Zoekresultaten - "Machine Learning"

A Sustainable Model for Emergency Medical Services in Developing Countries: A Novel Approach Using Partial Outsourcing and Machine Learning door Rathore N, Jain PK, Parida M

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Predictive models for small-for-gestational-age births in women exposed to pesticides before pregnancy based on multiple machine learning algorithms door Xi Bai, Zhibo Zhou, Mingliang Su, Yansheng Li, Liuqing Yang, Kejia Liu, Hongbo Yang, Huijuan Zhu, Shi Chen, Hui Pan

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The help-seeking process and predictors of mental health care use among individuals with depressive symptoms: a machine learning approach door Vanessa Juergensen, Lina-Jolien Peter, David Steyrl, Cindy Sumaly Lor, Anh Phi Bui, Thomas McLaren, Holger Muehlan, Holger Muehlan, Samuel Tomczyk, Silke Schmidt, Georg Schomerus, Georg Schomerus

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Predicting Mortality in Intensive Care Unit Patients With Heart Failure Using an Interpretable Machine Learning Model: Retrospective Cohort Study door Jili Li, Siru Liu, Yundi Hu, Lingfeng Zhu, Yujia Mao, Jialin Liu

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Virtual Screening Based on Machine Learning Explores Mangrove Natural Products as KRAS^G12C Inhibitors door Lianxiang Luo, Tongyu Zheng, Qu Wang, Yingling Liao, Xiaoqi Zheng, Ai Zhong, Zunnan Huang, Hui Luo

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Improving the Prediction of Survival in Cancer Patients by Using Machine Learning Techniques: Experience of Gene Expression Data: A Narrative Review door Azadeh BASHIRI, Marjan GHAZISAEEDI, Reza SAFDARI, Leila SHAHMORADI, Hamide EHTESHAM

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Signatures of illness in children requiring unplanned intubation in the pediatric intensive care unit: A retrospective cohort machine-learning study door Michael C. Spaeder, Michael C. Spaeder, J. Randall Moorman, J. Randall Moorman, Liza P. Moorman, Liza P. Moorman, Michelle A. Adu-Darko, Jessica Keim-Malpass, Jessica Keim-Malpass, Douglas E. Lake, Douglas E. Lake, Matthew T. Clark, Matthew T. Clark

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Identifying Key Factors for Predicting the Age at Peak Height Velocity in Preadolescent Team Sports Athletes Using Explainable Machine Learning door Nikolaos-Orestis Retzepis, Alexandra Avloniti, Christos Kokkotis, Maria Protopapa, Theodoros Stampoulis, Anastasia Gkachtsou, Dimitris Pantazis, Dimitris Balampanos, Ilias Smilios, Athanasios Chatzinikolaou

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Machine Learning Approach for Predicting the Impact of Food Insecurity on Nutrient Consumption and Malnutrition in Children Aged 6 Months to 5 Years door Radwan Qasrawi, Sabri Sgahir, Maysaa Nemer, Mousa Halaikah, Manal Badrasawi, Malak Amro, Stephanny Vicuna Polo, Diala Abu Al-Halawa, Doa'a Mujahed, Lara Nasreddine, Ibrahim Elmadfa, Siham Atari, Ayoub Al-Jawaldeh

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Big data analysis and artificial intelligence in epilepsy - common data model analysis and machine learning-based seizure detection and forecasting door Yoon Gi Chung, Yonghoon Jeon, Sooyoung Yoo, Hunmin Kim, Hee Hwang

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CRlncRC: a machine learning-based method for cancer-related long noncoding RNA identification using integrated features door Xuan Zhang, Jun Wang, Jing Li, Wen Chen, Changning Liu

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A machine learning strategy for the identification of key in silico descriptors and prediction models for IgG monoclonal antibody developability properties door Andrew B. Waight, David Prihoda, Rojan Shrestha, Kevin Metcalf, Marc Bailly, Marco Ancona, Talal Widatalla, Zachary Rollins, Alan C Cheng, Danny A. Bitton, Laurence Fayadat-Dilman

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Exploring the role of Yuxuebi tablet in neuropathic pain with the method of similarity research of drug pharmacological effects based on unsupervised machine learning door Xiao Du, Xiao Du, Chunhui Zhao, Yujie Xi, Pengfei Lin, Huihui Liu, Shuling Wang, Feifei Guo

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Subjective Well-Being of Chinese Sina Weibo Users in Residential Lockdown During the COVID-19 Pandemic: Machine Learning Analysis door Wang, Yilin, Wu, Peijing, Liu, Xiaoqian, Li, Sijia, Zhu, Tingshao, Zhao, Nan

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Black-white differences in chronic stress exposures to predict preterm birth: interpretable, race/ethnicity-specific machine learning model door Sangmi Kim, Patricia A. Brennan, George M. Slavich, Vicki Hertzberg, Ursula Kelly, Anne L. Dunlop

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Improving Teaching and Learning in Higher Education through Machine Learning: Proof of Concept' of AI's Ability to Assess the Use of Key Microskills door Christopher Dann, Shirley O'Neill, Seyum Getenet, Subrata Chakraborty, Khaled Saleh, Kun Yu

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Construction of Autophagy-Related Gene Classifier for Early Diagnosis, Prognosis and Predicting Immune Microenvironment Features in Sepsis by Machine Learning Algorithms door Chen Z, Zeng L, Liu G, Ou Y, Lu C, Yang B, Zuo L

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Pediatric Injury Surveillance From Uncoded Emergency Department Admission Records in Italy: Machine Learning-Based Text-Mining Approach door Danila Azzolina, Silvia Bressan, Giulia Lorenzoni, Giulia Andrea Baldan, Patrizia Bartolotta, Federico Scognamiglio, Andrea Francavilla, Corrado Lanera, Liviana Da Dalt, Dario Gregori

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The Random Forest Model Has the Best Accuracy Among the Four Pressure Ulcer Prediction Models Using Machine Learning Algorithms door Song J, Gao Y, Yin P, Li Y, Li Y, Zhang J, Su Q, Fu X, Pi H

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A regulatory science initiative to harmonize and standardize digital pathology and machine learning processes to speed up clinical innovation to patients door Hetal Desai Marble, Richard Huang, Sarah Nixon Dudgeon, Amanda Lowe, Markus D Herrmann, Scott Blakely, Matthew O Leavitt, Mike Isaacs, Matthew G Hanna, Ashish Sharma, Jithesh Veetil, Pamela Goldberg, Joachim H Schmid, Laura Lasiter, Brandon D Gallas, Esther Abels, Jochen K Lennerz

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