Results 131 to 140 of about 2,017,337 (259)
Dengue infection alters mosquito flight behavior, enabling detection using machine learning classifiers. This study analyzes 3D flight trajectories and evaluates multiple models, showing that longer sequence lengths improve classification performance.
Nouman Javed +3 more
wiley +1 more source
Correction: Primer on binary logistic regression
doaj +1 more source
This study demonstrates that cholesterol in messenger RNA‐lipid nanoparticles (mRNA‐LNPs) can be completely replaced with an immunopotentiating lipid, i.e., a synthetic analogue of the C‐type lectin receptor agonist monomycoloyl glycerol (MMG‐1), without compromising physicochemical properties, in vivo transfection efficiency, and immunogenicity of the
Abhijeet G. Lokras +19 more
wiley +1 more source
Improper reporting of multivariable logistic regression
Rajeev Kumar
doaj +1 more source
AI is transforming the research paradigm of battery materials and reshaping the entire landscape of battery technology. This comprehensive review summarizes the cutting‐edge applications of AI in the advancement of battery materials, underscores the critical challenges faced in harnessing the full potential of AI, and proposes strategic guidance for ...
Qingyun Hu +5 more
wiley +1 more source
Reliability of Pharmacodynamic Analysis by Logistic Regression [PDF]
Wei Lü, James M. Bailey
openalex +1 more source
Recycling of Thermoplastics with Machine Learning: A Review
This review shows how machine learning is revolutionizing mechanical, chemical, and biological pathways, overcoming traditional challenges and optimizing sorting, efficiency, and quality. It provides a detailed analysis of effective feature engineering strategies and establishes a forward‐looking research agenda for a truly circular thermoplastic ...
Rodrigo Q. Albuquerque +5 more
wiley +1 more source
Problems due to Small Samples and Sparse Data in Conditional Logistic Regression Analysis [PDF]
Sander Greenland +2 more
openalex +1 more source
Advances in integrating artificial intelligence into 3D bioprinting are systematically reviewed here. Machine learning, computer vision, robotics, natural language processing, and expert systems are examined for their roles in optimizing bioprinting parameters, real‐time monitoring, quality control, and predictive maintenance.
Joao Vitor Silva Robazzi +10 more
wiley +1 more source

