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Deep learning driven interpretable and informed decision making model for brain tumour prediction using explainable AI

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Scientific reports 2025年第1期15卷 19223页

作者： Khan Muhammad Adnan Taher M Ghazal Muhammad Saleem Muhammad Sajid Farooq Chan Yeob Yeun Munir Ahmad Sang-Woong Lee Pattern Recognition and Machine Learning Lab Faculty of Artificial Intelligence and Software Gachon University Seongnam-si 13557 Republic of Korea. Department of Networks and Cybersecurity Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman 19111 Jordan. Chitkara University Institute of Engineering and Technology Chitkara University Rajpura Punjab 140401 India. Department of Cyber Security NASTP Institute of Information Technology Lahore 58810 Pakistan. Center for Secure Cyber-Physical Systems (C2PS) Computer Science Department Khalifa University Abu Dhabi United Arab Emirates. chan.yeun@ku.ac.ae. University College Korea University Seoul 02841 Republic of Korea. Pattern Recognition and Machine Learning Lab Faculty of Artificial Intelligence and Software Gachon University Seongnam-si 13557 Republic of Korea. slee@gachon.ac.kr.

Brain Tumours are highly complex, particularly when it comes to their initial and accurate diagnosis, as this determines patient prognosis. Conventional methods rely on MRI and CT scans and employ generic machine learning techniques, which are heavily dependent on feature extraction and require human intervention. These methods may fail in complex cases and do not produce human-interpretable results, making it difficult for clinicians to trust the model's predictions. Such limitations prolong the diagnostic process and can negatively impact the quality of treatment. The advent of deep learning has made it a powerful tool for complex image analysis tasks, such as detecting brain Tumours, by learning advanced patterns from images. However, deep learning models are often considered "black box" systems, where the reasoning behind predictions remains unclear. To address this issue, the present study applies Explainable AI (XAI) alongside deep learning for accurate and interpretable brain Tumour prediction. XAI enhances model interpretability by identifying key features such as Tumour size, location, and texture, which are crucial for clinicians. This helps build their confidence in the model and enables them to make better-informed decisions. In this research, a deep learning model integrated with XAI is proposed to develop an interpretable framework for brain Tumour prediction. The model is trained on an extensive dataset comprising imaging and clinical data and demonstrates high AUC while leveraging XAI for model explainability and feature selection. The study findings indicate that this approach improves predictive performance, achieving an accuracy of 92.98% and a miss rate of 7.02%. Additionally, interpretability tools such as LIME and Grad-CAM provide clinicians with a clearer understanding of the decision-making process, supporting diagnosis and treatment. This model represents a significant advancement in brain Tumour prediction, with the potential to enhance pat

关键词： Brain tumour CT scans MRI XAI

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Effect of number of versions on receiving high citations

TechRxiv

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TechRxiv 2020年

作者： Ale Ebrahim, Nader Salehi, Hadi Mohammadjafari, Marjan Embi, Mohamed Amin Bakhtiyari, Kaveh Danaee, Mahmoud Shakiba, Masoud Shahbazi-Moghadam, Masoomeh Zavvari, Azam Department of Industrial Engineering Faculty of Engineering Kerman Branch Islamic Azad University Kerman Iran Faculty of Literature and Humanities Najafabad Branch Islamic Azad University Isfahan Najafabad Iran Bangi 43600 Malaysia Department of Computer & Cognitive Science Facultyof Engineering University of Duisburg-Essen Duisburg Germany Department of Electrical Electronics and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Bangi Malaysia University of Malaya Malaysia Faculty of Agriculture Roudehen Branch Islamic Azad University Roudehen Iran Center for Software Technology and Management Faculty of Information Science and Technology Universiti Kebangsaan Malaysia UKM Bangi Selangor 43600 Malaysia Perdana School of Science Technology and Innovation Policy Universiti Teknologi Malaysia Malaysia

Nowadays, the h-index is an index that attempts to measure both the productivity and impact of the published work of a scientist or scholar. The index is based upon the set of the scientist's most cited papers and the number of citations that they have received in other publications. Besides, the most commonly used measure of journal quality is Impact Factor. This is a number which attempts to measure the impact of a journal in terms of the average number of citations to recent articles published in the journal. So, receiving more citation is very important for authors and journals to get high h-index and impact factor. In this paper, we tried to analyses the effect of the number of available version from the web on receive more citations. We analyzed 10162 papers which are published in Scopus database in year 2010. Then we developed a software to collect the number of citations and versions of each paper from Google Scholar automatically. The results show that … © 2020, CC BY.

关键词： Indexing (of information)

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Preface

Studies in Big Data

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Studies in Big Data 2021年 73卷 v-vii页

作者： Chakraborty, Chinmay Banerjee, Amit Kolekar, Maheshkumar H. Garg, Lalit Chakraborty, Basabi Department of Electronics and Communication Engineering Birla Institute of Technology Ranchi Mesra India Department of Electrical Engineering Indian Institute of Technology Patna Patna India Faculty of Software and Information Science Iwate Prefectural University Takizawa Japan Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore Department of Computer Information Systems Faculty of Information and Communication Technology University of Malta Msida Malta

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AMOGA: A Static-Dynamic Model Generation Strategy for Mobile Apps Testing

arXiv

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arXiv 2019年

作者： Salihu, Ibrahim-Anka Ibrahim, Rosziati Ahmed, Bestoun S. Zamli, Kamal Z. Usman, Asmau Department of Software Engineering Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Batu Pahat Johor86400 Malaysia Department of Software Engineering Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Batu Pahat Johor86400 Malaysia Department of Mathematics and Computer Science Karlstad University Karlstad Sweden Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang GambangPahang26300 Malaysia Department of Software Engineering Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Batu Pahat Johor86400 Malaysia

In the past few years, mobile devices have been increasingly replacing traditional computers as their capabilities such as CPU computation, memory, RAM size, and many more, are being enhanced almost to the level of conventional computers. These capabilities are being exploited by mobile apps developers to produce apps that offer more functionalities and optimized performance. To ensure acceptable quality and to meet their specifications (e.g., design), mobile apps need to be tested thoroughly. As the testing process is often tedious, test automation can be the key to alleviating such laborious activities. In the context of the Android-based mobile apps, researchers and practitioners have proposed many approaches to automate the testing process mainly on the creation of the test suite. Although useful, most existing approaches rely on reverse engineering a model of the application under test for test case creation. Often, such approaches exhibit a lack of comprehensiveness as the application model does not capture the dynamic behavior of the applications extensively due to the incompleteness of reverse engineering approaches. To address this issue, this paper proposes AMOGA, a strategy that uses a hybrid, static-dynamic approach for generating user interface model from mobile apps for model-based testing. AMOGA implements a novel crawling technique that uses the event list of UI element associated with each event to dynamically exercise the events ordering at the run-time to explore the applications’ behavior. An experimental evaluation was performed to assess the effectiveness of our strategy by measuring the code coverage and the fault detection capability through the use of mutation testing concept. Results of the experimental assessment showed that AMOGA represents an alternative approach for model-based testing of mobile apps by generating comprehensive models to improve the coverage of the applications. The strategy proved its effectiveness by achieving high co

关键词： Model checking

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Prioritized process test: An alternative to current process testing strategies

arXiv

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arXiv 2019年

作者： Bures, Miroslav Ahmed, Bestoun S. Zamli, Kamal Z. Department of Computer Science Faculty of Electrical Engineering Czech Technical University Karlovo nam. 13 Praha 2 121 35 Czech Republic Department of Mathematics and Computer Science Karlstad University Sweden IBM Center of Excellence Faculty of Computer Systems and Software Engineering University Malaysia Pahang Gambang Malaysia

Testing processes and workows in information and Internet of Things systems is a major part of the typical software testing effort. Consistent and efficient path-based test cases are desired to support these tests. Because certain parts of software system workows have a higher business priority than others, this fact has to be involved in the generation of test cases. In this paper, we propose a Prioritized Process Test (PPT), which is a model-based test case generation algorithm that represents an alternative to currently established algorithms that use directed graphs and test requirements to model the system under test. The PPT accepts a directed multigraph as a model to express priorities, and edge weights are used instead of test requirements. To determine the test-coverage level of test cases, a test-depth-level concept is *** compared the presented PPT with five alternatives (i.e., the Process Cycle Test, a naive reduction of test set created by the Process Cycle Test, Brute Force algorithm, Set-covering Based Solution and Matching-based Prefix Graph Solution) for edge coverage and edge-pair coverage. To assess the optimality of the path-based test cases produced by these strategies, we used fourteen metrics based on the properties of these test cases and 59 models that were created for three real-world systems. For all edge coverage, the PPT produced more optimal test cases than the alternatives in terms of the majority of the metrics. For edge-pair coverage, the PPT strategy yielded similar results to those of the alternatives. Thus, the PPT strategy is an applicable alternative, as it reects both the required test coverage level and the business priority in parallel. Copyright © 2019, The Authors. All rights reserved.

关键词： software testing

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Correction to: Next-generation UWB antennas gadgets for human health care using SAR

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EURASIP Journal on Wireless Communications and Networking 2021年第1期2021卷 1-1页

作者： Ali, Aysha Maryam Al Ghamdi, Mohammed A. Iqbal, Muhammad Munwar Khalid, Shehzad Aldabbas, Hamza Saeed, Saqib University of Engineering and Technology Taxila Pakistan Computer Science Department Umm Al-Qura University Makkah City Saudi Arabia Computer Engineering Department Bahria University Islamabad Pakistan Software Engineering Department Prince Abdullah Bin Ghazi Faculty of Information and Communication Technology Al-Balqa Applied University Al-Salt Jordan Department of Computer Information Systems College of Computer Science and Information Technology Imam Abdulrahman Bin Faisal University Dammam Kingdom of Saudi Arabia

An amendment to this paper has been published and can be accessed via the original article.

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Generation and application of constrained interaction test suites using base forbidden tuples with mixed neighborhood tabu search

arXiv

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arXiv 2019年

作者： Hasan, Imad H. Ahmed, Bestoun S. Potrus, Moayad Y. Zamli, Kamal Z. Erbil44002 Iraq Department of Mathematics and Computer Science Karlstad University Karlstad651 88 Sweden Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Gambang Pahang26300 Malaysia

To ensure the quality of current highly configurable software systems, intensive testing is needed to test all the configuration combinations and detect all the possible faults. This task becomes more challenging for most modern software systems when constraints are given for the configurations. Here, intensive testing is almost impossible, especially considering the additional computation required to resolve the constraints during the test generation process. In addition, this testing process is exhaustive and time-consuming. Combinatorial interaction strategies can systematically reduce the number of test cases to construct a minimal test suite without affecting the effectiveness of the tests. This paper presents a new efficient search-based strategy to generate constrained interaction test suites to cover all possible combinations. The paper also shows a new application of constrained interaction testing in software fault searches. The proposed strategy initially generates the set of all possible t − tuple combinations;then, it filters out the set by removing the forbidden t − tuples using the base forbidden tuple (BFT) approach. The strategy also utilizes a mixed neighborhood tabu search (TS) to construct optimal or near-optimal constrained test suites. The efficiency of the proposed method is evaluated through a comparison against two well-known state-of-the-art tools. The evaluation consists of three sets of experiments for 35 standard benchmarks. Additionally, the effectiveness and quality of the results are assessed using a real-world case study. Experimental results show that the proposed strategy outperforms one of the competitive strategies, ACTS, for approximately 83% of the benchmarks and achieves similar results to CASA for 65% of the benchmarks when the interaction strength is 2. For an interaction strength of 3, the proposed method outperforms other competitive strategies for approximately 60% and 42% of the benchmarks. The proposed strategy can also

关键词： software testing

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A NovelMethod to Improve the Retrieved Multilingual Documents Score

A NovelMethod to Improve the Retrieved Multilingual Document...

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International Conference on computer, Control, Electrical, and Electronics engineering (ICCCEEE)

作者： Abas Aboras Aiman Solyman Albaraa Abobieda Hajer Yousif School of Software Engineering South China University of Technology Guangzhou China Faculty of Computer Studies International University of Africa Khartoum Sudan Department of Computer Systems and Networks Sudan University of Science and Technology SUST Khartoum Sudan

ISBN: (数字)9781728110066

ISBN: (纸本)9781728110073

With an ever-increasing number of resources on the Web, different language resources such as newspapers, magazines, and articles have become available. This demands for an improved technique in the information retrieval to extirpate the communication barrier among languages. Search engines are the cornerstones for informational contents and the link between the two parties of publishing and retrieval of content. Moreover, the search for information is no longer narrowed to users of the native language of the original source. Most of the non-English users such as Arabic speakers are unable to express the terms in their own language. Also, the terminologies written in the native language of the source are acquired from the English language. This challenge drives users to use mixed terms (multilingual terms) to get better results, especially in the scientific domain. This paper attempts to address the problem of documents retrieval using multilingual queries. When users use mixed queries, the results of the multilingual documents will dominate the top of the retrieved documents rather than other relevant documents, and the scores of the mixed documents obtain extra weight values that are not really part of their actual weighting value. This paper proposes a novel method to improve the results of the retrieved documents by adjusting the score of multilingual documents. For experiments, we used a mixed test collection containing mixedlanguage documents (Arabic and English). The results showed that the proposed method led to an enhanced performance in documents retrieval from multilingual queries which made them relevant, effective and accurate thus proving that our approach is more reliable than other traditional approaches.

关键词： Search engines Terminology Mathematical model Search problems Vocabulary Indexes

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Modal regression based structured low-rank matrix recovery for multi-view learning

arXiv

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arXiv 2020年

作者： Xu, Jiamiao Wang, Fangzhao Peng, Qinmu You, Xinge Wang, Shuo Jing, Xiao-Yuan Philip Chen, C.L. School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute China State Key Laboratory of Software Engineering School of Computer Wuhan University China Department of Computer and Information Science Faculty of Science and Technology University of Macau 99999 China Dalian Maritime University Dalian116026 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100080 China

Low-rank Multi-view Subspace Learning (LMvSL) has shown great potential in cross-view classification in recent years. Despite their empirical success, existing LMvSL based methods are incapable of well handling view discrepancy and discriminancy simultaneously, which thus leads to the performance degradation when there is a large discrepancy among multi-view data. To circumvent this drawback, motivated by the block-diagonal representation learning, we propose Structured Low-rank Matrix Recovery (SLMR), a unique method of effectively removing view discrepancy and improving discriminancy through the recovery of structured low-rank matrix. Furthermore, recent low-rank modeling provides a satisfactory solution to address data contaminated by predefined assumptions of noise distribution, such as Gaussian or Laplacian distribution. However, these models are not practical since complicated noise in practice may violate those assumptions and the distribution is generally unknown in advance. To alleviate such limitation, modal regression is elegantly incorporated into the framework of SLMR (term it MR-SLMR). Different from previous LMvSL based methods, our MR-SLMR can handle any zero-mode noise variable that contains a wide range of noise, such as Gaussian noise, random noise and outliers. The alternating direction method of multipliers (ADMM) framework and half-quadratic theory are used to efficiently optimize MR-SLMR. Experimental results on four public databases demonstrate the superiority of MR-SLMR and its robustness to complicated noise. Copyright © 2020, The Authors. All rights reserved.

关键词： Gaussian noise (electronic)

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The simulation on vehicular traffic congestion using discrete event simulation (DES): A case study

The simulation on vehicular traffic congestion using discret...

引用

2018 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2018

作者： Bakar, Noor Akma Abu Adi, Ainil Fahsha Nasrun Majid, Mazlina Abdul Adam, Khalid Younis, Younis M. Fakhreldin, M. Faculty of Computer Systems and Software Engineering University Malaysia Pahang Kuantan Malaysia Faculty of Electric and Electronic Engineering University Malaysia Pahang Kuantan Malaysia College of Internet of Things Engineering Hohai University Nanjing Shi Jiangsu Sheng China Faculty of Computer Science and Information Technology Jazan University Saudi Arabia

ISBN: (纸本)9781538692073

The bottleneck networks of the vehicular traffic flow required the clear understanding and the insights of congestion factors, determines the time and location of traffic breakdown. The congestion propagates through the network caused by the numbers of vehicles continuously growing. There have been lots of research studies to resolve the issues. Simulation and modelling to the related issues seem significance to the operational research specifically the traffic flow dynamic for the design, analysis and the management. Hence, this work focused on a simulation model for the vehicular traffic flow in order to reduce the traffic congestion for a smooth and low-density traffic flow system. Three scenarios from a traffic flow system based on queuing environment which is current traffic flow system as S1, the newly proposed models as S2 and S3 have been suggested to improve the traffic flow of the intersection. The method of comparing the performance of simulation results and difficulties, alternative road, the predictive strategy as decision support model with the potential alternative road has been identified with developing traffic flow simulation using Discrete Event Simulation (DES). DES is as the well-known traditional approach to catering the problems regarding the queuing system and run simulation models on the different traffic scenarios for bottleneck analysis. The lower values for the cumulative average all the parameters indicated the traffic congestion is decreased and to avoid the traffic jam. The experimental results and statistical analysis showed that the proposed simulation model S2 and S3 for vehicular traffic flow is better than the current traffic flow system S1. It can be summarized that model 3 (S3) can be applied to the new vehicular traffic flow system with the better simulation results has been produced from the experimental simulations. © 2018 IEEE.

关键词： Discrete event simulation

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