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Treatment Algorithm for the Resorption of Calcific Tendinitis Using Extracorporeal Shockwave Therapy: A Data Mining Study

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Orthopaedic Journal of Sports Medicine 2024年第3期12卷 23259671241231609页

作者： Chou, Wen-Yi Cheng, Jai-Hong Lien, Yu-Jui Huang, Tian-Hsiang Ho, Wen-Hsien Chou, Paul Pei-Hsi Doctoral Degree Program in Biomedical Engineering College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Department of Orthopedic Surgery Kaohsiung Chang Gung Memorial Hospital Chang Gung University College of Medicine Kaohsiung Taiwan Department of Leisure and Sport Management Cheng Shiu University Kaohsiung Taiwan Center for Shockwave Medicine and Tissue Engineering Department of Medical Research Kaohsiung Chang Gung Memorial Hospital Chang Gung University College of Medicine Kaohsiung Taiwan Department of Healthcare Administration and Medical Informatics Kaohsiung Medical University Kaohsiung Taiwan Department of Computer Science and Information Engineering National Penghu University of Science and Technology Penghu Taiwan College of Professional Studies National Pingtung University of Science and Technology Pingtung Taiwan Department of Sports Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Division of Sports Medicine Department of Orthopaedic Surgery Kaohsiung Medical University Hospital Kaohsiung Taiwan Department of Orthopaedics School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Department of Orthopaedic Surgery Kaohsiung Municipal Hsiao-Kang Hospital Kaohsiung Taiwan

Background: Although evidence indicates that extracorporeal shockwave therapy (ESWT) is effective in treating calcifying shoulder tendinitis, incomplete resorption and dissatisfactory results are still reported in many cases. Data mining techniques have been applied in health care in the past decade to predict outcomes of disease and treatment. Purpose: To identify the ideal data mining technique for the prediction of ESWT-induced shoulder calcification resorption and the most accurate algorithm for use in the clinical setting. Study Design: Case-control study. Methods: Patients with painful calcified shoulder tendinitis treated by ESWT were enrolled. Seven clinical factors related to shoulder calcification were adopted as the input attributes: sex, age, side affected, symptom duration, pretreatment Constant-Murley score, and calcification size and type. The 5 data mining techniques assessed were multilayer perceptron (neural network), naïve Bayes, sequential minimal optimization, logistic regression, and the J48 decision tree classifier. Results: A total of 248 patients with calcified shoulder tendinitis were enrolled in this study. Shorter symptom duration yielded the highest gain ratio (0.374), followed by smaller calcification size (0.336) and calcification type (0.253). With the J48 decision tree method, the accuracy of 3 input attributes was 89.5% by 10-fold cross-validation, indicating satisfactory accuracy. A treatment algorithm using the J48 decision tree indicated that a symptom duration of ≤10 months was the most positive indicator of calcification resorption, followed by a calcification size of ≤10.82 mm. Conclusion: The J48 decision tree method demonstrated the highest precision and accuracy in the prediction of shoulder calcification resorption by ESWT. A symptom duration of ≤10 months or calcification size of ≤10.82 mm represented the clinical scenarios most likely to show resorption after ESWT. © The Author(s) 2024.

关键词： calcific tendinitis data mining extracorporeal shockwave therapy J48 decision tree shoulder

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Negative prognostic factors and clinical improvement prediction modeling for extracorporeal shockwave therapy in calcific shoulder tendinitis using artificial intelligence techniques

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Journal of Shoulder and Elbow Surgery 2025年

作者： Chou, Wen-Yi Huang, Tian-Hsiang Cheng, Jai-Hong Lien, Yu-Jui Ho, Wen-Hsien Chou, Paul Pei-Hsi Ph.D. Program in Biomedical Engineering College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Department of Orthopedic Surgery Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine Kaohsiung Taiwan Department of Leisure and Sport Management Cheng Shiu University Kaohsiung Taiwan Department of Computer Science and Information Engineering National Penghu University of Science and Technology Penghu Taiwan Department of Medical Research Center for Shockwave Medicine and Tissue Engineering Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine Kaohsiung Taiwan Department of Healthcare Administration and Medical Informatics Kaohsiung Medical University Kaohsiung Taiwan Department of Medical Research Kaohsiung Medical University Hospital Kaohsiung Taiwan College of Professional Studies National Pingtung University of Science and Technology Pingtung Taiwan Precision Sports Medicine and Health Promotion Center Kaohsiung Medical University Kaohsiung Taiwan Department of Sports Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Division of Sports Medicine Department of Orthopaedic Surgery Kaohsiung Medical University Hospital Kaohsiung Taiwan Department of Orthopaedics School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan

Background: The efficacy of extracorporeal shockwave therapy (ESWT) for treating shoulder calcific tendinitis can be influenced by various prognostic factors. This study aimed to identify prognostic factors associated with the failure of ESWT for symptom relief and to evaluate the predictive capability of the eXtreme Gradient Boosting (XGBoost) algorithm of artificial intelligence techniques in this context. Methods: This retrospective study enrolled patients with persistent shoulder pain attributed to calcific tendinitis who underwent ESWT after failed conservative treatment between January 1998 and December 2022. Age, sex, duration of symptoms, calcification classification and size, pre-ESWT visual analog scale (VAS), and pre-ESWT Constant-Murley score (CMS) served as potential input attributes. The difference in VAS and CMS were defined as the output attributes. The XGBoost model was used to predict treatment outcomes based on these factors. The dataset was balanced using the synthetic minority oversampling technique, and the model's performance was assessed using 10-fold cross-validation. Spearman's rank correlation coefficient analysis was adopted to explore the relationships between significant continuous input attributes and post-ESWT VAS and CMS scores. Results: A total of 296 patients with calcific tendinitis were enrolled and completed the 1-year follow-up. The findings revealed that a prolonged symptom duration (>10 months), severe pain (pre-ESWT VAS >5), and higher pre-ESWT CMS (>55) were significant prognostic factors for the failure of ESWT for symptom relief. Using these factors as inputs, the XGBoost model demonstrated high accuracy, precision, recall, and F1 score. By reducing the input attributes to age, calcification size, pre-ESWT CMS, and symptom duration, the model maintained a high prediction rate, suggesting that these factors are sufficient for effective prediction. Discussion: The present study identified significant prognostic factors asso

关键词： Artificial intelligence Basic science Study calcific tendinitis CMS Development of Predictive Computer Modeling Using AI/Machine Learning ESWT shoulder VAS XGBoost

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Collaborative networks in gene editing (vol 37, pg 1107, 2019)

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NATURE BIOtechnology 2019年第12期37卷 1522-1522页

作者： Huang, Ying Porter, Alan Zhang, Yi Barrangou, Rodolphe School of Information Management Wuhan University Wuhan China Centre for R&D Monitoring (ECOOM) and Department of MSI KU Leuven Leuven Belgium Search Technology Inc. Norcross GA USA Program in Science Technology & Innovation Policy (STIP) Georgia Institute of Technology Atlanta GA USA Centre for Artificial Intelligence Faculty of Engineering and Information Technology University of Technology Sydney Sydney New South Wales Australia Department of Food Bioprocessing and Nutrition Sciences North Carolina State University Raleigh NC USA

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Association of alcohol consumption, betel nut chewing, and cigarette smoking with mortality in patients with head and neck cancer among the Taiwanese population: A nationwide population-based cohort study

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Cancer Epidemiology 2024年 89卷 102526-102526页

作者： Su, Ming-Jang Ho, Chung-Han Yeh, Chih-Ching School of Public Health College of Public Health Taipei Medical University New Taipei City Taiwan Department of Family Medicine School of Medicine College of Medicine Taipei Medical University Taipei City Taiwan Department of Clinical Pathology Shuang Ho Hospital Taipei Medical University New Taipei City Taiwan Department of Medical Research Chi Mei Medical Center Tainan City Taiwan Department of Information Management Southern Taiwan University of Science and Technology Tainan City Taiwan Cancer Center Wan Fang Hospital Taipei Medical University Taipei City Taiwan Department of Public Health College of Public Health China Medical University Taichung City Taiwan Master Program in Applied Epidemiology College of Public Health Taipei Medical University New Taipei City Taiwan

Objectives: This study investigated the association of alcohol consumption, betel nut chewing, and cigarette smoking (ABC) with mortality in patients with head and neck cancer (HNC). This nationwide population-based cohort study determined whether ABC habits were associated with overall or cancer-specific mortality in patients with HNC in Taiwan. Methods: Data from the Taiwan Cancer Registry and Taiwan's National Health Insurance Research Database were used to identify patients with HNC from 2011 to 2017. All the identified patients were monitored until the date of death or the end of 2017. Poisson regression models were employed to estimate the incidence rate ratios (IRRs) and 95% confidence intervals (CIs) associated with the effect of ABC habits on mortality. Results: A total of 31,246 patients with HNC were analyzed in this study. The results revealed that betel nut chewing alone exhibited the strongest effect, significantly increasing the risk of overall mortality (adjusted IRR = 1.44, 95% CI = 1.27–1.63). Additionally, betel nut chewing alone was significantly associated with cancer-specific mortality (adjusted IRR = 1.51, 95% CI = 1.30–1.44). Stratified analyses by sex and tumor location indicated that the effect of betel nut chewing alone on overall or cancer-specific mortality remained significant across both sexes, and among patients with oral cancer and patients with oropharyngeal cancer. Conclusions: ABC habits, particularly betel nut chewing, are significantly associated with diminished survival rates in patients with HNC. Accordingly, the implementation of an integrated campaign targeting the prevention of betel nut chewing would be one of the effective public health strategies for improving outcomes for HNC patients. © 2024 Elsevier Ltd

关键词： Alcohol consumption Betel nut chewing Cigarette smoking Head and neck cancer Mortality

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ANTARCTICA AND THE SOUTHERN OCEAN

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BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY 2023年第9期104卷 S322-S365页

作者： Clem, Kyle R. Raphael, Marilyn N. School of Geography Environment and Earth Sciences Victoria University of Wellington Wellington New Zealand Scripps Institution of Oceanography University of California San Diego La Jolla California Department of Atmospheric and Oceanic Sciences University of Colorado Boulder Boulder Colorado Earth Science Observation Center Cooperative Institute for Research in Environmental Sciences (ESOC/CIRES) University of Colorado Boulder Boulder Colorado Argentine Naval Hydrographic Service Buenos Aires Argentina Department of Earth and Environmental Science Temple University Philadelphia Pennsylvania Department of Meteorology University of Valparaíso Valparaíso Chile Center for Climate and Resilience Research (CR)2 Santiago Chile British Antarctic Survey Cambridge United Kingdom Science Systems and Applications Inc. Lanham Maryland NASA Goddard Space Flight Center Greenbelt Maryland Royal Netherlands Meteorological Institute (KNMI) DeBilt The Netherlands Department of Marine Sciences University of Gothenburg Gothenburg Sweden Department of Geography Ohio University Athens Ohio NASA Jet Propulsion Laboratory Pasadena California NOAA/OAR Earth System Research Laboratory Global Monitoring Division Boulder Colorado University of Colorado Boulder Boulder Colorado National Oceanography Centre Southampton United Kingdom. Antarctic Meteorological Research and Data Center Space Science and Engineering Center University of Wisconsin-Madison Madison Wisconsin Department of Physical Sciences School of Arts and Sciences Madison Area Technical College Madison Wisconsin Australian Bureau of Meteorology and Institute for Marine and Antarctic Studies (IMAS) University of Tasmania Hobart Australia Earth Science and Observation Center CIRES University of Colorado Boulder Colorado University of St. Andrews St Andrews United Kingdom Princeton University Princeton New Jersey Australian Antarctic Division Australian Antarctic Program Partnership (AAPP) and Australian Centre fo

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Comparing the effects of robots and IoT objects on STEM learning outcomes and computational thinking skills between programming-experienced learners and programming-novice learners

Comparing the effects of robots and IoT objects on STEM lear...

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International Conference on Advanced Learning Technologies (ICALT)

作者： Chih-Chien Hu Hsiao-Ting Tseng Ming-Hsien Chen Alexis Goh Phaik Imm Nian-Shing Chen Bachelor Program in Interdisciplinary Studies College of Future National Yunlin University of Science and Technology Yunlin Taiwan R.O.C Department of Information Management National United University Miaoli Taiwan R.O.C Tatung University Taipei Taiwan R.O.C National Yunlin University of Science and Technology Yunlin Taiwan National Yunlin University of Science and Technology Yunlin Taiwan R.O.C

ISBN: (数字)9781728160900

ISBN: (纸本)9781728160917

Recent college students have been observed to be motivated and engaged in acquiring science, technology, engineering, and mathematics (STEM) knowledge and skills with robots and IoT objects. A sample of 13 master's students participated in the program. Data collected include the pre-and post- STEM and computational thinking (CT) written tests, and the pre- and post- surveys of learning perceptions toward the robots and IoT objects learning activities. The results show that the learning activities were an effective approach for the master's students' STEM learning outcome and CT as shown in the post-test. The differences between the master's students' STEM learning outcome, CT, and perceptions were also confirmed, particularly between the groups of computer programming-experienced learners and computer programming-novice learners. The results revealed that the learning activities with robots and IoT objects could improve the overall master's students' CT, STEM knowledge, and learning perceptions. Both programming-experienced and programming-novice learners' STEM learning outcome were improved.

关键词： programming profession Educational robots STEM

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Assessing Water Quality Characteristics of pH and Biochemical Oxygen Demand (CBOD) of Public Utility using Statistical Quality Control (SQC) 23

Assessing Water Quality Characteristics of pH and Biochemica...

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23rd World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2019

作者： Blevins, Nathaniel Bryce Segall, Richard S. Choppari, Sharanya Engineering Program College of Engineering and Computer Science Arkansas State University State University AR7247 United States Department of Computer and Information Technology Neil Griffin College of Business Arkansas State University State University AR72467 United States Engineering Management Program College of Engineering and Computer Science Arkansas State University State University AR72467 United States

ISBN: (纸本)9781950492091

This paper is a continuation of previous research supervised by co-author Segall that appeared in Akarapu et al. (2016a, 2016b) at WMSCI 2016. This research studies in depth only two of the characteristics of water quality for actual 2016 data collected for a water treatment plant located in United States where the previous studies Akarapu et al. (2016a, 2016) studied five characteristics of water quality for 2014 data for the same water treatment plant. The two water quality characteristics studied in-depth with this paper with a more recent data set for the same water treatment plant are pH and Carbonaceous Biochemical Oxygen Demand (CBOD). Discussions of the analyses are presented as obtained using Minitab 17 and Minitab 18. © WMSCI 2019 - 23rd World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings. All rights reserved.

关键词： Water treatment plants

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The design of an online information system of the check stage in plan-do-check-act cycle for evaluation of student learning in Taiwan Preschools 19

The design of an online information system of the check stag...

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3rd International Conference on E-Education, E-Business and E-technology, ICEBT 2019

作者： Huang, Huei-Ting Wongthai, Winai Doctoral Program of Educational Leadership and Technology Management Tamkang University No.151 Yingzhuan Rd. Tamsui Dist. New Taipei City25137 Taiwan Department of Computer Science and Information Technology Naresuan University 99 Moo 9 Phitsanulok-Nakhonsawan Road Tambon Tapho Muang Phitsanulok65000 Thailand

ISBN: (纸本)9781450372565

It is a hard job for two teachers to deal with 30 students in a preschool classroom in Taiwan. Teachers need to take photos and manage paper documents related to each student's activities and assessments, then print all of them to show to their parents. This is not an efficient and effective working style. In order to support e-education and mitigate these issues in the education domain via application of the Plan-Do-Check-Act (PDCA) cycle, this paper thoroughly investigates appropriate features of previous studies related to e-education and the PDCA computing system. It then proposes the design of an online information system for the "check" stage in the Plan-Do-Check-Act cycle or OISC for evaluating Taiwanese preschool students' learning. The design is simple and equipped with current technologies such as mobile applications. We provided the details of all components and technologies in this design and how the design works, which is arranged for participants to use as a blueprint of an e-education system such as OISC that can be built upon the participants' requirements. We believe that a system based on our design can help teachers to work effectively and efficiently. Thus, this paper can be regarded as an example of adopting an e-education approach to evaluating and enhancing students' learning performance. © 2019 ACM.

关键词： HTTP

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INTRODUCTION

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Bulletin of the American Meteorological Society 2024年第8期105卷 S1-S11页

作者： Boyer, T. Blunden, J. Dunn, R.J.H. NOAA/NESDIS National Centers for Environmental Information Silver Spring Maryland NOAA/NESDIS National Centers for Environmental Information Asheville North Carolina Met Office Hadley Centre Exeter United Kingdom European Centre for Medium-Range Weather Forecasts Reading United Kingdom University of Maryland College Park Maryland Scripps Institution of Oceanography University of California San Diego La Jolla California NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center College Park Maryland Brandenburg University of Technology (BTU) Cottbus-Senftenberg Germany Servicio Meteorológico Nacional Buenos Aires Argentina NOAA/OAR Physical Sciences Laboratory Boulder Colorado European Centre for Medium-Range Weather Forecasts Bonn Germany Center for Geophysical Research and School of Physics University of Costa Rica San José Costa Rica Department of Meteorology and National Centre for Earth Observation University of Reading Reading United Kingdom Centro Nacional de Monitoramento e Alertas de Desastres Naturais CEMADEN São Paulo Brazil Université Grenoble Alpes Institut des Géosciences de l’Environnement IRD CNRS Grenoble INP Grenoble France Hampton University Hampton Virginia Seychelles Meteorological Authority Mahe Seychelles Section for Glaciers Ice and Snow Norwegian Water Resources and Energy Directorate Oslo Norway National Research Institute for Agriculture Food and Environment (INRAE) CARRTEL Université Savoie Mont Blanc Thonon les Bains France Graduate School of Agriculture Osaka Metropolitan University Sakai Japan Science Faculty Universidad Nacional de Colombia Bogotá Colombia University of Bremen Bremen Germany NOAA Global Monitoring Laboratory Boulder Colorado Servicio Nacional de Meteorología e Hidrología del Perú Lima Perú Centro de Investigaciones sobre Desertificación – Spanish National Research Council (CSIC-UV-GVA) Valencia Spain Hydro-Climate Extremes Lab (H-CEL) Ghent University Ghent Belgium Department o

In 2023, La Niña conditions that generally prevailed in the eastern Pacific Ocean from mid-2020 into early 2023 gave way to a strong El Niño by October. Atmospheric concentrations of Earth’s major greenhouse gases—carbon dioxide, methane, and nitrous oxide—all increased to record-high levels. The annual global average carbon dioxide concentration in the atmosphere rose to 419.3±0.1 ppm, which is 50% greater than the pre-industrial level. The growth from 2022 to 2023 was 2.8 ppm, the fourth highest in the record since the 1960s. The combined short-term effects of El Niño and the long-term effects of increasing levels of heat-trapping gases in the atmosphere contributed to new records for many essential climate variables reported here. The annual global temperature across land and oceans was the highest in records dating as far back as 1850, with the last seven months (June–December) having each been record warm. Over land, the globally averaged temperature was also record high. Dozens of countries reported record or near-record warmth for the year, including China and continental Europe as a whole (warmest on record), India and Russia (second warmest), and Canada (third warmest). Intense and widespread heatwaves were reported around the world. In Vietnam, an all-time national maximum temperature record of 44.2°C was observed at Tuong Duong on 7 May, surpassing the previous record of 43.4°C at Huong Khe on 20 April 2019. In Brazil, the air temperature reached 44.8°C in Araçuaí in Minas Gerais on 20 November, potentially a new national record and 12.8°C above normal. The effect of rising temperatures was apparent in the cryosphere, where snow cover extent by June 2023 was the smallest in the 56-year record for North America and seventh smallest for the Northern Hemisphere overall. Heatwaves contributed to the greatest average mass balance loss for Alpine glaciers around the world since the start of the record in 1970. Due to rapid volume loss beginning in 2021, St. A

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Leading sector analysis in West Kotawaringin Regency, Central Kalimantan Province, Indonesia 1

Leading sector analysis in West Kotawaringin Regency, Centra...

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1st International Seminar on Natural Resources and Environmental management 2019, ISeNREM 2019

作者： Sutrisna, M.G. Sitorus, S.R.P. Widiatmaka Marimin Nurwajedi Natural Resources and Environmental Management Program Study Postgraduate School IPB University Bogor Indonesia Dept. of Soil Science and Land Resources IPB University Bogor Indonesia Dept. of Agricultural Industral Technology IPB University Bogor Indonesia Geospatial Information Agency Cibinong Indonesia

The balance between economic, social, and environmental aspects should be fulfilled in the planning of sustainable regional development. The main engine of regional economic development is the leading sector, which is characterized by strong linkage between forward and backward sectors. This research is intended to analyze leading sectors in West Kotawaringin Regency, Central Kalimantan Province. The data used is the 2012 IO (Input-output) table, analysed using the Input-Output analysis method. Result of the research indicates that the leading sectors of West Kotawaringin Regency are agriculture;transportation and communication;trade, hotel and restaurant;and processing industry. As for the 48 sector groups, for the agricultural sector are rubber, wood, and oil palm;transportation and communication sector are river, lake and harbor transportation, sea transportation, and air transportation;trade, hotel, and restaurant sector is hotels and restaurants followed by trade. The manufacturing sector is the processing and preservation, the building wood and the sawmill industry. © Published under licence by IOP Publishing Ltd.

关键词： Commerce

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