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The EMPOWER blended digital intervention for relapse prevention in schizophrenia: a feasibility cluster randomised controlled trial in Scotland and Australia

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The Lancet Psychiatry 2022年第6期9卷 477-486页

作者： Gumley, Andrew I Bradstreet, Simon Ainsworth, John Allan, Stephanie Alvarez-Jimenez, Mario Aucott, Lorna Birchwood, Maximillian Briggs, Andrew Bucci, Sandra Cotton, Sue M Engel, Lidia French, Paul Lederman, Reeva Lewis, Shôn Machin, Matthew MacLennan, Graeme McLeod, Hamish McMeekin, Nicola Mihalopoulos, Cathy Morton, Emma Norrie, John Schwannauer, Matthias Singh, Swaran P Sundram, Suresh Thompson, Andrew Williams, Chris Yung, Alison R Farhall, John Gleeson, John Glasgow Institute of Health and Wellbeing University of Glasgow Glasgow United Kingdom Division of Psychology and Mental Health School of Health Sciences Faculty of Biology Medicine and Health Manchester Academic Health Science Centre University of Manchester Manchester United Kingdom Division of Informatics Imaging and Data Sciences School of Health Sciences Faculty of Biology Medicine and Health Manchester Academic Health Science Centre University of Manchester Manchester United Kingdom Orygen Melbourne Melbourne VIC Australia Centre for Youth Mental Health University of Melbourne Melbourne VIC Australia School of Computing and Information Systems Faculty of Engineering and Information Technology University of Melbourne Melbourne VIC Australia Centre for Healthcare Randomised Trials (CHaRT) University of Aberdeen Aberdeen United Kingdom Centre for Mental Health and Wellbeing Research Warwick Medical School University of Warwick Warwick United Kingdom Department of Health Services Research and Policy London School of Hygiene & Tropical Medicine London United Kingdom Greater Manchester Mental Health NHS Foundation Trust Manchester United Kingdom School of Public Health and Preventive Medicine Monash University Melbourne VIC Australia Department of Psychiatry School of Clinical Sciences Monash University Melbourne VIC Australia School of Medicine Deakin University Melbourne VIC Australia Department of Psychiatry Manchester Metropolitan University Manchester United Kingdom Department of Psychiatry University of British Columbia Vancouver BC Canada The Usher Institute University of Edinburgh Edinburgh United Kingdom School for Health in Social Sciences University of Edinburgh Edinburgh United Kingdom Mental Health Program Monash Health Melbourne VIC Australia Department of Psychology and Counselling La Trobe University Melbourne VIC Australia NorthWestern Mental Health The Royal Melbourne Hospital Epping VIC Australia Healthy Brain and Mi

Background: Early warning signs monitoring by service users with schizophrenia has shown promise in preventing relapse but the quality of evidence is low. We aimed to establish the feasibility of undertaking a definitive randomised controlled trial to determine the effectiveness of a blended digital intervention for relapse prevention in schizophrenia. Methods: This multicentre, feasibility, cluster randomised controlled trial aimed to compare Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery (EMPOWER) with treatment as usual in community mental health services (CMHS) in Glasgow and Melbourne. CMHS were the unit of randomisation, selected on the basis of those that probably had five or more care coordinators willing to participate. Participants were eligible if they were older than 16 years, had a schizophrenia or related diagnosis confirmed via case records, were able to provide informed consent, had contact with CMHS, and had had a relapse within the previous 2 years. Participants were randomised within stratified clusters to EMPOWER or to continue their usual approach to care. EMPOWER blended a smartphone for active monitoring of early warning signs with peer support to promote self-management and clinical triage to promote access to relapse prevention. Main outcomes were feasibility, acceptability, usability, and safety, which was assessed through face-to-face interviews. App usage was assessed via the smartphone and self-report. Primary end point was 12 months. Participants, research assistants and other team members involved in delivering the intervention were not masked to treatment conditions. Assessment of relapse was done by an independent adjudication panel masked to randomisation group. The study is registered at ISRCTN (99559262). Findings: We identified and randomised eight CMHS (six in Glasgow and two in Melbourne) comprising 47 care coordinators. We recruited 86 service users between Jan 19 and Au

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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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Mathematical model of SARS-CoV-2 immunity predicts Paxlovid rebound

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Journal of Critical Care 2023年 74卷 154210-154210页

作者： Ranard, Benjamin L., MD, MSHP Vodovotz, Yoram, PhD Asgari, Shadnaz, PhD Megjhani, Murad, PhD Chow, Carson C., PhD Park, Soojin, MD Division of Pulmonary Allergy and Critical Care Medicine NewYork-Presbyterian Hospital/Columbia University Irving Medical Center New York NY USA Program for Hospital and Intensive Care Informatics Department of Neurology Columbia University Irving Medical Center New York NY USA Department of Surgery University of Pittsburgh Pittsburgh PA USA Department of Biomedical Engineering California State University Long Beach CA USA Department of Neurology NewYork-Presbyterian Hospital/Columbia University Irving Medical Center New York NY USA Laboratory of Biological Modeling National Institute of Diabetes and Digestive and Kidney Diseases National Institutes of Health Bethesda MD USA

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Short-Term Effects of a Therapeutic Diet on Biochemical Parameters in Hemodialysis Patients: A Randomized Crossover Trial

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Journal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation 2023年第6期33卷 731-739页

作者： Wan-Chuan Tsai Shih-Ping Hsu Yen-Ling Chiu Hon-Yen Wu Chia-Chin Luan Ju-Yeh Yang Mei-Fen Pai Cheng-Jui Lin Wan-Yu Lin Wen-Huei Sun Yu-Sen Peng Division of Nephrology Department of Internal Medicine Far Eastern Memorial Hospital New Taipei City Taiwan Center for General Education Lee-Ming Institute of Technology New Taipei City Taiwan. School of Life Science National Taiwan Normal University Taipei City Taiwan. Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan. Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei City Taiwan Faculty of Medicine School of Medicine National Yang-Ming University Taipei City Taiwan. Dietary Department Far Eastern Memorial Hospital New Taipei City Taiwan. Division of Nephrology Department of Internal Medicine Far Eastern Memorial Hospital New Taipei City Taiwan. Division of Nephrology Department of Internal Medicine Mackay Memorial Hospital Taipei City Taiwan Department of Medicine Mackay Medical College Taipei City Taiwan Mackay Junior College of Medicine Nursing and Management Taipei City Taiwan. Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei City Taiwan. Dietary Department Far Eastern Memorial Hospital New Taipei City Taiwan. Electronic address: 830636231@mail.femh.org.tw. Department of Applied Cosmetology Lee-Ming Institute of Technology New Taipei City Taiwan Department of Electrical Engineering Yuan Ze University Taoyuan City Taiwan. Electronic address: taan70@***.

OBJECTIVE:Although unhealthy diets exacerbate nutritional and metabolic derangements in patients with end-stage kidney disease (ESKD), how therapeutic diets that possess a variety of different dietary strategies acutely modify diverse biochemical parameters related to cardiovascular disease remains underexplored. METHODS:Thirty-three adults with end-stage kidney disease undergoing thrice-weekly hemodialysis participated in a randomized crossover trial comparing a therapeutic diet with their usual diets for 7 days, separated by a 4-week washout period. The therapeutic diet was characterized by adequate calorie and protein amounts, natural food ingredients with a low phosphorus-to-protein ratio, higher portions of plant-based food, and high fiber content. The primary outcome measure was the mean difference in the change-from-baseline intact fibroblast growth factor 23 (FGF23) level between the 2 diets. The other outcomes of interest included changes in mineral parameters, uremic toxins, and high-sensitivity C-reactive protein (hs-CRP) levels. RESULTS:Compared with the usual diet, the therapeutic diet lowered intact FGF23 levels (P = .001), decreased serum phosphate levels (P < .001), reduced intact parathyroid hormone (PTH) levels (P = .003), lowered C-terminal FGF23 levels (P = .03), increased serum calcium levels (P = .01), and tended to lower total indoxyl sulfate levels (P = .07) but had no significant effect on hs-CRP levels. Among these changes, reduction in serum phosphate level achieved in 2 days, modifications of intact PTH and calcium levels in 5 days, and reductions in intact and C-terminal FGF23 levels in 7 days of therapeutic diet intervention. CONCLUSION:Within the 1-week intervention period, the dialysis-specific therapeutic diet rapidly reversed mineral abnormalities and tended to decrease total indoxyl sulfate levels in patients undergoing hemodialysis but had no effect on inflammation. Future studies to assess the long-term effects of such therapeuti

关键词： FGF23 dialysis inflammation therapeutic diet uremic toxin

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Variations among Electronic Health Record and Physiologic Streaming Vital Signs for Use in Predictive Algorithms in Pediatric Severe Sepsis

ACI Open

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ACI Open 2022年第2期06卷 e76-e84页

作者： Adam C. Dziorny Robert B. Lindell Julie C. Fitzgerald Christopher P. Bonafide Department of Pediatrics University of Rochester School of Medicine Rochester New York United States Department of Biomedical Engineering University of Rochester Rochester New York United States Department of Anesthesiology and Critical Care Medicine Children's Hospital of Philadelphia Philadelphia Pennsylvania United States Pediatric Sepsis Program Children's Hospital of Philadelphia Philadelphia Pennsylvania United States Department of Pediatrics Children's Hospital of Philadelphia Philadelphia Pennsylvania United States Department of Biomedical and Health Informatics Children's Hospital of Philadelphia Philadelphia Pennsylvania United States

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Performance Analysis of a Modified Conjugate Gradient Algorithm for Optimization Models

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IOP Conference Series: Materials Science and engineering 2021年第1期1115卷

作者： S E Olowo I M Sulaiman M Mamat A E Owoyemi M A Zaini Kalfin S H Yuningsih Department of Mathematics Kano University of science and Technology Kano Nigeria Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Campus Kuala Nerus 22200 Terengganu Malaysia Department of General Studies. Federal College of Agricultural Produce Technology Kano Nigeria Institute of Engineering Mathematics Universiti Malaysia Perlis Kangar Malaysia Doctor Program of Mathematics Faculty of Mathematics and Natural Sciences Universitas Padjadjaran Indonesia Master Program of Mathematics Faculty of Mathematics and Natural Sciences Universitas Padjadjaran Indonesia

The Conjugate gradient (CG) algorithms is very important and widely used in solving optimization models. This is due to its simplicity as well as global convergence properties. Various line search procedures as usually employ in the analysis of the CG methods. Recently, many studies have been done aimed at improving the CG method. In this paper, an alternative formula for conjugate gradient coefficient has been proposed which possesses the global convergence properties under exact minimization condition. The result of the numerical computation has shown that this new coefficient performs better than the existing CG methods.

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Electronic Snellen Chart with Bluetooth Connection and Smartphone App

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IOP Conference Series: Materials Science and engineering 2020年第1期851卷

作者： H R Fajrin R N Adnan M Irfan I P Sari Department of Medical Electronics Technology Vocational Program Universitas Muhammadiyah Yogyakarta Bantul Yogyakarta Indonesia PKU Muhammadiyah Hospital Gamping Yogyakarta Indonesia Department of Informatics and Computer Engineering Jakarta State Polytechnic Depok Indonesia

Snellen chart is a tool to measure a person's visual acuity consisting of a series of black capitalized letters on a whiteboard arranged in rows. Snellen charts commonly used in many hospitals today are still in the form of posters, which are inefficient because to show the letters on the Snellen board, we still have to input it manually. Therefore, an electronic Snellen chart tool, which is considered to be more efficient and practical is made. The control device is an application on a cellphone connected via Bluetooth by utilizing LED as lighting while showing letters on the Snellen chart. It will facilitate ophthalmologists to perform examinations, and also show the letters by pressing a button on the cellphone so that they can install a trial lens without having to return to the Snellen board to indicate the letters. The testing method used in this study tested the Bluetooth connection and the tool's performance with seven questions on a questionnaire testing method to determine the eligibility of the instrument. The feasibility test results by using a questionnaire show that it has 82.8% feasibility percentage with 0.9 validity rate and 0.87 reliability; moreover, the results of 20 trials of Bluetooth connection testing have a 100% success rate. The questionnaire results showed that the tool is eligible and proper to use because the installation of the application is easy to do.

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Numerical Simulation of Spear Motion as Game Items

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Journal of Physics: Conference Series 2020年第1期1445卷

作者： R R Muhima S Mardi M Hariadi I Puspitasari Informatics Engineering Department ITATS Arief Rachman Hakim 100 Surabaya Indonesia Electrical Engineering Department Sepuluh Nopember Institute of Technology Indonesia Information System Study Program Faculty of Science and Technology Universitas Airlangga Jl. Mulyorejo Surabaya 60115 Indonesia

Game development in 3D is mostly done by characters, items and the environment. Game items such as character weapons modeled in 3D will be the attraction of a game. In this paper, spear motion as a game items is modeled in 3D. Nonlinear Equations Six Degrees of Freedom (6 DOF) are used for mathematical models of spear motion. The parameters studied in the motion model are: geometry, mass and aerodynamics. Spear aerodynamic parameters were analyzed using the Datcom method. Numerical simulation of mathematical models of spear motion with variations in the initial velocity of the throw and the direction of the throw. From the results of numerical simulation, the maximum range R = 131.7 m at the initial velocity V0 = 40 m/s, the direction of throw (angle θ0 = 35 deg, angle 0 = 10 deg, ψ0 = 0 deg). And the maximum height Hmax = 12.18 m is achieved at the initial velocity V0 = 20 m/s, direction of throw (angle θ0 = 35 deg, angle 0 = 40 deg, angle ψ0 = 0 deg).

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License plate Recognition for moving vehicles case : at night and under rain condition 2

License plate Recognition for moving vehicles case : at nigh...

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2nd International Conference on informatics and Computing, ICIC 2017

作者： Ismail, Muh Department of Informatics Electrical Engineering Study Program Hasanuddin University Makassar Indonesia

ISBN: (纸本)9781538629840

Research for the detection and identification of existing license plate focus on static image under different weather conditions. This research aims to detect and recognize the license plate on moving vehicle at night and under rain condition. The method used to detect license plate is Cascade Classifier with Local Binary Pattern (LBP) as a descriptor, top-hat transform for image enhancement, and recognizing character of license plate detected is using Optical Character Recognition (OCR) and Template Matching (TM). The testing process using 9 videos data with duration 30 seconds. The testing result that accuracy rates LBP OCR reach 77.42% increase 32.26% than without top-hat transform and LBP TM 64.52% increase 45.16% than without top-hat transform. © 2017 IEEE.

关键词： Local binary pattern

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Medical Knowledge-Guided Deep Learning for Imbalanced Medical Image Classification

arXiv

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arXiv 2021年

作者： Gao, Long Liu, Chang Arefan, Dooman Panigrahy, Ashok Zuley, Margarita L. Wu, Shandong Department of Radiology School of Medicine University of Pittsburgh 4200 Fifth Ave PittsburghPA15260 United States College of Computer National University of Defense Technology Changsha410073 China Department of Bioengineering Swanson School of Engineering University of Pittsburgh 4200 Fifth Ave PittsburghPA15260 United States Department of Radiology University of Pittsburgh University of Pittsburgh Medical Center Children’s Hospital of Pittsburgh 4401 Penn Ave PittsburghPA15224 United States Magee-Womens Hospital University of Pittsburgh Medical Center 300 Halket St PittsburghPA15213 United States Department of Biomedical Informatics University of Pittsburgh 4200 Fifth Ave PittsburghPA15260 United States Intelligent Systems Program University of Pittsburgh 4200 Fifth Ave PittsburghPA15260 United States

Deep learning models have gained remarkable performance on a variety of image classification tasks. However, many models suffer from limited performance in clinical or medical settings when data are imbalanced. To address this challenge, we propose a medical-knowledge-guided one-class classification approach that leverages domain-specific knowledge of classification tasks to boost the model’s performance. The rationale behind our approach is that some existing prior medical knowledge can be incorporated into data-driven deep learning to facilitate model learning. We design a deep learning-based one-class classification pipeline for imbalanced image classification, and demonstrate in three use cases how we take advantage of medical knowledge of each specific classification task by generating additional "middle" classes to achieve higher classification performances. We evaluate our approach on three different clinical image classification tasks (a total of 8459 images) and show superior model performance when compared to six state-of-the-art methods. © 2021, CC BY.

关键词： Image classification

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