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Quantum Computing and Engineering (QCE), IEEE International Conference on

作者： Yu-Ching Chen Chih-Yu Chen Tsung-Wei Huang Chia-Ho Ou Master Program in Intelligent Computing and Big Data Chung Yuan Christian University Taoyuan Taiwan Quantum Information Center Chung Yuan Christian University Taoyuan Taiwan Department of Computer Science and Information Engineering National Pingtung University Pingtung Taiwan

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

Electrocardiograms (ECGs) are crucial for detecting cardiac diseases like atrial fibrillation (AF). Traditional analysis methods like fast Fourier transform (FFT) face challenges with increasing data complexity. This study uses Taipei Veterans General Hospital data to explore quantum Fourier transform (QFT) for ECG analysis. Results show that QFT effectively analyzes ECG signals, matching FFT performance while benefiting from quantum computing's efficiency.

关键词： Heart Quantum computing Fast Fourier transforms Hospitals High performance computing Atrial fibrillation Machine learning Electrocardiography Real-time systems Signal analysis

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The largest genome-wide association study for breast cancer in Taiwanese Han population

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Breast Cancer Research and Treatment 2024年第2期203卷 291-306页

作者： Hsu, Yu-Ching Chen, Hung-Lin Cheng, Chi-Fung Chattopadhyay, Amrita Chen, Pei-Shan Lin, Che-Chen Chiang, Hsiu-Yin Liu, Ting-Yuan Huang, Chi-Hao Kuo, Chin-Chi Chuang, Eric Y. Lu, Tzu-Pin Tsai, Fuu-Jen Bioinformatics Program Taiwan International Graduate Program National Taiwan University Taipei Taiwan Bioinformatics Program Institute of Statistical Science Taiwan International Graduate Program Academia Sinica Taipei Taiwan Institute of Health Data Analytics and Statistics Department of Public Health College of Public Health National Taiwan University Taipei Taiwan Big Data Center China Medical University Hospital Taichung Taiwan Center for Translational Genomic Research Department of Medical Research China Medical University Hospital Taichung Taiwan Million-Person Precision Medicine Initiative Department of Medical Research China Medical University Hospital Taichung Taiwan Division of Breast Surgery Department of Surgery China Medical University Hospital Taichung Taiwan Division of Nephrology Department of Internal Medicine China Medical University Hospital Taichung Taiwan Department of Medical Research China Medical University Hospital Taichung Taiwan Bioinformatics and Biostatistics Core Center of Genomic and Precision Medicine National Taiwan University Taipei Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Biomedical Technology and Device Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan Genetic Center Department of Medical Research China Medical University Hospital Taichung Taiwan

Purpose: Breast cancer is a molecularly heterogeneous disease, and multiple genetic variants contribute to its development and prognosis. Most of previous genome-wide association studies (GWASs) and polygenic risk scores (PRSs) analyses focused on studying breast cancers of Caucasian populations, which may not be applicable to other population. Therefore, we conducted the largest breast cancer cohort of Taiwanese population to fill in the knowledge gap. Methods: A total of 152,534 Participants recruited by China Medical University Hospital between 2003 and 2019 were filtered by several patient selection criteria and GWAS quality control steps, resulting in the inclusion of 2496 cases and 9984 controls for this study. We then conducted GWAS for all breast cancers and PRS analyses for all breast cancers and the four breast cancer subtypes, including luminal A, luminal B, basal-like, and HER2-enriched. Results: The GWAS analyses identified 113 SNPs, 50 of which were novel. The PRS models for all breast cancers and the luminal A subtype showed positively correlated trends between the PRS and the risk of developing breast cancer. The odds ratios (95% confidence intervals) for the groups with the highest PRS in all breast cancers and the luminal A subtype were 5.33 (3.79–7.66) and 3.55 (2.13–6.14), respectively. Conclusion: In summary, we explored the association of genetic variants with breast cancer in the largest Taiwanese cohort and developed two PRS models that can predict the risk of developing any breast cancer and the luminal A subtype in Taiwanese women. © 2023, The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature.

关键词： Breast cancer Genome-wide association study Polygenic risk score Taiwanese population

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Quantum-Inspired Acceleration for Image Reconstruction on Ising Machines

Quantum-Inspired Acceleration for Image Reconstruction on Is...

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Quantum Computing and Engineering (QCE), IEEE International Conference on

作者： Yen-Jui Chang Hao-Yuan Chen Ying Chang Lu Lien-Po Yu Chao-Ming Fu Ching-Ray Chang Master Program in Intelligent Computing and Big Data Chung Yuan Christian University Taoyuan City Taiwan Department of Physics National Taiwan University Taipei Taiwan Fujitsu Taiwan Ltd. Taipei Taiwan Department of Computer Science University of London London United Kingdom Institute for Information Industry Taipei Taiwan Fo Guang University Yilan Taiwan Quantum Information Center Chung Yuan Christian University Taoyuan City Taiwan

The study investigates a quantum-inspired approach to image reconstruction using Ising machines and demonstrates its significant improvements over the contrastive divergence method in Restricted Boltzmann Machines tra... 详细信息

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

关键词： Training Quantum computing Image reconstruction

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APPLICATION OF THE DIGITAL ANNEALER UNIT IN OPTIMIZING CHEMICAL REACTION CONDITIONS FOR ENHANCED PRODUCTION YIELDS

arXiv

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arXiv 2024年

作者： Li, Shih-Cheng Wang, Pei-Hwa Su, Jheng-Wei Chiang, Wei-Yin Huang, Shih-Hsien Lin, Yen-Chu Ou, Chia-Ho Chen, Chih-Yu Insilico Medicine Taiwan Ltd. Taipei City110208 Taiwan Department of Chemical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Quantum Information Center Chung Yuan Christian University Taoyuan City320314 Taiwan Master Program in Intelligent Computing and Big Data Chung Yuan Christian University Taoyuan City320314 Taiwan Department of Computer Science and Information Engineering National Pingtung University Pingtung City900392 Taiwan

Finding appropriate reaction conditions that yield high product rates in chemical synthesis is crucial for the chemical and pharmaceutical industries. However, due to the vast chemical space, conducting experiments for each possible reaction condition is impractical. Consequently, models such as QSAR (Quantitative Structure-Activity Relationship) or ML (Machine Learning) have been developed to predict the outcomes of reactions and illustrate how reaction conditions affect product yield. Despite these advancements, inferring all possible combinations remains computationally prohibitive when using a conventional CPU. In this work, we explore using a Digital Annealing Unit (DAU) to tackle these large-scale optimization problems more efficiently by solving Quadratic Unconstrained Binary Optimization (QUBO). Two types of QUBO models are constructed in this work: one using quantum annealing and the other using ML. Both models are built and tested on four high-throughput experimentation (HTE) datasets and selected Reaxys datasets. Our results suggest that the performance of models is comparable to classical ML methods (i.e., Random Forest and Multilayer Perceptron (MLP)), while the inference time of our models requires only seconds with a DAU. Additionally, in campaigns involving active learning and autonomous design of reaction conditions to achieve higher reaction yield, our model demonstrates significant improvements by adding new data, showing promise of adopting our method in the iterative nature of such problem settings. Our method can also accelerate the screening of billions of reaction conditions, achieving speeds millions of times faster than traditional computing units in identifying superior conditions. Therefore, leveraging the DAU with our developed QUBO models has the potential to be a valuable tool for innovative chemical synthesis. Copyright © 2024, The Authors. All rights reserved.

关键词： Machine learning

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Trends and sex-specific incidence of upper urinary tract cancer in Taiwan: A birth cohort study

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Cancer medicine 2023年第14期12卷 15350-15357页

作者： Yu-Hsuan Chang Wan-Lun Hsu Yu-Kwang Lee Chun-Ju Chiang Ya-Wen Yang San-Lin You Yong-Chen Chen Tai-Shuan Lai School of Medicine Fu-Jen Catholic University New Taipei City Taiwan. Data Science Center College of Medicine Fu-Jen Catholic University New Taipei City Taiwan. Master Program of Big Data Analysis in Biomedicine College of Medicine Fu-Jen Catholic University New Taipei City Taiwan. Department of Surgery Division of General Surgery National Taiwan University Hospital Taipei Taiwan. Graduate Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei Taiwan. Department of Internal Medicine National Taiwan University Hospital Taipei Taiwan. Department of Internal Medicine College of Medicine National Taiwan University Taipei Taiwan.

BACKGROUND:Taiwan has one of the highest incidences of upper tract urothelial cancer (UTUC) worldwide, especially in women; however, no nationwide, long-term follow-up study has evaluated this. METHODS:We investigated the incidence of UTUC in Taiwan using data from the national population-based Taiwan Cancer Registry database (1985-2019). We divided the birth cohort into nine 5-year age groups and calculated the age-specific incidence for these groups according to the corresponding birth years. RESULTS:The average annual percent change in the incidence of renal pelvis cancer from 1985 to 2019 showed sex-specific differences, with 3.5% and 5.3% increases in the incidences in men and women, respectively. The age-specific incidence rate for renal pelvis cancer among women showed a gradual increase in the group with older women as well as an increase over time in each age group. The results of a birth cohort analysis revealed that younger cohorts had higher incidence rates of renal pelvis cancer than older cohorts did. CONCLUSION:We demonstrated that the incidence of UTUC is unusually high among older Taiwanese women and that younger cohorts have a high risk of UTUC than older cohorts.

关键词： age period cohort incidence sex upper tract urothelial cancer

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big data: Prospects and Challenges

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Vikalpa 2015年第1期40卷 74 - 96页

作者： Janakiraman Moorthy Rangin Lahiri Neelanjan Biswas Dipyaman Sanyal Jayanthi Ranjan Krishnadas Nanath Pulak Ghosh (Coordinator) Director and Professor of Marketing at the Institute of Management Technology Dubai. Earlier he was Professor of Marketing at the IIM Calcutta and IIM Lucknow. He received his PhD from IIM Ahmedabad. His recent research papers were published in the leading scholarly ournals such as Marketing Science British Food Journal Journal of Information Technology Case and Application Research Journal of Database Marketing & Customer Strategy Management. He has wide experience in the banking and investment industry. He was earlier the Global Research and Project Director of the Institute for Customer Relationship Management Atlanta USA. He was the Convener of the prestigious CAT Exam 2011. e-mail: Practice Director leading Atos India's CRM practice while supporting Strategic Business Development for North American Market. With an experience of more than 15 years Rangin has worked extensively as a Business Consultant in Information Technology (Sales Automation Marketing & Service Management area) Customer Data Management and CRM Analytics. e-mail: Business Consultant at Atos with extensive experience in Business Analysis Risk Management Analytics Business Development Presales Solution Ideation on Enterprise Data Management Enterprise Reference Data and Master Data Management area. e-mail: founder and CEO of dono consulting a boutique quantitative analytics and investment research firm. He has worked for leading financial firms in New York and India including Dow Jones Blackstone Sorin Capital (VP Quantitative Modeling) and Thomson Reuters (Head of Real Estate Analytics). A CFA charter holder and Commonwealth Scholar Deep has an MS (Applied Economics) from University of Texas Dallas and an MA (Economics) from Jadavpur University e-mail: Professor in the Information Systems Group of the Institute of Management Technology Ghaziabad. Her PhD is in the field of data mining from Jamia Millia Islamia Central University India. She has published five edited books. She is serving on the editorial b

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Efficient Bitcoin Address Classification Using Quantum-Inspired Feature Selection

arXiv

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arXiv 2024年

作者： Sie, Ming-Fong Chang, Yen-Jui Lin, Chien-Lung Chang, Ching-Ray Liao, Shih-Wei Department of Computer Science and Information Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Rd. Taipei City10617 Taiwan Master Program in Intelligent Computing and Big Data Chung Yuan Christian University No. 499 Xingzhong N. Rd. Taoyuan City320317 Taiwan Department of Physics National Taiwan University Taiwan Quantum Information Center Chung Yuan Christian University No. 499 Xingzhong N. Rd. Taoyuan City320317 Taiwan

Over 900 million Bitcoin transactions have been recorded, posing considerable challenges for machine learning regarding computation time and maintaining prediction accuracy. We propose an innovative approach using quantum-inspired algorithms implemented with Simulated Annealing and Quantum Annealing to address the challenge of local minima in solution spaces. This method efficiently identifies key features linked to mixer addresses, significantly reducing model training time. By categorizing Bitcoin addresses into six classes—exchanges, faucets, gambling, marketplaces, mixers, and mining pools—and applying supervised learning methods, our results demonstrate that feature selection with SA reduced training time by 30.3% compared to using all features in a random forest model while maintaining a 91% F1-score for mixer addresses. This highlights the potential of quantum-inspired algorithms to swiftly and accurately identify high-risk Bitcoin addresses based on transaction features. © 2024, CC BY.

关键词： Simulated annealing

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Projected Time for the Elimination of Cervical Cancer Under Various Intervention Scenarios: Age-Period-Cohort Macrosimulation Study

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JMIR Public Health and Surveillance 2024年 10卷 e46360页

作者： Chen, Yi-Chu Chen, Yun-Yuan Su, Shih-Yung Jhuang, Jing-Rong Chiang, Chun-Ju Yang, Ya-Wen Lin, Li-Ju Wu, Chao-Chun Lee, Wen-Chung Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei Taiwan Head Office Taiwan Blood Services Foundation Taipei Taiwan Master Program in Statistics National Taiwan University Taipei Taiwan Institute of Statistical Science Academia Sinica Taipei Taiwan Taiwan Cancer Registry Taipei city Taiwan Health Promotion Administration Ministry of Health and Welfare Taipei Taiwan Institute of Health Data Analytics College of Public Health National Taiwan University Taipei Taiwan

BACKGROUND: The World Health Organization aims for the global elimination of cervical cancer, necessitating modeling studies to forecast long-term outcomes. OBJECTIVE: This paper introduces a macrosimulation framework using age-period-cohort modeling and population attributable fractions to predict the timeline for eliminating cervical cancer in Taiwan. METHODS: data for cervical cancer cases from 1997 to 2016 were obtained from the Taiwan Cancer Registry. Future incidence rates under the current approach and various intervention strategies, such as scaled-up screening (cytology based or human papillomavirus [HPV] based) and HPV vaccination, were projected. RESULTS: Our projections indicate that Taiwan could eliminate cervical cancer by 2050 with either 70% compliance in cytology-based or HPV-based screening or 90% HPV vaccination coverage. The years projected for elimination are 2047 and 2035 for cytology-based and HPV-based screening, respectively;2050 for vaccination alone;and 2038 and 2033 for combined screening and vaccination approaches. CONCLUSIONS: The age-period-cohort macrosimulation framework offers a valuable policy analysis tool for cervical cancer control. Our findings can inform strategies in other high-incidence countries, serving as a benchmark for global efforts to eliminate the disease. ©Yi-Chu Chen, Yun-Yuan Chen, Shih-Yung Su, Jing-Rong Jhuang, Chun-Ju Chiang, Ya-Wen Yang, Li-Ju Lin, Chao-Chun Wu, Wen-Chung Lee. Originally published in JMIR Public Health and Surveillance (https://***), 18.04.2024.

关键词： Age-period-cohort model Cancer screening Cervical cancer Cervical screening HPV Human papillomavirus Intervention Macrosimulation Population attributable fraction Public health intervention Women

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MOOCs – international information and education phenomenon?

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Bulletin of the Association for Information science and Technology 2014年第5期40卷

作者： Lee Wilson Anatoliy Gruzd Graduate Student School of Information Management in the master of library and information studies program at Dalhousie University. He is currently working as a research assistant at the Dalhousie Social Media Lab working on a SSHRC funded Insight grant project entitled “Learning Analytics for the Social Media Age” Associate Professor School of Information Management director of the Social Media Lab at the Faculty of Management and cross-appointed to the Faculty of Computer Science at Dalhousie University Canada. He is also a co-editor of a new multidisciplinary journal on Big Data and Society to be published by Sage and a member of the Institute for Big Data Analytics at Dalhousie University

EDITOR'S SUMMARY Since the 1990s massive open online courses (MOOCs) have offered web-based learning on a large scale and with open access. The leading MOOC providers in 2014 – Udemy, Coursera and edX – vary in detail but share the goal of facilitating learning for unlimited audiences at no cost or minimal charge, overcoming socioeconomic hurdles and opening education to all. The potential is strong, and data shows promising registration figures from India and economically developing countries. Yet MOOCs fall short of their goal of widespread and readily accessed education, impeded by technology challenges, lack of basic education and predominance of English as the language of instruction. Maintaining a high standard of educational quality is challenging, and attrition rates are very high. Those in library and information science can facilitate learning through MOOCs and also benefit by using the platform to build awareness of the professional field.

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Surveillance of Multidrug-Resistant Bacterial Infections in Non-Adult Patients-Zhejiang Province,China,2014-2019

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China CDC weekly 2021年第47期3卷 1005-1013,I0004页

作者： Yuchen Wu Shi Chen Jiaping Li Chang Cai Hanyu Wang Mingming Zhou Junmin Cao Qiang Wang Shenghai Wu Shibiao Ding Xiaofei Zhao Long Sun Qingfeng Hu Hongwei Zhou Xiang Qian Qing Yang Sheng Chen Rong Zhang Department of Clinical Laboratory the Second Affiliated Hospital of Zhejiang UniversityZhejiang UniversityHangzhouZhejiangChina Clinical Microbiology Laboratory the Third People’s Hospital of HangzhouHangzhouZhejiangChina China Australia Joint Laboratory for Animal Health Big Data Analytics College of Animal Science and TechnologyZhejiang Agricultural and Forestry UniversityHangzhouZhejiangChina Master of Science New Jersey Institute of TechnologyNewarkNew Jerseythe United States of America National Clinical Research Center for Child Health the Children’s HospitalZhejiang University School of MedicineHangzhouZhejiangChina Department of Hospital Infection Control Zhejiang Provincial Hospital of Traditional Chinese MedicineHangzhouZhejiangChina Department of Clinical Laboratory the Second Affiliated Hospital of Zhejiang Chinese Medical UniversityHangzhouZhejiangChina Department of Laboratory Medicine the First Affiliated People’s Hospital of HangzhouZhejiang University School of MedicineHangzhouZhejiangChina Hangzhou Red Cross Hospital HangzhouZhejiangChina Department of Clinical Laboratory the Affiliated Hospital of Hangzhou Normal UniversityHangzhouZhejiangChina Department of Clinical Laboratory Hangzhou Women’s HospitalHangzhou Maternity and Child Health Care HospitalHangzhouZhejiangChina Clinical Diagnostic Laboratory People’s Hospital of ZhejiangHangzhouZhejiangChina Department of Clinical Laboratory Hangzhou Hospital of Traditional Chinese MedicineHangzhouZhejiangChina The First Affiliated Hospital of Zhejiang University Zhejiang UniversityHangzhouZhejiangChina Department of Infectious Diseases and Public Health Jockey Club College of Veterinary Medicine and Life SciencesCity University of Hong KongHong Kong Special Administrative RegionChina

ABSTRACT Introduction:Antimicrobial resistance has become a major public health threat *** prevalence of multidrug-resistant(MDR)bacterial infections increased substantially among inpatients under 18 years of age in recent *** Zhejiang Province,China,the trends of drug-resistance in non-adult patients from 2014 to 2019 were monitored,aiming to determine the variation patterns and epidemiological features of MDR strains.

关键词： globally threat Zhejiang

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