Results 151 to 160 of about 271,697 (289)
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
A Comparative Metabolomics Study of Multiple Urological Diseases by Highly Sensitive Dansylation Isotope Labeling LC-MS. [PDF]
Wang WH +9 more
europepmc +1 more source
A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley +1 more source
First Report of Entrectinib as a Treatment Option for Pure Squamous Cell Carcinoma Harboring <i>ROS1</i> Rearrangement: Exploring the Role of Next-Generation Sequencing in Targeted Therapy. [PDF]
Tang YJ, Chen RH, Lu YS, Wu CE.
europepmc +1 more source
Five-Second Squeeze Testing in 333 Professional and Semiprofessional Male Ice Hockey Players: How Are Hip and Groin Symptoms, Strength, and Sporting Function Related? [PDF]
Tobias Wörner +2 more
openalex +1 more source
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source
(Poly)Borylated Species as Modern Reactive Groups toward Unusual Synthetic Applications
In this review, we spotlight recent breakthroughs in α‐polyboron‐substituted carbon‐centered intermediates (carbanion, carbocation, radical, and carbene) and polyborylated alkenes. By bridging fundamental reactivity with the application potential of these extraordinary species, we hope this review will serve as a roadmap for harnessing these unique ...
Nadim Eghbarieh +5 more
wiley +2 more sources

