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In BMJ global health
Marshall Iain James, L’Esperance Veline, Marshall Rachel, Thomas James, Noel-Storr Anna, Soboczenski Frank, Nye Benjamin, Nenkova Ani, Wallace Byron C
geographic information systems, randomised control trial
Investigation of Influential Factors of Predicting Individuals' Use and Non-use of Fitness and Diet Apps on Smartphones: Application of the Machine Learning Algorithm (XGBoost).
In American journal of health behavior
Cho Jaehee, Kim Sehwan, Jeong Gwangjin, Kim Chonghye, Seo Ja-Kyoung
Gandi Carlo, Vaccarella Luigi, Bientinesi Riccardo, Racioppi Marco, Pierconti Francesco, Sacco Emilio
Bladder cancer, artificial intelligence, deep learning, machine learning, neural network
Viscosity of Ionic Liquids: Application of the Eyring's Theory and a Committee Machine Intelligent System.
In Molecules (Basel, Switzerland)
Mousavi Seyed Pezhman, Atashrouz Saeid, Nait Amar Menad, Hemmati-Sarapardeh Abdolhossein, Mohaddespour Ahmad, Mosavi Amir
CMIS modeling, Eyring’s theory, artificial intelligence, artificial neural networks, ionic liquids, machine intelligent system, machine learning, viscosity
How Resiliency and Hope Can Predict Stress of Covid-19 by Mediating Role of Spiritual Well-being Based on Machine Learning.
In Journal of religion and health
Nooripour Roghieh, Hosseinian Simin, Hussain Abir Jaafar, Annabestani Mohsen, Maadal Ameer, Radwin Laurel E, Hassani-Abharian Peyman, Pirkashani Nikzad Ghanbari, Khoshkonesh Abolghasem
Covid-19, Hope, Machine learning, Resiliency, Spiritual well-being, Stress
In Healthcare (Basel, Switzerland)