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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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5S towards sustainable competitive advantage in franchise retail business

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IOP Conference Series: Earth and Environmental science 2021年第1期729卷

作者： E Astuty A Sinaga Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Bandung Indonesia Informatics Department School of Computer Science Bina Nusantara University Bandung Indonesia

This study aims to find empirical evidence in filling the 'how-to' gap of a service company in order to have a sustainable competitive advantage by adopting lean system or known as a workplace organization. This study surveyed 150 customers from three largest franchise minimarts in Bandung City in order to determine the characteristics and interrelations that occur in the three research objects observed, namely 5S or workplace organization, service's waste, and service quality. The method used is descriptive method and structural equation modeling based on the least squares method or PLS-SEM. The statistical tools used are SPSS20 and SmartPLS3. The results reveals that the three largest franchise minimarts in Bandung City, had a high level of service quality, low service's waste, and well-managed workplace organization. The relationship between them shows that the three franchise minimarts continue to survive and continue to grow after operating for more than 3 decades, because they implemented a workplace organization (5S, seiri-seiton-seiso-seiketsu-shitsuke), so that this can reduce the occurrence of service's waste by 82.4 %, where even this has an impact on increasing service quality by 27.9% with a very high model strength of 73.5%.

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Analysis of denial of service attack on web security systems

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Journal of Physics: Conference Series 2021年第1期1811卷

作者： S. Iswandi Walad Muhammad Zarlis M.IT Syahril Efendi Department of Information and Technology Faculty of Computer Science and Information Technology University of Sumatera Utara Medan Indonesia. Master Program (S2) of Informatics Engineering Faculty of Computer Science and Information Technology University of Sumatera Utara Medan Indonesia.

In this study, an analysis of the Web security system from a Denial-of-Service Attack (DoS) with SYN Attack, Ping of Death, Land Attack, Smurf Attack and UDP Flood types. The server computer that will be tested for DoS attacks is a local web server including *** IP: 54.169.71.56, *** IP: 104.152.168.14, *** IP: 156.67.210.132, *** IP: 202.162. 207,101 and *** with IP Address 213.136.83.52 port 80. The attack on the local web server computer was carried out through attacking cloned computers as many as 5 zombie computers and then observing data traffic on each Web server computer. The test results use ping to the local web server computer, where the target web server sends a replay request time out and the check results in the Google Chrome browser are slow to inaccessible conditions. Ping access time the greater the packet, the greater the average time when accessing a local web server with 5,000 packets is 242.68 seconds, 10,000 packets is 310.28 seconds, 20,000 packets are 337.4 seconds, 30,000 packets are 377.2 seconds, 40,000 packets are 398.4 seconds, 50,000 packets are 545.4 seconds and 100,000 packets are above 600 seconds with the condition that the web server will recover after 600 seconds where the system recovery process depends on each local web server.

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Implementation of Augmented Reality in Pretend Play Therapy for Children with Autism Spectrum Disorder 3

Implementation of Augmented Reality in Pretend Play Therapy ...

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3rd International Conference on Computing and Applied informatics 2018, ICCAI 2018

作者： Syahputra, M.F. Angkasih, A.P. Purnamawati, S. Andayani, U. Abdullah, D. Sriadhi, S. Iskandar, A. Rosida, T.M. Fitriany, J. Sari, I.N. Utama, M.D. Nanuru, R.F. Department of Information Technology Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Utara Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Pediatric Universitas Malikussaleh Aceh Utara Indonesia Departement of Social Science Education Program Post Graduate Program Universitas Kanjuruhan Malang Malang Indonesia Faculty of Social and Political Science Universitas Kristen Indonesia Maluku Indonesia Universitas Kristen Indonesia Maluku Ambon Indonesia

Autism Spectrum Disorder is a pervasive developmental disorder that will affect children in terms of interpersonal communication, social interaction, and imaginative levels in play. Many therapies to help the motor neuron performance is one of them Pretend Play. Pretend Play is a therapy that invites children in playing to demonstrate something else and tell how to use objects that are considered in the child's imagination. However, in the era of highly developed technology, many fields have used the Augmented Reality method as a visualization of various aspects. With this method researchers will present the therapeutic visualization of the block to 3D transportation tool that is useful for strengthening motor nerves and visual strength of the child. The system can run well during marker detection, marker movement, and 3D object display with the accuracy of precision angle and distance between virtual world with real world reach 100% with angle 0 at distance 31 cm and the maximum distance from the marker is 46 cm and the maximum angle is 30. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Augmented reality

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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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A Step Towards a Reinforcement Learning De Novo Genome Assembler

Research Square

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Research Square 2021年

作者： Padovani, Kleber Xavier, Roberto Carvalho, André Reali, Anna Chateau, Annie Alves, Ronnie Federal University of Pará Computer Science Graduate Program Belém66.075-110 Brazil University of the State of Amazonas Itacoatiara-AM 69.101-416 Brazil Vale Technology Institute Sustainable Development Belém66.055-090 Brazil Institute of Mathematics and Computer Sciences University of São Paulo São Carlos-SP 13566-590 Brazil Polytechnic School University of São Paulo São Paulo-SP 05508-010 Brazil LIRMM-Montpellier Laboratory of Informatics Robotics and Microelectronics Univ Montpellier CNRS Montpellier France

Genome assembly is one of the most relevant and computationally complex tasks in genomics projects. It aims to reconstruct a genome through the analysis of several small textual fragments of such genome — named reads. Ideally, besides ignoring any errors contained in reads, the reconstructed genome should also optimally combine these reads, thus reaching the original genome. The quality of the genome assembly is relevant because the more reliable the genomes, the more accurate the understanding of the characteristics and functions of living beings, and it allows generating many positive impacts on society, including the prevention and treatment of diseases. The assembly becomes even more complex (and it is termed de novo in this case) when the assembler software is not supplied with a similar genome to be used as a reference. Current assemblers have predominantly used heuristic strategies on computational graphs. Despite being widely used in genomics projects, there is still no irrefutably best assembler for any genome, and the proper choice of these assemblers and their configurations depends on Bioinformatics experts. The use of reinforcement learning has proven to be very promising for solving complex activities without human supervision during their learning process. However, their successful applications are predominantly focused on fictional and entertainment problems - such as games. Based on the above, this work aims to shed light on the application of reinforcement learning to solve this relevant real-world problem, the genome assembly. By expanding the only approach found in the literature that addresses this problem, we carefully explored the aspects of intelligent agent learning, performed by the Q-learning algorithm, to understand its suitability to be applied in scenarios whose characteristics are more similar to those faced by real genome projects. The improvements proposed here include changing the previously proposed reward system and including stat

关键词： Reinforcement learning

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Feasibility study of Information Technology Investment (a case study of ODOO ERP: Project Management Module Implementation in Indonesia Based Company)

Feasibility study of Information Technology Investment (a ca...

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International Conference on ICT For Smart Society (ICISS)

作者： Fredy Jingga Raymond Kosala Suhono Harso Supangkat Benny Ranti Computer Science Department BINUS Graduate Program - Doctor of Computer Science Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

IT Governance are one of the needs in managing Enterprise Level IT. This study shows part of the decision domain of IT Governance Help, which are IT Investment and Prioritization. The purpose of this study is to determine feasibility of implementation open source ERP system Odoo project management module that replaces current system based on operational, economic, and technical aspects. The method used are Fit / Gap Analysis and Cost Benefit model using economic impact worksheet. The analysis is done by comparing the requirement with features owned by current system and Odoo ERP system. This research resulted that Odoo ERP System is feasible in the 3 aspects, the operational feasibility Odoo reaching 72% Fit, the economic feasibility with ROI of 84%, and technical feasibility indicating the technical requirement can be fulfilled by leasing AWS server. The conclusion is the open source ERP system Odoo project management module is feasible to be applied in terms of 3 aspects that have been studied, those are operational, economic, and technical.

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Load balancing factor using greedy algorithm in the routing protocol for improving internet access 2

Load balancing factor using greedy algorithm in the routing ...

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2nd Nommensen International Conference on Technology and Engineering, NICTE 2018

作者： Satria, Ady Sihombing, Poltak Sawaluddin Informatics Engineering Study Program Magister Faculty of Computer Science and Information Technology University of Sumatera Utara Indonesia

Load Balancing is very well applied to the distribution of internet access at any point of the Wi-Fi area so that the use of limited devices can be optimal and on target. The proper use of the Greedy Algorithms when applied to an access point device is very capable in resolving excessive loading in a single resource to take the best choice at every stage in an optimum process. Access point device is also a success factor in running the optimization of the distribution of Wi-Fi access on the Access Point is strongly influenced by the parameters set. In this research, user access factor in one very high Wi-Fi area also influences the possibility of incoming access failure. For the application of the results of this study can be utilized on all access point devices that have limits, but for speed internet access remains at the capacity provided bandwidth. © Published under licence by IOP Publishing Ltd.

关键词： Wireless local area networks (WLAN)

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Influence of blended learning on learning result of algorithm and programming 3

Influence of blended learning on learning result of algorith...

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3rd International Conference on informatics and Computing, ICIC 2018

作者： Anggrawan, Anthony Ibrahim, Nurdin Suyitno, M. Satria, Christofer Informatics Engineering Study Program of College of Informatics Management and Computer Science Bumigora West Nusa Tenggara Indonesia Education Technology Study Program of Jakarta State University Jakarta Indonesia Education Technology Study Program of Jakarta State University Jakarta Indonesia Visual Communication Design Study Program of College of Informatics Management and Computer Science Bumigora West Nusa Tenggara Indonesia

ISBN: (纸本)9781538669204

The advancement of today's learning technology makes the learning process no longer fully bases on face to face learning, but can achieve by online learning. Online learning is not only useful in overcoming deficiencies in conventional classroom learning, but also a means to meet the learning styles of students who are less fond of and/or dislike face-to-face learning. On the other hand, the main disadvantage of online learning is the lack of face-to-face interaction, while the strength of face-to-face learning is the intensity of student interaction with teachers, the ease of cooperative learning and the clarity of learning materials. In turn, the superiorities on face-to-face learning and online self-learning can be acquired by blended learning. However, blended learning is a learning solution by taking the best advantage of face-to-face classroom learning and online learning. Blended learning has been a learning solution of today's learning. In this study, two blended learning that has different learning content portions between the portion of face-to-face learning materials and online self-learning was conducted to find out which blended learning results produce better pedagogy between two blended learning, and how well the learning outcomes of blended learning are, especially for Algorithm and programming subject. The research results showed the blended learning with 60% face-to-face learning content and 40% online self-learning content delivers learning cognitive competency outcomes worse than 40% face-to-face learning content and 60% online self-learning content. The learning outcome of both blended learning is good, that is greater than 60% from the ideal number. © 2018 IEEE.

关键词： Students

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Assessing the Potential of GPT-4 to Annotate Medical Notes Across Different Languages and Countries: A Model Evaluation Study

SSRN

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SSRN 2024年

作者： Saad Menezes, Maria Clara Hoffman, Alexander F. Tan, Amelia L.M. Nalbandyan, Mariné Omenn, Gilbert S. Mazzotti, Diego R. Hernández-Arango, Alejandro Visweswaran, Shyam Venkatesh, Shruthi Mandl, Kenneth D. Bourgeois, Florence T. Lee, James W.K. Makmur, Andrew Hanauer, David A. Semanik, Michael G. Kerivan, Lauren T. Hill, Terra Forero, Julian Restrepo Castro, Carlos Andrés C.R. Vigna, Matteo Ceriana, Piero Abu-El-rub, Noor Avillach, Paul Bellazzi, Riccardo Callaci, Thomas Gutiérrez-Sacristán, Alba Malovini, Alberto Mathew, Jomol P. Morris, Michele Murthy, Venkatesh Parimbelli, Enea Patel, Lav P. Sáez, Carlos Samayamuthu, Malarkodi Jebathilagam Thompson, Jeffrey A. Tibollo, Valentina Xia, Zongqi Kohane, Isaac S. Harvard Medical School Department of Biomedical Informatics 10 Shattuck Street BostonMA02115 United States School of Medicine and Public Health University of Wisconsin-Madison Office of Informatics and Information Technology 750 Highland Ave MadisonWI53705 United States University of Michigan Department of Computational Medicine & Bioinformatics Internal Medicine Human Genetics Environmental Health 100 Washtenaw Avenue Ann ArborMI48109 United States University of Kansas Medical Center Division of Medical Informatics Division of Pulmonary Critical Care and Sleep Medicine Department of Internal Medicine 3901 Rainbow Blvd Kansas CityKS66160 United States University of Antioquia Hospital Alma Máter de Antioquia Department of Internal Medicine Calle 64 N°51 D - 154 Medellín Colombia University of Pittsburgh Department of Biomedical Informatics 5607 Baum Blvd PittsburghPA15206 United States University of Pittsburgh Department of Neurology 3501 5th Avenue PittsburghPA15206 United States Boston Children's Hospital Computational Health Informatics Program 300 Longwood Avenue BostonMA02115 United States Boston Children's Hospital Department of Pediatrics 300 Longwood Avenue BostonMA02115 United States National University Health System Department of Surgery 1E Kent Ridge Rd Singapore119228 Singapore National University Health System Department of Diagnostic Imaging 1E Kent Ridge Rd Singapore119228 Singapore University of Michigan Department of Learning Health Sciences NCRC 100 2800 Plymouth Road Ann ArborMI48109 United States University of Kansas Medical Center Department of Surgery 3901 Rainbow Blvd Kansas CityKS66160 United States Istituti Clinici Scientifici Maugeri IRCCS Respiratory rehabilitation unit Via Maugeri 10 Pavia27100 Italy University of Kansas Medical Center 3901 Rainbow Blvd Kansas CityKS66160 United States University of Pavia Department of Electrical Computer and Biomedical Engineering via Ferrata 5 Pavia2710

Background: Physicians invest hours creating patient notes, which are rich in information but difficult for computers to analyze due to their unstructured format. GPT-4 reshaped our ability to process text, yet it is unknown how well this model can handle medical notes. This project aims to compare GPT-4’s ability to annotate medical notes against experienced physicians across three different languages at multiple institutions and countries. Methods: This study included eight sites from four countries - the United States, Colombia, Singapore, and Italy. Each site contributed seven de-identified notes (admission, progress, or consult) from hospitalized patients. GPT-4 assessed each note by answering 14 questions, including demographic information, clinical judgments, data quality, and patients’ eligibility for a hypothetical study enrollment. For validation, two physicians from each site independently evaluated GPT-4's responses. Findings: Overall, 56 medical notes, written in English, Italian, and Spanish, were analyzed. A total of 784 responses from GPT-4 were generated. Both physicians agreed with GPT-4’s response 79% of the time (622/784, 95%CI 76-82%). Only one of the two physicians agreed with GPT-4’s response 10% of the time (82/784, 95%CI 8-13%). Neither physician agreed with GPT-4’s response 10% of the time (80/784, 95%CI 8-13%). Both physicians agreed with GPT-4 more often in notes written in Spanish and Italian than in English, with agreement rates of 88% (86/98, 95%CI 79-93%), 84% (82/98, 95%CI 75-90%), and 77% (454/588, 95%CI 74-80%), respectively. Hallucinations were rare (10/784, 95%CI 0-2%). GPT-4 correctly selected patients for a hypothetical study enrollment based on three criteria 90% of the time (95%CI 81-98%). Interpretation: The findings indicate that GPT-4 annotations demonstrated a high agreement rate with physicians across all languages. We also demonstrate GPT-4's potential to assist in patient selection for studies. Funding: None. Declarati

关键词： Medical computing

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