Ohcanbohtosat - "automated machine learning"

Development of a pharmaceutical science systematic review process using a semi‐automated machine learning tool: Intravenous drug compatibility in the neonatal intensive care setting Dahkki D. Thisuri N. De Silva, Brioni R. Moore, Tobias Strunk, Michael Petrovski, Vanessa Varis, Kevin Chai, Leo Ng, Kevin T. Batty

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Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) Technologies

Fáttát: “…automated machine learning…”
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The 8th International Conference on Time Series and Forecasting

Fáttát: “… automated machine learning…”
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Machine learning-assisted rapid determination for traditional Chinese Medicine Constitution Dahkki Wen Sun, Minghua Bai, Ji Wang, Bei Wang, Yixing Liu, Qi Wang, Dongran Han

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Detection of electricity theft in developing countries-A machine learning approach Dahkki Leonardo Grant, Haniph Latchman, Kolapo Alli

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Democratic Frontiers Algorithms and Society

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Integrated QSAR Models for Prediction of Serotonergic Activity: Machine Learning Unveiling Activity and Selectivity Patterns of Molecular Descriptors Dahkki Natalia Łapińska, Adam Pacławski, Jakub Szlęk, Aleksander Mendyk

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Diabetic retinopathy pathological signs detection using image enhancement technique and deep learning / Abdul Hafiz Abu Samah ...[et al.] Dahkki Abu Samah, Abdul Hafiz, Ahmad, Fadzil, Osman, Muhammad Khusairi, Md Tahir, Noritawati, Idris, Mohaiyedin, Abd. Aziz, Nor Azimah

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Democratic Frontiers Algorithms and Society

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A novel oppositional binary crow search algorithm with optimal machine learning based postpartum hemorrhage prediction model Dahkki Sujatha Krishnamoorthy, Yihang Liu, Kun Liu

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Advanced neuroimaging techniques for evaluating pediatric epilepsy Dahkki Yun Jeong Lee

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Advanced Optimization Methods and Big Data Applications in Energy Demand Forecast

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Curated Database and Preliminary AutoML QSAR Model for 5-HT1A Receptor Dahkki Natalia Czub, Adam Pacławski, Jakub Szlęk, Aleksander Mendyk

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Transfer Learning for Risk Classification of Social Media Posts: Model Evaluation Study Dahkki Howard, Derek, Maslej, Marta M, Lee, Justin, Ritchie, Jacob, Woollard, Geoffrey, French, Leon

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Discovery of Depression-Associated Factors From a Nationwide Population-Based Survey: Epidemiological Study Using Machine Learning and Network Analysis Dahkki Sang Min Nam, Thomas A Peterson, Kyoung Yul Seo, Hyun Wook Han, Jee In Kang

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Risk and Protective Factors in the COVID-19 Pandemic: A Rapid Evidence Map Dahkki Rebecca Elmore, Lena Schmidt, Juleen Lam, Brian E. Howard, Arpit Tandon, Christopher Norman, Jason Phillips, Mihir Shah, Shyam Patel, Tyler Albert, Debra J. Taxman, Ruchir R. Shah

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An Easy-to-Use Machine Learning Model to Predict the Prognosis of Patients With COVID-19: Retrospective Cohort Study Dahkki Kim, Hyung-Jun, Han, Deokjae, Kim, Jeong-Han, Kim, Daehyun, Ha, Beomman, Seog, Woong, Lee, Yeon-Kyeng, Lim, Dosang, Hong, Sung Ok, Park, Mi-Jin, Heo, JoonNyung

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The Impact of Digital Hospitals on Patient and Clinician Experience: Systematic Review and Qualitative Evidence Synthesis Dahkki Oliver J Canfell, Leanna Woods, Yasaman Meshkat, Jenna Krivit, Brinda Gunashanhar, Christine Slade, Andrew Burton-Jones, Clair Sullivan

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Genome-wide association meta-analysis for early age-related macular degeneration highlights novel loci and insights for advanced disease Dahkki Thomas W. Winkler, Felix Grassmann, Caroline Brandl, Christina Kiel, Felix Günther, Tobias Strunz, Lorraine Weidner, Martina E. Zimmermann, Christina A. Korb, Alicia Poplawski, Alexander K. Schuster, Martina Müller-Nurasyid, Annette Peters, Franziska G. Rauscher, Tobias Elze, Katrin Horn, Markus Scholz, Marisa Cañadas-Garre, Amy Jayne McKnight, Nicola Quinn, Ruth E. Hogg, Helmut Küchenhoff, Iris M. Heid, Klaus J. Stark, Bernhard H. F. Weber

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