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Osteoarthritis and Cartilage Open 2025年第3期7卷 100621-100621页

作者： Roberts, Jack B. Rockel, Jason S. Mulders, Rick Capellini, Terence D. Appleton, C. Thomas Phanstiel, Douglas H. Lories, Rik Geurts, Jeroen Ali, Shabana Amanda Bhutani, Nidhi Stone, Laura Cruz-Almeida, Yenisel Jurisica, Igor Boer, Cindy G. Ramos, Yolande F.M. Rice, Sarah J. Kapoor, Mohit Biosciences Institute Newcastle University Newcastle upon Tyne United Kingdom Division of Orthopedics Osteoarthritis Research Program Schroeder Arthritis Institute University Health Network and Krembil Research Institute University Health Network Toronto ON Canada Department of Medical Biophysics and Computer Science University of Toronto Toronto ON Canada Department of Biomedical Data Sciences Section Molecular Epidemiology Leiden University Medical Center Leiden Netherlands Department of Human Evolutionary Biology Harvard University Cambridge MA United States Bone and Joint Institute and Department of Medicine Schulich School of Medicine and Dentistry Western University London Canada Curriculum in Bioinformatics and Computational Biology University of North Carolina Chapel Hill NC United States Laboratory of Tissue Homeostasis and Disease Skeletal Biology and Engineering Research Centre Department of Development and Regeneration KU Leuven Leuven Belgium Division of Rheumatology University Hospitals Leuven Leuven Belgium Rheumatology Department of Musculoskeletal Medicine Lausanne University Hospital and University of Lausanne (CHUV-UNIL) Lausanne Switzerland Bone and Joint Center Henry Ford Health + Michigan State University Health Sciences Detroit MI United States Department of Orthopaedic Surgery Stanford School of Medicine Stanford CA United States Department of Anesthesiology School of Medicine University of Minnesota Minneapolis MN United States Pain Research and Intervention Center of Excellence (PRICE) at the University of Florida Gainesville FL United States Department of Internal Medicine Genomics Medicine Center Erasmus MC University Medical Center Rotterdam Netherlands Department of Laboratory Medicine and Pathobiology University of Toronto Toronto ON Canada Department of Surgery University of Toronto Toronto ON Canada

Objective: Osteoarthritis (OA) is a chronic, degenerative disease of the articular joints. The disease presents an enormous clinical and economic burden globally, due in part to the lack of disease modifying therapies. For over a decade, OA researchers have been working to determine epigenetic mechanisms underlying the disease to better understand pathology, identify biomarkers of progression, and pinpoint novel targets for therapeutic intervention. Design: This article presents a summary of the 3rd International Workshop on the Epigenetics of Osteoarthritis held in Toronto, Ontario, Canada, in September 2024. The purpose of this meeting was to gather the international community to discuss the status of OA epigenetic research and share expertise on innovative techniques for future. Results: Since the two previous meetings, there has been increasing adoption of advanced single-cell and spatial sequencing technologies and bioinfomatic analyses. Furthermore, investigations of multiple joint tissues has highlighted the shifting paradigm from OA as a cartilage centric disease to the consideration of all joint tissues. Conclusions: The workshop provided a unique opportunity for early-career researchers to expand their network, and for all participants to discuss new or improved approaches to advance the field, including international consortia and data sharing. The highlights and outcomes from this OA epigenetics workshop are described in this report. © 2025 The Authors

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The Brain Tumor Segmentation in Pediatrics (BraTS-PEDs) Challenge: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)

arXiv

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arXiv 2024年

作者： Kazerooni, Anahita Fathi Khalili, Nastaran Liu, Xinyang Gandhi, Deep Jiang, Zhifan Anwar, Syed Muhammed Albrecht, Jake Adewole, Maruf Anazodo, Udunna Anderson, Hannah Baid, Ujjwal Bergquist, Timothy Borja, Austin J. Calabrese, Evan Chung, Verena Conte, Gian-Marco Dako, Farouk Eddy, James Ezhov, Ivan Familiar, Ariana Farahani, Keyvan Franson, Andrea Gottipati, Anurag Haldar, Shuvanjan Iglesias, Juan Eugenio Janas, Anastasia Johansen, Elaine Jones, Blaise V. Khalili, Neda Kofler, Florian LaBella, Dominic Lai, Hollie Anne Van Leemput, Koen Li, Hongwei Bran Maleki, Nazanin McAllister, Aaron S. Meier, Zeke Menze, Bjoern Moawad, Ahmed W. Nandolia, Khanak K. Pavaine, Julija Piraud, Marie Poussaint, Tina Prabhu, Sanjay P. Reitman, Zachary Rudie, Jeffrey D. Sanchez-Montano, Mariana Shaikh, Ibraheem Salman Sheth, Nakul Tu, Wenxin Wang, Chunhao Ware, Jeffrey B. Wiestler, Benedikt Zapaishchykova, Anna Bornhorst, Miriam Deutsch, Michelle Fouladi, Maryam Lazow, Margot Mikael, Leonie Hummel, Trent Kann, Benjamin de Blank, Peter Hoffman, Lindsey Aboian, Mariam Nabavizadeh, Ali Packer, Roger Bakas, Spyridon Resnick, Adam Rood, Brian Vossough, Arastoo Linguraru, Marius George Children’s Hospital of Philadelphia PhiladelphiaPA United States Department of Neurosurgery University of Pennsylvania PhiladelphiaPA United States University of Pennsylvania PhiladelphiaPA United States Sheikh Zayed Institute for Pediatric Surgical Innovation Children’s National Hospital WashingtonDC United States Sage Bionetworks United States Lab Crestview Radiology Lagos Nigeria McGill University MontrealQC Canada Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Division of Computational Pathology Department of Pathology and Laboratory Medicine Indiana University School of Medicine IndianapolisIN United States Department of Neurosurgery The University of Southern California CA United States Department of Radiology Duke University Medical Center DurhamNC United States Mayo Clinic MN United States Center for Global Health Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Informatics Technical University Munich Germany TranslaTUM - Central Institute for Translational Cancer Research Technical University of Munich Germany Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD United States C. S. Mott Children’s Hospital University of Michigan MI United States Biomedical Engineering Rutgers University New BrunswickNJ United States Athinoula A Martinos Center for Biomedical Imaging Massachusetts General Hospital BostonMA United States Yale University New HavenCT United States PrecisionFDA U.S. Food and Drug Administration Silver SpringMD United States Cincinnati Children’s Hospital Medical Center OH United States Helmholtz AI Helmholtz Munich Germany Department of Radiation Oncology Duke University Medical Center DurhamNC United States Department of Radiology Children’s Health Orange County CA United States Department of Applied Mathematics and Computer Science Technical University of De

关键词： Deep learning

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Market Basket Analysis Using Apriori and FP-Growth for Analysis Consumer Expenditure Patterns at Berkah Mart in Pekanbaru Riau

Market Basket Analysis Using Apriori and FP-Growth for Analy...

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2018 Workshop on Multidisciplinary and Its Applications: Applied Mathematics, computer science, Information Systems, and Information Technology, WMA-Mathcomtech 2018

作者： Mustakim Herianda, Della Maulina Ilham, Ahmad Daeng Gs, Achmad Laumal, Folkes E. Kurniasih, Nuning Iskandar, Akbar Manulangga, Gloria Indra Iswara, Ida Bagus Ary Rahim, Robbi Puzzle Research Data Technology UIN Sultan Syarif Kasim Riau Indonesia Department of Information System UIN Sultan Syarif Kasim Riau Indonesia Informatics Department Universitas Muhammadiyah Semarang Semarang Indonesia Department of Management University of 45 Surabaya Surabaya Indonesia Department of Electrical Engineering Politeknik Negeri Kupang Kupang Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Informatics Department STMIK STIKOM Indonesia Denpasar Indonesia School of Computer and Communication Engineering Universiti Malaysia Perlis Kubang Gajah Malaysia

Berkah Mart is one of the new minimarkets in Pekanbaru city which began to develop as a retail business to meet the needs of the community. In his operation, Berkah Mart still uses the traditional store management perception that the placement of product layout on sale shelves has not been through sales analysis. Existing products have not been reviewed from the consumer's point of view, whereas the marketing economics concept provides a variety of product and consumer management methods for business management in Berkah Mart, including market bucket analysis techniques and various itemset search algorithms. In this research, Market Basket Basket Analysis with FP-Growth algorithm is proposed to determine the layout and planning of goods availability. The application of FP-Growth algorithm proved to be useful in generating many and informative association rules to find out the consumer spending pattern at Berkah Mart in Pekanbaru. Moreover, from the rules of the customer association can be segmented separately to meet the specific needs of customers with cost-effective by using some special promotions for the general group. The experimental results show that FP-Growth algorithm can analyze quickly and efficiently informing consumer shopping pattern at Berkah Mart and can increase Berkah Mart revenue. © Published under licence by IOP Publishing Ltd.

关键词： Sales

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The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)

arXiv

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arXiv 2023年

作者： Kazerooni, Anahita Fathi Khalili, Nastaran Liu, Xinyang Haldar, Debanjan Jiang, Zhifan Anwar, Syed Muhammed Albrecht, Jake Adewole, Maruf Anazodo, Udunna Anderson, Hannah Bagheri, Sina Baid, Ujjwal Bergquist, Timothy Borja, Austin J. Calabrese, Evan Chung, Verena Conte, Gian-Marco Dako, Farouk Eddy, James Ezhov, Ivan Familiar, Ariana Farahani, Keyvan Haldar, Shuvanjan Iglesias, Juan Eugenio Janas, Anastasia Johansen, Elaine Jones, Blaise V. Kofler, Florian LaBella, Dominic Lai, Hollie Anne Van Leemput, Koen Li, Hongwei Bran Maleki, Nazanin McAllister, Aaron S. Meier, Zeke Menze, Bjoern Moawad, Ahmed W. Nandolia, Khanak K. Pavaine, Julija Piraud, Marie Poussaint, Tina Prabhu, Sanjay P. Reitman, Zachary Rodriguez, Andres Rudie, Jeffrey D. Sanchez-Montano, Mariana Shaikh, Ibraheem Salman Shah, Lubdha M. Sheth, Nakul Shinohara, Russel Taki Tu, Wenxin Viswanathan, Karthik Wang, Chunhao Ware, Jeffrey B. Wiestler, Benedikt Wiggins, Walter Zapaishchykova, Anna Aboian, Mariam Bornhorst, Miriam de Blank, Peter Deutsch, Michelle Fouladi, Maryam Hoffman, Lindsey Kann, Benjamin Lazow, Margot Mikael, Leonie Nabavizadeh, Ali Packer, Roger Resnick, Adam Rood, Brian Vossough, Arastoo Bakas, Spyridon Linguraru, Marius George Children’s Hospital of Philadelphia PhiladelphiaPA United States Department of Neurosurgery University of Pennsylvania PhiladelphiaPA United States University of Pennsylvania PhiladelphiaPA United States Sheikh Zayed Institute for Pediatric Surgical Innovation Children’s National Hospital WashingtonDC United States Department of Neurosurgery Thomas Jefferson University Hospital PA United States Sage Bionetworks United States Lab Crestview Radiology Lagos Nigeria McGill University MontrealQC Canada Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Neurosurgery The University of Southern California CA United States Department of Radiology Duke University Medical Center United States Mayo Clinic MN United States Center for Global Health Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Informatics Technical University Munich Germany TranslaTUM - Central Institute for Translational Cancer Research Technical University of Munich Germany Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD United States Biomedical Engineering Rutgers University New BrunswickNJ United States Athinoula A Martinos Center for Biomedical Imaging Massachusetts General Hospital BostonMA United States Yale University New HavenCT United States PrecisionFDA U.S. Food and Drug Administration Silver SpringMD United States Cincinnati Children’s Hospital Medical Center United States Helmholtz AI Helmholtz Munich Germany Department of Radiation Oncology Duke University Medical Center United States Department of Radiology Children’s Health Orange County CA United States Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark Department of Radiol

Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less than 20%. Due to their rarity, the diagnosis of these entities is often delayed, their treatment is mainly based on historic treatment concepts, and clinical trials require multi-institutional collaborations. The MICCAI Brain Tumor Segmentation (BraTS) Challenge is a landmark community benchmark event with a successful history of 12 years of resource creation for the segmentation and analysis of adult glioma. Here we present the CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge, which represents the first BraTS challenge focused on pediatric brain tumors with data acquired across multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. The BraTS-PEDs 2023 challenge focuses on benchmarking the development of volumentric segmentation algorithms for pediatric brain glioma through standardized quantitative performance evaluation metrics utilized across the BraTS 2023 cluster of challenges. Models gaining knowledge from the BraTS-PEDs multi-parametric structural MRI (mpMRI) training data will be evaluated on separate validation and unseen test mpMRI dataof high-grade pediatric glioma. The CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge brings together clinicians and AI/imaging scientists to lead to faster development of automated segmentation techniques that could benefit clinical trials, and ultimately the care of children with brain tumors. © 2023, CC BY.

关键词： Tumors

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Diversity of Artists in Major U.S. Museums

arXiv

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arXiv 2018年

作者： Topaz, Chad M. Klingenberg, Bernhard Turek, Daniel Heggeseth, Brianna Harris, Pamela E. Blackwood, Julie C. Ondine Chavoya, C. Nelson, Steven Murphy, Kevin M. Department of Mathematics and Statistics Williams College WilliamstownMA United States Graduate Program in Data Science New College of Florida SarasotaFL United States Department of Mathematics Statistics and Computer Science Macalester College St. PaulMN United States Department of Art Williams College WilliamstownMA United States Department of Art History University of California Los AngelesCA United States Williams College Museum of Art WilliamstownMA United States

The U.S. art museum sector is grappling with diversity. While previous work has investigated the demographic diversity of museum staffs and visitors, the diversity of artists in their collections has remained unreported. We conduct the first large-scale study of artist diversity in museums. By scraping the public online catalogs of 18 major U.S. museums, deploying a sample of 10,000 artist records comprising over 9,000 unique artists to crowdsourcing, and analyzing 45,000 responses, we infer artist genders, ethnicities, geographic origins, and birth decades. Our results are threefold. First, we provide estimates of gender and ethnic diversity at each museum, and overall, we find that 85% of artists are white and 87% are men. Second, we identify museums that are outliers, having significantly higher or lower representation of certain demographic groups than the rest of the pool. Third, we find that the relationship between museum collection mission and artist diversity is weak, suggesting that a museum wishing to increase diversity might do so without changing its emphases on specific time periods and regions. Our methodology can be used to broadly and efficiently assess diversity in other fields. Copyright © 2018, The Authors. All rights reserved.

关键词： Population statistics

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Network Topology Mapping from Partial Virtual Coordinates and Graph Geodesics

arXiv

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arXiv 2017年

作者： Jayasumana, Anura P. Paffenroth, Randy Ramasamy, Sridhar Department of Electrical & Computer Engineering Colorado State University Fort CollinsCO80525 Department of Mathematical Sciences Department of Computer Science Data Science Program Worcester Polytechnic Institute WorcesterMA01609

For many important network types (e.g., sensor networks in complex harsh environments and social networks) physical coordinate systems (e.g., Cartesian), and physical distances (e.g., Euclidean), are either difficult to discern or inappropriate. Accordingly, Topology Preserving Maps (TPMs) derived from a Virtual-Coordinate (VC) system representing the distance to a small set of anchors is an attractive alternative to physical coordinates for many network algorithms. Herein, we present an approach, based on the theory of low-rank matrix completion, to recover geometric properties of a network with only partial information about the VCs of nodes. In particular, our approach is a combination of geodesic recovery concepts and low-rank matrix completion, generalized to the case of hop-distances in graphs. Distortion evaluated using the change of distance among node pairs shows that even with up to 40% to 60% of random coordinates missing, accurate TPMs can be obtained. TPM generation can now also be based on different context appropriate VC systems or measurements as long as they characterize each node with distances to a small set of random nodes (instead of a global set of anchors). The proposed method is a significant generalization that allows the topology to be extracted from a random set of graph geodesics, making it applicable in contexts such as social networks where VC generation may not be *** Codes 15A83 Copyright © 2017, The Authors. All rights reserved.

关键词： Sensor networks

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Ten simple rules for reproducible research in jupyter notebooks

arXiv

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arXiv 2018年

作者： Rule, Adam Birmingham, Amanda Zuniga, Cristal Altintas, Ilkay Huang, Shih-Cheng Knight, Rob Moshiri, Niema Nguyen, Mai H. Rosenthal, Sara Brin Pérez, Fernando Rose, Peter W. Design Lab UC San Diego San DiegoCA United States Center for Computational Biology and Bioinformatics UC San Diego San DiegoCA United States Department of Pediatrics UC San Diego San DiegoCA United States Data Science Hub San Diego Supercomputer Center UC San Diego San DiegoCA United States Departments of Bioengineering and Computer Science and Engineering Center for Microbiome Innovation UC San Diego San DiegoCA United States Bioinformatics and Systems Biology Graduate Program UC San Diego San DiegoCA United States Department of Statistics Berkeley Institute for Data Science UC Berkeley Lawrence Berkeley National Laboratory BerkeleyCA United States Biomedical Informatics Graduate Program Stanford University StanfordCA United States

Reproducibility of computational studies is a hallmark of scientific methodology. It enables researchers to build with confidence on the methods and findings of others, reuse and extend computational pipelines, and thereby drive scientific progress. Since many experimental studies rely on computational analyses, biologists need guidance on how to set up and document reproducible data analyses or simulations. In this paper, we address several questions about reproducibility. For example, what are the technical and non-technical barriers to reproducible computational studies? What opportunities and challenges do computational notebooks offer to overcome some of these barriers? What tools are available and how can they be used effectively? We have developed a set of rules to serve as a guide to scientists with a specific focus on computational notebook systems, such as Jupyter Notebooks, which have become a tool of choice for many applications. Notebooks combine detailed workflows with narrative text and visualization of results. Combined with software repositories and open source licensing, notebooks are powerful tools for transparent, collaborative, reproducible, and reusable data analyses. Copyright © 2018, The Authors. All rights reserved.

关键词： Digital storage

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Author Correction: The landscape of viral associations in human cancers

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Nature genetics 2023年第6期55卷 1077页

作者： Marc Zapatka Ivan Borozan Daniel S Brewer Murat Iskar Adam Grundhoff Malik Alawi Nikita Desai Holger Sültmann Holger Moch Colin S Cooper Roland Eils Vincent Ferretti Peter Lichter Division of Molecular Genetics German Cancer Research Center (DKFZ) Heidelberg Germany. Informatics and Bio-computing Program Ontario Institute for Cancer Research Toronto Ontario Canada. Norwich Medical School University of East Anglia Norwich UK. Earlham Institute Norwich UK. Heinrich-Pette-Institute Leibniz Institute for Experimental Virology Hamburg Germany. German Center for Infection Research (DZIF) Partner Site Hamburg-Borstel-Lübeck-Riems Hamburg Germany. Bioinformatics Core University Medical Center Hamburg-Eppendorf Hamburg Germany. Bioinformatics Group Department of Computer Science University College London London UK. Biomedical Data Science Laboratory Francis Crick Institute London UK. National Center for Tumor Diseases (NCT) Heidelberg Heidelberg Germany. Division of Cancer Genome Research German Cancer Research Center (DKFZ) Heidelberg Germany. German Cancer Consortium (DKTK) Heidelberg Germany. Department of Pathology and Molecular Pathology University and University Hospital Zürich Zurich Switzerland. Institute of Cancer Research London UK. University of East Anglia Norwich UK. Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany. Department of Bioinformatics and Functional Genomics Institute of Pharmacy and Molecular Biotechnology Heidelberg University and BioQuant Center Heidelberg Germany. Center for Digital Health Berlin Institute of Health and Charité Universitätsmedizin Berlin Berlin Germany. Ontario Institute for Cancer Research MaRS Centre Toronto Ontario Canada. Department of Biochemistry and Molecular Medicine University of Montreal Montreal Québec Canada. Division of Molecular Genetics German Cancer Research Center (DKFZ) Heidelberg Germany. peter.lichter@dkfz-heidelberg.de. German Cancer Consortium (DKTK) Heidelberg Germany. peter.lichter@dkfz-heidelberg.de.

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Author Correction: Genomic footprints of activated telomere maintenance mechanisms in cancer (Dec, 10.1038/s41467-019-13824-9, 2022)

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NATURE COMMUNICATIONS 2022年第1期13卷 1-1页

作者： Sieverling, Lina Hong, Chen Koser, Sandra D. Ginsbach, Philip Kleinheinz, Kortine Hutter, Barbara Braun, Delia M. Cortes-Ciriano, Isidro Xi, Ruibin Kabbe, Rolf Park, Peter J. Eils, Roland Schlesner, Matthias Brors, Benedikt Rippe, Karsten Jones, David T. W. Feuerbach, Lars Division of Applied Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Faculty of Biosciences Heidelberg University 69120 Heidelberg Germany Division of Applied Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Biosciences Heidelberg University Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Department for Bioinformatics and Functional Genomics Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant 69120 Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Institute of Pharmacy and Molecular Biotechnology and BioQuant Heidelberg University Heidelberg Germany German Cancer Consortium (DKTK) Heidelberg Germany National Center for Tumor Diseases (NCT) Heidelberg Heidelberg Germany Heidelberg Center for Personalized Oncology (DKFZ-HIPO) German Cancer Research Center (DKFZ) Heidelberg Germany German Cancer Consortium (DKTK) German Cancer Research Center (DKFZ) Heidelberg Germany Division of Chromatin Networks German Cancer Research Center (DKFZ) and BioQuant 69120 Heidelberg Germany Department of Biomedical Informatics Harvard Medical School Boston Massachusetts 02115 USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge CB2 1EW UK Ludwig Center at Harvard Medical School Boston Massachusetts 02115 USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge UK Ludwig Center at Harvard Medical School Boston MA USA School of Mathematical Sciences and Center for Statistical Science Peking University Beijing 100871 China Heidelberg University Heidelberg Germany New BIH Digital Health Center Berlin Institute of Health (BIH) and Charité - Universitätsmedizin Berlin Berlin Germany Bioi

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Erratum for Wang et al., "Clinically Applicable System for Rapidly Predicting Enterococcus faecium Susceptibility to Vancomycin"

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Microbiology spectrum 2022年第1期10卷 e0261021页

作者： Hsin-Yao Wang Chia-Ru Chung Chao-Jung Chen Ko-Pei Lu Yi-Ju Tseng Tzu-Hao Chang Min-Hsien Wu Wan-Ting Huang Ting-Wei Lin Tsui-Ping Liu Tzong-Yi Lee Jorng-Tzong Horng Jang-Jih Lu Department of Laboratory Medicine Chang Gung Memorial Hospitalgrid.413801.f at Linkou Taoyuan City Taiwan. Ph.D. Program in Biomedical Engineering Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Department of Computer Science and Information Engineering National Central Universitygrid.37589.30 Taoyuan City Taiwan. Graduate Institute of Integrated Medicine China Medical Universitygrid.254145.3 Taichung Taiwan. Proteomics Core Laboratory China Medical Universitygrid.254145.3 Hospital Taichung Taiwan. Graduate Program in Biomedical Information Yuan-Ze University Taoyuan City Taiwan. Department of Information Management Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Graduate Institute of Biomedical Informatics Taipei Medical University Taipei City Taiwan. Clinical Big Data Research Center Taipei Medical University Hospital Taipei City Taiwan. Graduate Institute of Biomedical Engineering Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Division of Haematology/Oncology Department of Internal Medicine Chang Gung Memorial Hospitalgrid.413801.f at Linkou Taoyuan City Taiwan. Biosensor Group Biomedical Engineering Research Center Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Department of Pathology Kaohsiung Chang Gung Memorial Hospitalgrid.413801.f and Chang Gung University College of Medicine Kaohsiung Taiwan. School of Life and Health Sciences The Chinese University of Hong Kong Shenzhen China. Warshel Institute for Computational Biology The Chinese University of Hong Kong Shenzhen China. Department of Bioinformatics and Medical Engineering Asia University Taichung City Taiwan. School of Medicine Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Department of Medical Biotechnology and Laboratory Science Chang Gung Universitygrid.145695.a Taoyuan City Taiwan.

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