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International Forum on Medical Imaging in Asia 2021, IFMIA 2021

作者： Huang, Chao-Jung Wu, Tinghui Lu, Jui-Ting Lin, Beatrice Chang, Dawei Wang, Pochuan Wang, Mei-Chi Lee, Peijung Wang, Weichung National Taiwan University-Stanford Joint Program Office of AI in Biotechnology Ministry of Science and Technology Joint Research Center for Artificial Intelligence Technology and All Vista Healthcare Taipei Taiwan Institute of Applied Mathematical Sciences National Taiwan University Taipei Taiwan Department of Mathematics Ecole Normale Supérieure de Lyon Lyon France Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Mathematics National Taiwan University Taipei Taiwan

ISBN: (数字)9781510644212

ISBN: (纸本)9781510644205

Artificial intelligence (AI) training courses often require prerequisites such as calculus or statistics. It is hence challenging to design and develop an introductory AI course for students of secondary education. This research intends to develop a medical AI course, provide high school students with an overview of deep learning applications in medical image analysis, and inspire them to pursue careers in the field of medical AI. We designed a 20-hour course, including lectures and two hands-on projects based on medical image classification. The proposed courses provided medical AI disciplines and built up their knowledge from basic to advanced levels. During the ten-day online courses, all the students were fully engaged and gave us positive feedback. The students endeavored to complete the experimental study in training, testing, and hypothesis of medical images application in the course. Their performance exceeded all expectations, for they did further analysis by tuning different hyperparameters. We designed a course evaluation form, which suggested that the students found it essential and expected to interact with the instructors. The results indicate that combining lectures with hands-on sessions would lead to evidently better achievement in terms of high school students' medical AI knowledge and positive attitudes while addressing real-world problems in the projects. Through this innovative education model, high school students regained their enthusiasm and were encouraged to cultivate their medical AI skills through self-learning while finishing the project. We conclude that this course could be successfully applied to interdisciplinary education in high school. © 2021 SPIE.

关键词： Students

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Sub-structure Characteristic Mode Analysis of Microstrip Antennas Using a Global Multi-trace Formulation

arXiv

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arXiv 2022年

作者： Zhao, Ran Lu, Yuyu Cheng, Guang Shang Zhu, Wei Hu, Jun Bagci, Hakan Chengdu611731 China The Electrical and Computer Engineering Program Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia The Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Hefei230601 China The Anhui Province Key Laboratory of Target Recognition and Feature Extraction Lu’an237010 China Thuwal23955 Saudi Arabia

A characteristic mode (CM) method that relies on a global multi-trace formulation (MTF) of surface integral equations is proposed to compute the modes and the resonance frequencies of microstrip patch antennas with finite dielectric substrates and ground planes. Compared to the coupled formulation of electric field and Poggio-Miller-Chang-Harrington-Wu-Tsai integral equations, global MTF allows for more direct implementation of a sub-structure CM method. This is achieved by representing the coupling of the electromagnetic fields on the substrate and ground plane in the form of a numerical Green function matrix, which yields a more compact generalized eigenvalue equation. The resulting sub-structure CM method avoids the cumbersome computation of the multilayered medium Green function (unlike the CM methods that rely on mixed-potential integral equations) and the volumetric discretization of the substrate (unlike the CM methods that rely on volume-surface integral equations), and numerical results show that it is a reliable and accurate approach to predicting the modal behavior of electromagnetic fields on practical microstrip antennas. Copyright © 2022, The Authors. All rights reserved.

关键词： Microstrip antennas

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Eye-Zheimer: A Deep Transfer Learning Approach of Dementia Detection and Classification from NeuroImaging 7

Eye-Zheimer: A Deep Transfer Learning Approach of Dementia D...

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7th IEEE International Conference on Engineering Technologies and Applied Sciences, ICETAS 2020

作者： Alon, Helcy D. Ligayo, Michael Angelo D. Misola, Maribel A. Sandoval, Allan A. Fontanilla, Marites V. Technological Institute of the Philippines Graduate Program Manila Philippines Quezon City University Department of Electronics Engineering Quezon City Philippines FEU Institute of Technology Department of Computer Engineering Manila Philippines St. Paul University Department of Information Technology Quezon City Philippines

ISBN: (纸本)9780738105048

Dementia is a common term for memory loss, speech, problem-solving, and other cognitive skills that are serious enough to interfere with everyday life, and Alzheimer's is the leading cause of dementia. Alzheimer's disease is presumed to develop 20 years or more before symptoms occur, with degenerative changes that are unapparent to the person affected. The deep learning approach for early detection and Alzheimer's disease classification has recently gained significant attention. This study proposed disease detection trained by utilizing the YOLO v3 algorithm that aims to detect Alzheimer's disease based solely on Magnetic Resonance Imaging (MRI). Pascal VOC format and LabelImg tool are used for annotating the datasets, categorizing the image as non-demented and mild-demented. Model 4 was used in the system having 98.617% training accuracy, 98.8207% validation accuracy, and mAP of 96.17%. To test the accuracy of the used model, images of MRI scans are presented and it recorded 80% testing accuracy. © 2020 IEEE.

关键词： Object detection

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Weakly Supervised Joint Whole-Slide Segmentation and Classification in Prostate Cancer

arXiv

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arXiv 2023年

作者： Pati, Pushpak Jaume, Guillaume Ayadi, Zeineb Thandiackal, Kevin Bozorgtabar, Behzad Gabrani, Maria Goksel, Orcun IBM Research Europe Switzerland Department of Pathology Brigham and Women’s Hospital Harvard Medical School United States Department of Pathology Massachusetts General Hospital Harvard Medical School United States Cancer Program Broad Institute of Harvard MIT United States Data Science Program Dana-Farber Harvard Cancer Center United States Computer-Assisted Applications in Medicine ETH Zurich Switzerland Signal Processing Laboratory 5 EPFL Switzerland EPFL Switzerland Department of Information Technology Uppsala University Sweden

The segmentation and automatic identification of histological regions of diagnostic interest offer a valuable aid to pathologists. However, segmentation methods are hampered by the difficulty of obtaining pixel-level annotations, which are tedious and expensive to obtain for Whole-Slide images (WSI). To remedy this, weakly supervised methods have been developed to exploit the annotations directly available at the image level. However, to our knowledge, none of these techniques is adapted to deal with WSIs. In this paper, we propose WHOLESIGHT, a weakly-supervised method, to simultaneously segment and classify WSIs of arbitrary shapes and sizes. Formally, WHOLESIGHT first constructs a tissue-graph representation of the WSI, where the nodes and edges depict tissue regions and their interactions, respectively. During training, a graph classification head classifies the WSI and produces node-level pseudo labels via post-hoc feature attribution. These pseudo labels are then used to train a node classification head for WSI segmentation. During testing, both heads simultaneously render class prediction and segmentation for an input WSI. We evaluated WHOLESIGHT on three public prostate cancer WSI datasets. Our method achieved state-of-the-art weakly-supervised segmentation performance on all datasets while resulting in better or comparable classification with respect to state-of-the-art weakly-supervised WSI classification methods. Additionally, we quantify the generalization capability of our method in terms of segmentation and classification performance, uncertainty estimation, and model calibration. © 2023, CC BY-NC-ND.

关键词： Image segmentation

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Minimizing Number of Nodes in Decision Trees with Hypotheses

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Procedia computer Science 2021年 192卷 232-240页

作者： Mohammad Azad Igor Chikalov Shahid Hussain Mikhail Moshkov Jouf University College of Computer and Information Sciences Department of Computer Science Sakaka 72441 Saudi Arabia Intel Corporation 5000 W Chandler Blvd Chandler AZ 85226 USA Habib University Dhanani School of Science and Engineering Computer Science Program Karachi 75290 Pakistan King Abdullah University of Science and Technology (KAUST) Computer Electrical and Mathematical Sciences & Engineering Division Thuwal 23955-6900 Saudi Arabia

In this paper, we consider decision trees that use both conventional queries based on one attribute each and queries based on hypotheses about values of all attributes. This approach is similar to one studied in exact learning, where membership and equivalence queries are considered. We propose dynamic programming algorithms for the minimization of the number of nodes in such decision trees and discuss results of computer experiments.

关键词： Decision tree Hypothesis Number of nodes

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Modeling for small cell networks in 5G communication environment

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Telecommunication Systems 2022年第2期80卷 189-214页

作者： Kim, Tae-Yeun Singh, A. K. Ko, Hoon National Program of Excellence in Software Center Chosun University Gwangju Republic of Korea Department of Computer Science and Engineering National Institute of Technology Patna Patna India Research Institute of Computer Information Communications Chungbuk National University E8-7 Chungdae-ro 1 Seowon-ku Chungcheongbuk-do South Korea Instituto Superior de Engenharia do Porto Instituto Politecnico do Porto R. Dr. Antonio Bernardino de Almeida 431 Porto Portugal

The small cell structure in which many cells are arranged per unit area by reducing the size of cells is a candidate technology for an increase in transmission capacity in the 5G environment. However, the decrease in the size of the cell led to additional problems such as increased inter cell interference and frequent cell changes owing to the movement of the terminal. Therefore, the aim of this study was to propose small cell dynamic channel allocation (SDCA) and hybrid and dynamic channel allocation (HDCA) using conventional reuse methods to improve the macro cell performance while efficiently utilizing scarce frequency resources. The proposed method facilitates an improved performance that is lacking for macro-cell users in the center area of the cell boundary for the network where conventional macro cells and small cells are superposed. Furthermore, to improve the performance, it can provide resources that are lacking in the small cells of the center. To evaluate the performance, the proposed method was compared to frequency reuse factor1 (FRF1), frequency reuse factor3 (FRF3), and fractional frequency reuse (FFR) methods in terms of the signal-to-interference/noise-ratio (SINR) of users of each macro cell and small cell, outage, capacity for each user, and total system capacity. As a result of comparing the SINR, it was confirmed that the performance of the macro cell users has improved by an average of 43.88% compared to FRF1, FRF3, and FFR, and the performance of small cell users has improved by an average of 4.31%. Comparison results show that the outage proportions of the macro and small cell users are 61.29% and 70.59% lower on average, respectively. A comparison of results show that the capacities of the macro and small cell users have also improved by 22.5% and 14.5% on average, respectively. As the comparison results of the total system capacity indicate, the proposed method shows an average improvement of 11.67%. In cases in which the added resources o

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Phase transition in magic with random quantum circuits

arXiv

引用

arXiv 2023年

作者： Niroula, Pradeep White, Christopher David Wang, Qingfeng Johri, Sonika Zhu, Daiwei Monroe, Christopher Noel, Crystal Gullans, Michael J. Joint Center for Quantum Information and Computer Science University of Maryland and NIST College ParkMD20742 United States Joint Quantum Institute University of Maryland and NIST College ParkMD20742 United States Chemical Physics Program Institute for Physical Science and Technology University of Maryland College ParkMD20742 United States IonQ Inc. College ParkMD20740 United States Duke Quantum Center Department of Electrical & Computer Engineering Department of Physics Duke University DurhamNC27701 United States

Magic is a property of quantum states that enables universal fault-tolerant quantum computing using simple sets of gate operations. Understanding the mechanisms by which magic is created or destroyed is, therefore, a crucial step towards efficient and practical fault-tolerant computation. We observe that a random stabilizer code subject to coherent errors exhibits a phase transition in magic, which we characterize through analytic, numeric and experimental probes. Below a critical error rate, stabilizer syndrome measurements remove the accumulated magic in the circuit, effectively protecting against coherent errors;above the critical error rate syndrome measurements concentrate magic. A better understanding of such rich behavior in the resource theory of magic could shed more light on origins of quantum speedup and pave pathways for more efficient magic state generation. © 2023, CC BY.

关键词： Random errors

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A Reduced Features of Public Health Development Index by Using Clustering Methods 4

A Reduced Features of Public Health Development Index by Usi...

引用

4th International Conference on Informatics and Computing, ICIC 2019

作者： Adi Darmawan, Muhammad Prihandoko Gunadarma University Technology and Engineering Program Depok Indonesia Gunadarma University Department of Computer Science and Information Technology Depok Indonesia

ISBN: (纸本)9781728122076

Public Health Development Index (PHDI) is an index that released by Ministry of Health of The Republic of Indonesia which is used to measure the health of Indonesian people. The PHDI is divided into seven categories and measured by using 30 features. There are 497 cities that contributed to PHDI 2013. The problem emerged is that not all the cities have those 30 features required by PHDI. The objective of this paper is to reduce PHDI features with various Feature Selection For Clustering (FSFC) method. The subset of features resulted from FSFC method is then used to generate two types of clusters, i.e. k-means and DBSCAN clustering. The clusters generated from k-means and DBSCAN techniques will be evaluated by using internal and external validation method. The subset of features is then compared with the original ranking of PHDI. Experimental results show that the results of each FSFC method producing a different rank compared to the original rank of PHDI. This result concludes that all the features that are used to measure PHDI are important to be included in the process of calculation. © 2019 IEEE.

关键词： Feature Selection

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Technical debt and agile software development practices and processes: An industry practitioner survey

arXiv

引用

arXiv 2021年

作者： Holvitie, Johannes Licorish, Sherlock A. Spínola, Rodrigo O. Hyrynsalmi, Sami MacDonell, Stephen G. Mendes, Thiago S. Buchan, Jim Leppänen, Ville Turku Centre for Computer Science Software Development Laboratory Turku Finland University of Turku Department of Information Technology Turku Finland University of Otago Department of Information Science Otago Dunedin New Zealand Salvador University Graduate Program in Systems and Computer Bahia Salvador Brazil Federal University of Bahia Fraunhofer Project Center for Software and System Engineering Salvador Brazil Tampere University of Technology Pori Campus Pori Finland Federal Institute of Bahia Information Technology Department Bahia Santo Amaro Brazil Auckland University of Technology School of Engineering Computer and Mathematical Sciences Auckland New Zealand

Context: Contemporary software development is typically conducted in dynamic, resource-scarce environments that are prone to the accumulation of technical debt. While this general phenomenon is acknowledged, what remains unknown is how technical debt specifically manifests in and affects software processes, and how the software development techniques employed accommodate or mitigate the presence of this debt. Objectives: We sought to draw on practitioner insights and experiences in order to classify the effects of agile method use on technical debt management, given the popularity and perceived success of agile methods. We explore the breadth of practitioners' knowledge about technical debt;how technical debt is manifested across the software process;and the perceived effects of common agile software development practices and processes on technical debt. In doing so, we address a research gap in technical debt knowledge and provide novel and actionable managerial recommendations. Method: We designed, tested and executed a multi-national survey questionnaire to address our objectives, receiving 184 responses from practitioners in Brazil, Finland, and New Zealand. Results: Our findings indicate that: 1) Practitioners are aware of technical debt, although, there was under utilization of the concept, 2) Technical debt commonly resides in legacy systems, however, concrete instances of technical debt are hard to conceptualize which makes it problematic to manage, 3) Queried agile practices and processes help to reduce technical debt;in particular, techniques that verify and maintain the structure and clarity of implemented artifacts (e.g., Coding standards and Refactoring) positively affect technical debt management. Conclusions: The fact that technical debt instances tend to have characteristics in common means that a systematic approach to its management is feasible. However, notwithstanding the positive effects of some agile practices on technical debt management, comp

关键词： Legacy systems

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Benefits and drawbacks of radiofrequency ablation via percutaneous or minimally invasive surgery for treating hepatocellular carcinoma

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World Journal of Gastrointestinal Surgery 2024年第11期16卷 3400-3407页

作者： Ching-Lung Hsieh Cheng-Ming Peng Chun-Wen Chen Chang-Hsien Liu Chih-Tao Teng Yi-Jui Liu Department of Computer Science and Information Engineering Feng Chia UniversityTaichung 40724Taiwan Department of Surgery Chung Shan Medical University HospitalTaichung 40201Taiwan School of Medicine Chung Shan Medical UniversityTaichung 40201Taiwan Department of Radiology Taichung Armed Forces General HospitalTaichung 406Taiwan Department of Medical Imaging and Radiological Sciences Central Taiwan University of Science and TechnologyTaichung 406Taiwan Department of Radiology School of MedicineNational Defense Medical CenterTaipei 11490Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital and China Medical UniversityHsinchu 302Taiwan Institute of Nuclear Engineering and Science National Tsing Hua UniversityHsinchu 300Taiwan Department of Radiology Nantou Hospital of the Ministry of Health and WelfareNantou 540Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia UniversityTaichung 407Taiwan Department of Automatic Control Engineering Feng Chia UniversityTaichung 407Taiwan

The management of early stage hepatocellular carcinoma(HCC)presents significant *** radiofrequency ablation(RFA)has shown safety and effectiveness in treating HCC,with lower mortality rates and shorter hospital stays,its high recurrence rate remains a significant ***,achieving improved survival solely through RFA is challenging,particularly in retrospective studies with inherent *** is commonly used for guiding percutaneous RFA,but its low contrast can lead to missed tumors and the risk of HCC *** enhance the efficiency of ultrasound-guided percutaneous RFA,various techniques such as artificial ascites and contrast-enhanced ultrasound have been developed to facilitate complete tumor *** invasive surgery(MIS)offers advantages over open surgery and has gained traction in various surgical *** studies suggest that laparoscopic intraoperative RFA(IORFA)may be more effective than percutaneous RFA in terms of survival for HCC patients unsuitable for surgery,highlighting its ***,combining MIS-IORFA with these enhanced percutaneous RFA techniques may hold greater significance for HCC treatment using the MIS-IORFA *** article reviews liver resection and RFA in HCC treatment,comparing their merits and proposing a trajectory involving their combination in future therapy.

关键词： Percutaneous radiofrequency ablation Minimally invasive surgery Hepatocellular carcinoma Intraoperative radiofrequency ablation Contrast-enhanced ultrasound

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