Results 231 to 240 of about 2,611,781 (277)
Deep learning in obsessive-compulsive disorder: a narrative review. [PDF]
Zaboski BA+3 more
europepmc +1 more source
This work explores the MOF landscape to select a single, optimal candidate for successfully delivering cancer drugs (gemcitabine, paclitaxel, SN‐38) into tough pancreatic tumors. Machine learning and simulations guide this search, demonstrating colloidal stability, excellent biocompatibility, cellular uptake, and sustained release.
Francesca Melle+9 more
wiley +1 more source
Evidential deep learning-based drug-target interaction prediction. [PDF]
Zhao Y+20 more
europepmc +1 more source
Hierarchically MOF‐Based Porous Monolith Composites for Atmospheric Water Harvesting
This review explores the design of hierarchical porous materials for atmospheric water harvesting, focusing on metal‐organic frameworks (MOFs) and porous monoliths. Emphasis is placed on integrating MOF nanoscale porosity with the microscale channels of monolithic scaffolds to enhance sorption‐desorption performance.
Mahyar Panahi‐Sarmad+7 more
wiley +1 more source
Student engagement assessment using multimodal deep learning. [PDF]
Yan L, Wu X, Wang Y.
europepmc +1 more source
This review describes recent developments in the design and synthesis of metal–organic frameworks (MOF)/textile composites for the detoxification of chemical warfare agent and simulants with extensive discussion on the advantages and disadvantages of different methods.
Zhihua Cheng+4 more
wiley +1 more source
Breast Cancer Classification with Various Optimized Deep Learning Methods. [PDF]
Güler M+4 more
europepmc +1 more source
Adsorption and Separation by Flexible MOFs
Flexible metal–organic frameworks (MOFs) present significant potential for gas storage and separation due to their structural dynamic. This review explores the rationale behind the flexible MOFs' enhanced working capacity and separation factors. It also addresses key challenges, including phase transition kinetics, crystal robustness, cycling, shaping,
Irena Senkovska+4 more
wiley +1 more source
Deep learning prediction of noise-driven nonlinear instabilities in fibre optics. [PDF]
Boussafa Y+9 more
europepmc +1 more source
Retrospective Review on Reticular Materials: Facts and Figures Over the Last 30 Years
To shape the future course of research in reticular materials, this work reflects on the progress over the past 30 years, complemented by input from the community of 228 active researchers through a global, crowdsourced survey: ranging from demographics, how it works, publish and interact, to highlights on both academic and industrial milestones, as ...
Aamod V. Desai+8 more
wiley +1 more source