Zoekresultaten - "Machine Learning"

Exploring the Underlying Mechanism of Shenyankangfu Tablet in the Treatment of Glomerulonephritis Through Network Pharmacology, Machine Learning, Molecular Docking, and Experimental Validation door Jin M, Ren W, Zhang W, Liu L, Yin Z, Li D

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Identification of small cell lung cancer patients who are at risk of developing common serious adverse event groups with machine learning door Linda Wanika, Neil D. Evans, Michael J. Chappell

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A hybrid machine learning/pharmacokinetic approach outperforms maximum a posteriori Bayesian estimation by selectively flattening model priors door Jasmine H. Hughes, Ron J. Keizer

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Transforming Clinical Data into Actionable Prognosis Models: Machine-Learning Framework and Field-Deployable App to Predict Outcome of Ebola Patients. door Andres Colubri, Tom Silver, Terrence Fradet, Kalliroi Retzepi, Ben Fry, Pardis Sabeti

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Improving the Accuracy of Ensemble Machine Learning Classification Models Using a Novel Bit-Fusion Algorithm for Healthcare AI Systems door Sashikala Mishra, Kailash Shaw, Debahuti Mishra, Shruti Patil, Ketan Kotecha, Satish Kumar, Simi Bajaj

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Automatic Grading of Stroke Symptoms for Rapid Assessment Using Optimized Machine Learning and 4-Limb Kinematics: Clinical Validation Study door Park, Eunjeong, Lee, Kijeong, Han, Taehwa, Nam, Hyo Suk

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Development and Validation of a Questionnaire to Assess the Level of Salt Intake in the Adult Population of the Russian Federation Using Machine Learning Methods door D. O. Dragunov, A. V. Sokolova, G. P. Arutjunov

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Exploring predictors of interaction among low-birth-weight infants and their caregivers: a machine learning-based random forest approach door Qihui Wang, Wenying Gao, Yi Duan, Zijin Ren, Ying Zhang

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Machine learning-based integration of network features and chemical structure of compounds for SARS‐CoV‐2 drug effect analysis door Julian Späth, Rui‐Sheng Wang, Maeve Humphrey, Jan Baumbach, Joseph Loscalzo

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Predicting the clinical subcutaneous absorption rate constant of monoclonal antibodies using only the primary sequence: a machine learning approach door Ronghua Bei, Justin Thomas, Shiven Kapur, Mahlet Woldeyes, Adam Rauk, Jason Robarge, Jiangyan Feng, Kaoutar Abbou Oucherif

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Clinical Performance of Paraoxonase-1-Related Variables and Novel Markers of Inflammation in Coronavirus Disease-19. A Machine Learning Approach door Elisabet Rodríguez-Tomàs, Simona Iftimie, Helena Castañé, Gerard Baiges-Gaya, Anna Hernández-Aguilera, María González-Viñas, Antoni Castro, Jordi Camps, Jorge Joven

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Predicting Effortful Control at 3 Years of Age from Measures of Attention and Home Environment in Infancy: A Machine Learning Approach door Mariel F. Musso, Sebastián Moyano, Josué Rico-Picó, Ángela Conejero, M. Ángeles Ballesteros-Duperón, Eduardo C. Cascallar, M. Rosario Rueda

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Predicting cesarean delivery among gravidas with morbid obesity-a machine learning approachAJOG Global Reports at a Glance door Rajasri Kolli, MS, Talayeh Razzaghi, PhD, Stephanie Pierce, MD, Rodney K. Edwards, MD, Marta Maxted, MD, MS, Pavan Parikh, MD, MS

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Identification of spatial clusters of potentially toxic elements in different soil types using unsupervised machine learning and compositional data analysis door Gevorg Tepanosyan, Zhenya Poghosyan, Lilit Sahakyan

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Identifying potential circulating miRNA biomarkers for the diagnosis and prediction of ovarian cancer using machine-learning approach: application of Boruta door Farzaneh Hamidi, Neda Gilani, Neda Gilani, Reza Arabi Belaghi, Reza Arabi Belaghi, Reza Arabi Belaghi, Hanif Yaghoobi, Esmaeil Babaei, Esmaeil Babaei, Parvin Sarbakhsh, Jamileh Malakouti

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Molecular Properties of Drugs Handled by Kidney OATs and Liver OATPs Revealed by Chemoinformatics and Machine Learning: Implications for Kidney and Liver Disease door Anisha K. Nigam, Anupam A. Ojha, Julia G. Li, Da Shi, Vibha Bhatnagar, Kabir B. Nigam, Ruben Abagyan, Sanjay K. Nigam

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Development and validation of machine learning-based risk prediction models of oral squamous cell carcinoma using salivary autoantibody biomarkers door Yi-Ju Tseng, Yi-Cheng Wang, Pei-Chun Hsueh, Chih-Ching Wu

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Machine Learning Analysis of Time-Dependent Features for Predicting Adverse Events During Hemodialysis Therapy: Model Development and Validation Study door Yi-Shiuan Liu, Chih-Yu Yang, Ping-Fang Chiu, Hui-Chu Lin, Chung-Chuan Lo, Alan Szu-Han Lai, Chia-Chu Chang, Oscar Kuang-Sheng Lee

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Application of machine learning methods for predicting infant mortality in Rwanda: analysis of Rwanda demographic health survey 2014-15 dataset door Emmanuel Mfateneza, Pierre Claver Rutayisire, Emmanuel Biracyaza, Sanctus Musafiri, Willy Gasafari Mpabuka

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Personal Health Information Inference Using Machine Learning on RNA Expression Data from Patients With Cancer: Algorithm Validation Study door Kweon, Solbi, Lee, Jeong Hoon, Lee, Younghee, Park, Yu Rang

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