Uyo Teaching Hospital Uyo Nigeria Department of Community Medicine University of Uyo Nigeria Kyambogo University Kampala Uganda Department of Mathematics and Computing Mount Royal University Calgary Canada

Febrile diseases are highly prevalent in tropical regions due to elevated humidity and high temperatures. These regions, mainly comprising low- and middle-income countries, often face challenges related to inadequate medical infrastructure and a lack of skilled personnel for accurately diagnosing febrile diseases. Distinguishing one febrile illness from another posed a significant challenge, adding to the complexity of accurate diagnoses. This study developed a multi-symptom multi-disease model to address this challenge, leveraging exploratory data analysis of patient datasets from field studies and the expertise of medical practitioners specializing in tropical diseases. The research investigated the most effective modeling approach for differentiating among 11 febrile illnesses that are prevalent in Nigeria using three intelligent techniques: Extreme Gradient Boost (XGBoost), Fuzzy Cognitive Map (FCM), and Analytic Hierarchy Process (AHP). Comparative analysis demonstrates that AHP surpassed the others, achieving a precision of 84%, recall of 83%, and an F1-score of 84%. Consequently, the AHP technique was integrated into the development of “Febra Diagnostica,” an app aimed at enhancing febrile disease diagnosis in resource-constrained settings. The app was then deployed and utilized in select Nigerian states, offering scalability and empowering frontline health workers in primary health facilities. Febra Diagnostica featured user-friendly interfaces, automated diagnosis and treatment suggestions, streamlined referrals, and provisions for further investigations. Encryption, access control, and multi-factor authentication were some of the security and privacy considerations in the app which gained acceptance from medical experts and adapted to regulatory and ethical policies for smart healthcare systems. © 2023

关键词： Analytic hierarchy process Febrile diseases Fuzzy cognitive map Intelligent diagnosis and optimization Machine learning

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InLite-HRNet: Efficient Band Convolution Network for Human Pose Estimation

InLite-HRNet: Efficient Band Convolution Network for Human P...

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2024 International Conference on Measurement, Communication, and Virtual Reality, MCVR 2024

作者： Zhang, Ziyang Xie, Cui Dong, Junyu Chang, Xiaofeng Wang, Yiguo College of Computer Science and Technology Ocean University of China Qingdao China Basic Teaching Center Ocean University of China Qingdao China

ISBN: (纸本)9781510691773

In the task of fast human pose estimation, to obtain a broader receptive field and more comprehensive pose information, the traditional method is to use a large convolution kernel in a lightweight network to expand the receptive field. However, large convolution kernels bring high computational complexity and are not suitable for fast estimation tasks. To address these problems, this study presents a lightweight human pose estimation network named InLite-HRNet. It uses two orthogonal band kernels in the vertical and horizontal directions instead of a single large convolution kernel, effectively increasing the size of the receptive field without additional computation. This approach decomposes the depth-wise separable convolution of the large convolution kernel into four parallel branches along channel dimensional (a square kernel, two orthogonal band kernels, and identity mapping) and embeds them into a new module SyncroFuse to enhance its feature expression ability. SyncroFuse is the basic component unit of our InLite-HRNet that plays a significant advantage of using large Receptive field to extract features on the high-resolution network. Experimental results show that the proposed network achieves an average accuracy of 71.07% and 87.22% on COCO and MPII human pose estimation datasets, which is better than the existing excellent lightweight networks and comparable to the existing large-scale human pose estimation networks. © 2025 SPIE.

关键词： Image segmentation

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Influence of the Sequence of Drilling Fields on the Maximum Total Gas Production 16

Influence of the Sequence of Drilling Fields on the Maximum ...

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16th International Conference Management of Large-Scale System Development, MLSD 2023

作者： Skiba, Alexander Federal Research Center 'Computer Science and Control' of Ras Department of Mathematical Methods of Regional Programming Moscow Russia

We analyze an aggregated dynamic model for the development of gas fields. The same company consistently drills all fields. We pose and solve the problem of maximizing accumulated gas production over a predetermined pe... 详细信息

ISBN: (纸本)9798350337907

关键词： Gas industry

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Current Trends in Artificial Intelligence for Educational Advancements

Current Trends in Artificial Intelligence for Educational Ad...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Al-Tarawneh, Abdallah M. A. Alomoush, Reem Abdelkareem Ul Islam, Tanveer Janjua, Jamshaid Iqbal Abbas, Tahir Ihsan, Anaum Al-Ahliyya Amman University Clinical Psychology Amman Jordan Yarmouk University Faculty of Educational Sciences Department of Curricula and Methods of Teaching Jordan TIMES Institute Department of Computer Science Multan60000 Pakistan Lahore Pakistan

ISBN: (纸本)9798350369106

The focus of this paper is the integration of artificial intelligence (AI) within the educational field including but not limited to, adaptive learning, teaching evaluation, online learning environments, and individualized instruction. The authors investigate the positive role of AI in enhancing teaching performance and the quality of students' learning experiences. The study aims to demonstrate what role AI may play in the course of education development and practice improvement. It also sheds light on the limitations AI will have in the realm of education, such as accessibility, data ownership, and ethical issues. The paper does not contain only the limitations but the opportunities for this technology as well and describes how AI could be effectively incorporated into education, subsequently providing insights into the evolution of AI-based educational transformation. © 2024 IEEE.

关键词： Federated learning

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Design of Composite Factor Variance and Component Analysis System Based on Data Analysis Algorithm 13

Design of Composite Factor Variance and Component Analysis S...

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13th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2024

作者： Wang, Yue Zhang, Yiqian Jinan Vocational College Division of Public Teaching Jinan China Jinan Vocational College Department of Computer Science Jinan China

ISBN: (纸本)9798350305463

It is very difficult to analyze and mine massive and high-dimensional data. Although the current hardware conditions have greatly improved, they still cannot meet the needs of large-scale, high-dimensional data. In medical research, scientific experiments, and biological gene sequencing, a combination of analysis of variance and principal component analysis was used to study the above issues. On this basis, this article started from two main data analysis methods and studied the relevant theories and algorithms of binary analysis of variance and principal component analysis, in order to achieve the analysis of sample data. The experiment proved that the data analysis based on the system in this article can combine the factor load matrix of the main factor variables to evaluate the contribution of each factor in the investment portfolio to the overall risk. Finally, the optimal stock portfolio was 601989, 601601, 600028, 600104, 601857, and 601988. © 2024 IEEE.

关键词： Principal component analysis

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Leveraging deep learning for Python version identification 22

Leveraging deep learning for Python version identification

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22nd Belgium-Netherlands Software Evolution Workshop, BENEVOL 2023

作者： Gerhold, Marcus Solovyeva, Lola Zaytsev, Vadim Technical Computer Science University of Twente Enschede Netherlands Formal Methods and Tools University of Twente Enschede Netherlands

Python, recognized for its dynamic and adaptable nature, has found widespread application in a myriad of projects. As the language evolves, determining the Python version employed in a project becomes pivotal to ensure compatibility and facilitate maintenance. Deep learning (DL) has emerged as a promising tool to automate this process. In this research, we assess various DL techniques in determining the minimum Python version for a code snippet. We explore the complexities of handling Python data and the DL techniques to achieve high classification accuracy. Our experimental results show, that LSTM with CodeBERT embedding achives an accuracy of 92%. This success can be attributed to the LSTM's proficiency in capturing structural details of the hierarchical nature of a source code, complemented by CodeBERT's ability to discern contextual differences between keywords and variable names. This research provides insights into the challenges associated with utilizing programming languages for deep learning models and suggests potential solutions for addressing these issues. The envisioned applications extend to predicting the minimum required version for individual files or an entire code base. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Python

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Investment Planning in the Region 16

Investment Planning in the Region

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16th International Conference Management of Large-Scale System Development, MLSD 2023

作者： Solomatin, Alexander Federal Research Center 'Computer Science and Control' of Ras Department of Mathematical Methods of Regional Programming Moscow Russia

ISBN: (纸本)9798350337907

The principle of multiplicity is introduced for the components of the investment planning process. Some algorithms are given that ensure the process of investment planning at the regional level: the formation of integrated assessments of investment projects, automated generation of projects, multicriteria evaluation and selection of projects, taking into account the mutual influence of projects, optimizing the composition of projects, and taking into account financing restrictions. The features of the program system intended for the formation of plans for the territorial and sectoral development of the region are considered. © 2023 IEEE.

关键词： Regional planning

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Perfecting Nothingness by Refactoring Whitespace 15

Perfecting Nothingness by Refactoring Whitespace

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15th Seminar on Advanced Techniques and Tools for Software Evolution, SATToSE 2023

作者： Witmans, Rutger Zaytsev, Vadim Technical Computer Science University of Twente Enschede Netherlands Formal Methods & Tools University of Twente Enschede Netherlands

In this paper we explore the possibilities of refactoring code in Whitespace, a programming language which only recognises whitespace characters as code, and tolerates textual comments that describe the program. The paper presents a list of possible refactorings applicable to Whitespace, and describes a tool that automates some of these refactorings. The functionality of the tool is demonstrated with concrete examples. Refactoring is a important systematic process of improving code without creating new functionality, improving long-term properties of the code such as readability, maintainability, changeability, testability, extendability and safety. We argue that, despite the lack of real-life applications for Whitespace specifically, it is beneficial to apply refactoring methodology to it, since lessons learnt from esoteric languages can be ported elsewhere — in this case, to assemblers and similarly restrictive software languages. © 2023 Copyright for this paper by its authors.

关键词： Application programs

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