Zoekresultaten - "Machine Learning"

Investigating the Association between Nutrient Intake and Food Insecurity among Children and Adolescents in Palestine Using Machine Learning Techniques 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

Connect to this object online.

Identification of TXN and F5 as novel diagnostic gene biomarkers of the severe asthma based on bioinformatics and machine learning analysis door Lu Shou, Haidong He, Yi Wei, Xianrong Xu, Wenmin Wang, Jisheng Zheng

Connect to this object online.

A Genome-Wide Association Study and Machine-Learning Algorithm Analysis on the Prediction of Facial Phenotypes by Genotypes in Korean Women door Yoo HY, Lee KC, Woo JE, Park SH, Lee S, Joo J, Bae JS, Kwon HJ, Park BJ

Connect to this object online.

Automated Machine Learning Analysis of Patients With Chronic Skin Disease Using a Medical Smartphone App: Retrospective Study door Igor Bibi, Daniel Schaffert, Mara Blauth, Christian Lull, Jan Alwin von Ahnen, Georg Gross, Wanja Alexander Weigandt, Johannes Knitza, Sebastian Kuhn, Johannes Benecke, Jan Leipe, Astrid Schmieder, Victor Olsavszky

Connect to this object online.

The Use of Deep Learning and Machine Learning on Longitudinal Electronic Health Records for the Early Detection and Prevention of Diseases: Scoping Review door Laura Swinckels, Frank C Bennis, Kirsten A Ziesemer, Janneke F M Scheerman, Harmen Bijwaard, Ander de Keijzer, Josef Jan Bruers

Connect to this object online.

Development and validation of questionnaire-based machine learning models for predicting all-cause mortality in a representative population of China door Ziyi Li, Na Yang, Liyun He, Jialu Wang, Fan Ping, Wei Li, Lingling Xu, Huabing Zhang, Yuxiu Li

Connect to this object online.

Using machine learning to identify risk factors for pancreatic cancer: a retrospective cohort study of real-world data door Na Su, Na Su, Na Su, Rui Tang, Yice Zhang, Jiaqi Ni, Yimei Huang, Chunqi Liu, Chunqi Liu, Yuzhou Xiao, Yuzhou Xiao, Baoting Zhu, Yinglan Zhao, Yinglan Zhao

Connect to this object online.

Using Machine Learning Approaches to Explore Non-Cognitive Variables Influencing Reading Proficiency in English among Filipino Learners door Allan B. I. Bernardo, Macario O. Cordel, Rochelle Irene G. Lucas, Jude Michael M. Teves, Sashmir A. Yap, Unisse C. Chua

Connect to this object online.

Toward real‐world deployment of machine learning for health care: External validation, continual monitoring, and randomized clinical trials door Han Yuan

Connect to this object online.

Development of a machine learning tool to predict the risk of incident chronic kidney disease using health examination data door Yuki Yoshizaki, Kiminori Kato, Kazuya Fujihara, Hirohito Sone, Kohei Akazawa

Connect to this object online.

Spatial statistical machine learning models to assess the relationship between development vulnerabilities and educational factors in children in Queensland, Australia door Wala Draidi Areed, Aiden Price, Kathryn Arnett, Kerrie Mengersen

Connect to this object online.

Pharmacogenomic augmented machine learning in electronic health record alerts: A health system‐wide usability survey of clinicians door Caroline W. Grant, Jean Marrero‐Polanco, Jeremiah B. Joyce, Barbara Barry, Ashley Stillwell, Kellie Kruger, Therese Anderson, Heather Talley, Mary Hedges, Jose Valery, Richard White, Richard R. Sharp, Paul E. Croarkin, Liselotte N. Dyrbye, William V. Bobo, Arjun P. Athreya

Connect to this object online.

Machine learning-based risk factor analysis and prevalence prediction of intestinal parasitic infections using epidemiological survey data. door Aziz Zafar, Ziad Attia, Mehret Tesfaye, Sosina Walelign, Moges Wordofa, Dessie Abera, Kassu Desta, Aster Tsegaye, Ahmet Ay, Bineyam Taye

Connect to this object online.

Corrigendum: Using Machine Learning to Predict Cognitive Impairment Among Middle-Aged and Older Chinese: A Longitudinal Study door Haihong Liu, Haihong Liu, Xiaolei Zhang, Xiaolei Zhang, Haining Liu, Haining Liu, Haining Liu, Sheau Tsuey Chong, Sheau Tsuey Chong

Connect to this object online.

Using Machine Learning-Based Approaches for the Detection and Classification of Human Papillomavirus Vaccine Misinformation: Infodemiology Study of Reddit Discussions door Jingcheng Du, Sharice Preston, Hanxiao Sun, Ross Shegog, Rachel Cunningham, Julie Boom, Lara Savas, Muhammad Amith, Cui Tao

Connect to this object online.

Clinical outcomes of single blastocyst transfer with machine learning guided noninvasive chromosome screening grading system in infertile patients door Xiaoxi Li, Yaxin Yao, Dunmei Zhao, Xiufeng Chang, Yi Li, Huilan Lin, Huijuan Wei, Haiye Wang, Ying Mi, Lei Huang, Sijia Lu, Weimin Yang, Liyi Cai

Connect to this object online.

Predicting the risk factors of diabetic ketoacidosis-associated acute kidney injury: A machine learning approach using XGBoost door Tingting Fan, Jiaxin Wang, Luyao Li, Jing Kang, Wenrui Wang, Chuan Zhang

Connect to this object online.

Machine-Learning-Based Prediction of Photobiomodulation Effects on Older Adults With Cognitive Decline Using Functional Near-Infrared Spectroscopy door Kyeonggu Lee, Minyoung Chun, Bori Jung, Yunsu Kim, Chaeyoun Yang, JongKwan Choi, Jihyun Cha, Seung-Hwan Lee, Chang-Hwan Im

Connect to this object online.

Using image registration and machine learning to develop a workstation tool for rapid analysis of glomeruli in medical renal biopsies door David C Wilbur, Jason R Pettus, Maxwell L Smith, Lynn D Cornell, Alexander Andryushkin, Richard Wingard, Eric Wirch

Connect to this object online.

Machine learning models can predict cancer-associated disseminated intravascular coagulation in critically ill colorectal cancer patients door Li Qin, Li Qin, Jieling Mao, Jieling Mao, Min Gao, Min Gao, Jingwen Xie, Jingwen Xie, Zhikun Liang, Zhikun Liang, Xiaoyan Li, Xiaoyan Li

Connect to this object online.