Search Results - "neural networks"

Performance and Limitation of Machine Learning Algorithms for Diabetic Retinopathy Screening: Meta-analysis by Jo-Hsuan Wu, T Y Alvin Liu, Wan-Ting Hsu, Jennifer Hui-Chun Ho, Chien-Chang Lee

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Using Domain Adaptation and Inductive Transfer Learning to Improve Patient Outcome Prediction in the Intensive Care Unit: Retrospective Observational Study by Maruthi Kumar Mutnuri, Henry Thomas Stelfox, Nils Daniel Forkert, Joon Lee

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Improving Diabetes-Related Biomedical Literature Exploration in the Clinical Decision-making Process via Interactive Classification and Topic Discovery: Methodology Development Stu... by Adrian Ahne, Guy Fagherazzi, Xavier Tannier, Thomas Czernichow, Francisco Orchard

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Predicting Emotional States Using Behavioral Markers Derived From Passively Sensed Data: Data-Driven Machine Learning Approach by Sükei, Emese, Norbury, Agnes, Perez-Rodriguez, M Mercedes, Olmos, Pablo M, Artés, Antonio

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An SEM-ANN approach to evaluate public awareness about COVID, A pathway toward adaptation effective strategies for sustainable development by Muhammad Tayyab Sohail, Muhammad Tayyab Sohail, Minghui Yang, Minghui Yang, Petra Maresova, Petra Maresova, Sohaib Mustafa

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Assessing the Generalizability of Deep Learning Models Trained on Standardized and Nonstandardized Images and Their Performance Against Teledermatologists: Retrospective Comparativ... by Ayooluwatomiwa I Oloruntoba, Tine Vestergaard, Toan D Nguyen, Zhen Yu, Maithili Sashindranath, Brigid Betz-Stablein, H Peter Soyer, Zongyuan Ge, Victoria Mar

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Using MATLAB software with Tomcat server and Java platform for remote image analysis in pathology by Markiewicz Tomasz

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Genomic analyses based on pulmonary adenocarcinoma in situ reveal early lung cancer signature by Dan Li, William Yang, Yifan Zhang, Jack Y Yang, Renchu Guan, Dong Xu, Mary Qu Yang

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The Use of Synthetic Electronic Health Record Data and Deep Learning to Improve Timing of High-Risk Heart Failure Surgical Intervention by Predicting Proximity to Catastrophic Deco... by Aixia Guo, Randi E. Foraker, Randi E. Foraker, Robert M. MacGregor, Faraz M. Masood, Brian P. Cupps, Michael K. Pasque

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Application of geospatial multi-agent system for simulation of different aspects of tuberculosis transmission by I.O. Semianiv, L.D. Todoriko, Ya.I. Vyklyuk, D.V. Nevinskyi

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Controlled and Real-Life Investigation of Optical Tracking Sensors in Smart Glasses for Monitoring Eating Behavior Using Deep Learning: Cross-Sectional Study by Simon Stankoski, Ivana Kiprijanovska, Martin Gjoreski, Filip Panchevski, Borjan Sazdov, Bojan Sofronievski, Andrew Cleal, Mohsen Fatoorechi, Charles Nduka, Hristijan Gjoreski

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التعرف الآلي على نوع التعديل الرقمي باستخدام الشبكات العصبية الصنعية by محمد بهلول

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Reflective Processes and Social Orientation at Different Stages of Professionalisation (on the Example of Preparation for Medical Activity) by G. V. Manuilov, G. G. Gorelova, E. A. Rylskaya, S. V. Morozova, N. N. Vasyagina

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Contributions of Artificial Intelligence Reported in Obstetrics and Gynecology Journals: Systematic Review by Ferdinand Dhombres, Jules Bonnard, Kévin Bailly, Paul Maurice, Aris T Papageorghiou, Jean-Marie Jouannic

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تأثير إضافة معامل الزمن على أداء الشبكة العصبية الاصطناعية في تقدير التّبخر اليومي في المنطقة الجبلية من الساحل السوري... by غطفان عمار, بادية حيدر

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Machine Learning-Based Prediction for 4-Year Risk of Metabolic Syndrome in Adults: A Retrospective Cohort Study by Zhang H, Chen D, Shao J, Zou P, Cui N, Tang L, Wang X, Wang D, Wu J, Ye Z

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Fast and Accurate Detection of COVID-19 Along With 14 Other Chest Pathologies Using a Multi-Level Classification: Algorithm Development and Validation Study by Albahli, Saleh, Yar, Ghulam Nabi Ahmad Hassan

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Artificial Intelligence for Digitising Industry - Applications

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Machine Learning and Its Application to Reacting Flows ML and Combustion /

Table of Contents: “…Introduction -- ML Algorithms, Techniques and their Application to Reactive Molecular Dynamics Simulations -- Big Data Analysis, Analytics & ML role -- ML for SGS Turbulence (including scalar flux) Closures -- ML for Combustion Chemistry -- Applying CNNs to model SGS flame wrinkling in thickened flame LES (TFLES) -- Machine Learning Strategy for Subgrid Modelling of Turbulent Combustion using Linear Eddy Mixing based Tabulation -- MILD Combustion-Joint SGS FDF -- Machine Learning for Principal Component Analysis & Transport -- Super Resolution Neural Network for Turbulent non-premixed Combustion -- ML in Thermoacoustics -- Concluding Remarks & Outlook.…”
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xxAI - Beyond Explainable AI International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers /

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