Novel approach for noninvasive pelvic floor muscle strength measurement using extracorporeal surface perineal pressure measurement and machine learning modeling by Ui-jae Hwang, Sun-hee Ahn, Hyeon-ju Lee, Yurin Jeon, Myung Jae Jeon

“…Seven ESPP variables were calculated based on ESPP data and intra- and inter-rater reliabilities were assessed. Machine learning algorithms predicted bladder base displacement from ESPP variables. …”
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Machine learning prediction models for mortality risk in sepsis-associated acute kidney injury: evaluating early versus late CRRT initiation by Chuanren Zhuang, Ruomeng Hu, Ke Li, Zhengshuang Liu, Songjie Bai, Sheng Zhang, Xuehuan Wen

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Novel Unsupervised Machine Learning Method for Identifying Falling from Height Hazards in Building Information Models through Path Simulation Sampling by Yu Yan, Shen Zhang, Xingyu Wang, Xuechun Li

“…To address this issue, we proposed a new identification method for FFH risk points by incorporating BIM, path simulation, and machine learning techniques. Our approach, based on the likelihood exposure consequence criterion, efficiently identified and prioritized hazardous FFH risk points. …”
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Machine Learning for Movement Pattern Changes during Kinect-Based Mixed Reality Exercise Programs in Women with Possible Sarcopenia: Pilot Study by Yunho Sung, Ji-won Seo, Byunggul Lim, Shu Jiang, Xinxing Li, Parivash Jamrasi, So Young Ahn, Seohyun Ahn, Yuseon Kang, Hyejung Shin, Donghyun Kim, Dong Hyun Yoon, Wook Song

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PhyIndBC: Development of a machine learning tool for screening of potential breast cancer inhibitors from phytochemicalsGitHub by Agneesh Pratim Das, Subhash M. Agarwal

Subjects: “…Machine learning…”
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A machine learning model to predict the risk factors causing feelings of burnout and emotional exhaustion amongst nursing staff in South Africa by Maria Magdalena Van Zyl-Cillié, Jacoba H. Bührmann, Alwiena J. Blignaut, Derya Demirtas, Siedine K. Coetzee

Subjects: “…Supervised machine learning model…”
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Enhancing Manufacturing Precision: Leveraging Motor Currents Data of Computer Numerical Control Machines for Geometrical Accuracy Prediction Through Machine Learning by Lucijano Berus, Jernej Hernavs, David Potocnik, Kristijan Sket, Mirko Ficko

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Bayesian optimization with Gaussian-process-based active machine learning for improvement of geometric accuracy in projection multi-photon 3D printing by Jason E. Johnson, Ishat Raihan Jamil, Liang Pan, Guang Lin, Xianfan Xu

“…In this work, an active machine learning based framework is presented for determining optimal process parameters for the recently developed, high-speed, layer-by-layer continuous projection 3D printing process. …”
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Toward a Next Generation Particle Precipitation Model: Mesoscale Prediction Through Machine Learning (a Case Study and Framework for Progress) by Ryan M. McGranaghan, Jack Ziegler, Téo Bloch, Spencer Hatch, Enrico Camporeale, Kristina Lynch, Mathew Owens, Jesper Gjerloev, Binzheng Zhang, Susan Skone

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Derivation and validation of a clinical predictive model for longer duration diarrhea among pediatric patients in Kenya using machine learning algorithms by Billy Ogwel, Vincent H. Mzazi, Alex O. Awuor, Caleb Okonji, Raphael O. Anyango, Caren Oreso, John B. Ochieng, Stephen Munga, Dilruba Nasrin, Kirkby D. Tickell, Patricia B. Pavlinac, Karen L. Kotloff, Richard Omore

Subjects: “…Machine Learning…”
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Retraction Note: A prospective diagnostic model for breast cancer utilizing machine learning to examine the molecular immune infiltrate in HSPB6 by Lizhe Wang, Yu Wang, Yueyang Li, Li Zhou, Sihan Liu, Yongyi Cao, Yuzhi Li, Shenting Liu, Jiahui Du, Jin Wang, Ting Zhu

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BÜYÜK VERİ ANALİZİNDE YAPAY ZEKÂ VE MAKİNE ÖĞRENMESİ UYGULAMALARI - ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING APPLICATIONS IN BIG DATA ANALYSIS by Muhammet Atalay, Enes Çelik

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Solar Energy Forecasting Framework Using Prophet Based Machine Learning Model: An Opportunity to Explore Solar Energy Potential in Muscat Oman by Mazhar Baloch, Mohamed Shaik Honnurvali, Adnan Kabbani, Touqeer Ahmed, Sohaib Tahir Chauhdary, Muhammad Salman Saeed

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Predicting child mortality determinants in Uttar Pradesh using Machine Learning: Insights from the National Family and Health Survey (2019–21) by Pinky Pandey, Sacheendra Shukla, Niraj Kumar Singh, Mukesh Kumar

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Predicting pregnancy loss and its determinants among reproductive-aged women using supervised machine learning algorithms in Sub-Saharan Africa by Tirualem Zeleke Yehuala, Sara Beyene Mengesha, Nebebe Demis Baykemagn

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Ocular Biometry OCR: a machine learning algorithm leveraging optical character recognition to extract intra ocular lens biometry measurements by Anish Salvi, Leo Arnal, Kevin Ly, Gabriel Ferreira, Sophia Y. Wang, Sophia Y. Wang, Curtis Langlotz, Curtis Langlotz, Vinit Mahajan, Vinit Mahajan, Chase A. Ludwig, Chase A. Ludwig

“…To ensure the models’ predictions could be put into a machine learning-ready format, artifacts were removed from categorical text data through manual modification where necessary. …”
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Development and validation of a screening tool for sepsis without laboratory results in the emergency department: a machine learning studyResearch in context by Shan Jiang, Shuai Dai, Yulin Li, Xianlong Zhou, Cheng Jiang, Cong Tian, Yana Yuan, Chengwei Li, Yan Zhao

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On-Demand Gait-Synchronous Electrical Cueing in Parkinson's Disease Using Machine Learning and Edge Computing: A Pilot Study by Ardit Dvorani, Constantin Wiesener, Christina Salchow-Hommen, Magdalena Jochner, Lotta Spieker, Matej Skrobot, Hanno Voigt, Andrea Kuhn, Nikolaus Wenger, Thomas Schauer

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Explore the factors related to the death of offspring under age five and appraise the hazard of child mortality using machine learning techniques in Bangladesh by Ashikur Rahman, Md. Habibur Rahman

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Leaf Water Potential in a Mixed Mediterranean Forest from Machine Learning and Unmanned Aerial Vehicle (UAV)-Based Hyperspectral Imaging by Netanel Fishman, Yehuda Yungstein, Assaf Yaakobi, Sophie Obersteiner, Laura Rez, Gabriel Mulero, Yaron Michael, Tamir Klein, David Helman

“…We compared the machine learning model results with linear models based on spectral indices and the NDSI. …”
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