Federated Multi-Label Learning (FMLL): Innovative Method for Classification Tasks in Animal Science. [PDF]
Animals (Basel)Ghasemkhani B +5 more
europepmc +1 more source
Gene function prediction based on combining gene ontology hierarchy with multi-instance multi-label learning. [PDF]
RSC Adv, 2018 Li Z +5 more
europepmc +1 more source
Escaping the Scaling Relationships in Oxygen Reduction Catalysis: Implications for PEM Fuel Cells
Advanced Materials, EarlyView.Escaping the scaling relationships of the oxygen reduction reaction is vital for hydrogen fuel cells. This outlook examines how interfacial heterogeneity, spanning the subsurface lattice, chemisorption layer, and near‐interface solvation volume, mechanistically decouples intermediate binding energetics.
Muhammad Bilal Wazir +2 more
wiley +1 more source
Multi-Instance Multi-Label Learning for Multi-Class Classification of Whole Slide Breast Histopathology Images. [PDF]
IEEE Trans Med Imaging, 2018 Mercan C +5 more
europepmc +1 more source
Advanced Materials, EarlyView.Coupled materials design enables a monolithic fiber that integrates complementary sensing regimes into a single wearable strand. By preserving informative signal features across subtle physiological deformation, large body motion, and mixed mechanical inputs, the dual‐gradient architecture generates synchronized, less redundant outputs that improve ...
Yunheum Lee +13 more
wiley +1 more source
Predicting human splicing branchpoints by combining sequence-derived features and multi-label learning methods. [PDF]
BMC Bioinformatics, 2017 Zhang W, Zhu X, Fu Y, Tsuji J, Weng Z.
europepmc +1 more source
Advanced Materials, EarlyView.Mixed‐cation lead mixed‐halide perovskites suffer from structural instabilities linked to nanoscale heterogeneity. To probe this non‐destructively, a low‐dose, concurrent 4D‐STEM and EDX methodology has been developed. Examining a (FA0.83Cs0.17)Pb(I0.8Br0.2)3 film revealed a complex mosaic of coexisting crystal structures. Crucially, local deficiencies
Jinseok Ryu +6 more
wiley +1 more source
Imbalanced multi-label learning for identifying antimicrobial peptides and their functional types. [PDF]
Bioinformatics, 2016 Lin W, Xu D.
europepmc +1 more source
Data‐Driven Materials Science for Energy‐Sustainable Applications
Advanced Materials, EarlyView.Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley +1 more source
Closed‐Loop Solid‐State Synthesis Planning for Materials Discovery With Large Language Models
Advanced Materials, EarlyView.Leveraging literature data, we build a large‐language‐model‐driven workflow that extracts synthesis steps from 4407 papers, retrieves similar precedents, and generates candidate solid‐state synthesis recipes. The system benchmarks against ground‐truth and then operates in a closed loop with experiments to synthesize oxy‐selenide electrolyte materials ...
Dong Won Jeon +9 more
wiley +1 more source