Results 131 to 140 of about 141,868 (281)
Mixed Mutual Transfer for Long-Tailed Image Classification
Real-world datasets often follow a long-tailed distribution, where a few majority (head) classes contain a large number of samples, while many minority (tail) classes contain significantly fewer samples.
Ning Ren, Xiaosong Li, Yanxia Wu, Yan Fu
doaj +1 more source
We developed a nanoparticle named OAF, which simultaneously targeted to both the brain and liver via the transferrin receptor 1 (TfR1) receptor, promoting lipoprotein receptor‐related protein 1 (LRP1) expression to enhance amyloid‐beta (Aβ) clearance. In AD mice model, OAF significantly reduced Aβ deposition and cognitive impairment, while a mitigating
Wenshuai Gong +8 more
wiley +1 more source
INB3P is a multimodal framework for blood–brain barrier‐penetrating peptide prediction under extreme data scarcity and class imbalance. By combining physicochemical‐guided augmentation, sequence–structure co‐attention, and imbalance‐aware optimization, it improves predictive performance and interpretability.
Jingwei Lv +11 more
wiley +1 more source
Accurate prediction of early recurrence in pancreatic ductal adenocarcinoma is vital for optimizing treatment. A novel, integrated radiomics‐pathology machine learning model successfully forecasts recurrence risks by analyzing preoperative CT images and computational pathology.
Sihang Cheng +17 more
wiley +1 more source
It is innovatively utilized single‐cell RNA sequencing to explore the underlying causes of diabetes mellitus‐induced erectile dysfunction, followed by machine learning‐driven design of a single‐atom nanozyme (Fe‐DMOF) for precision treatment of erectile dysfunction.
Xiang Zhou +8 more
wiley +1 more source
Imbalanced learning: Improving classification of diabetic neuropathy from magnetic resonance imaging. [PDF]
Teh K +4 more
europepmc +1 more source
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
We investigate whether Montessori and traditional schooling systems shape the developmental trajectory of large‐scale brain dynamics in different ways. We quantify the arrow of time (“non‐reversibility”) in neural activity during resting state and movie‐watching, revealing distinct maturational patterns.
Elvira del Agua +6 more
wiley +1 more source
Machine learning is proving to be an ideal tool for materials design, capable of predicting forward structure-property relationships, and inverse property-structure relationships.
A S Barnard
doaj +1 more source
Advanced Technologies for Characterizing and Detecting Battery Thermal Failure: A Review
Illustration of advanced characterization techniques to predict battery thermal failure. ABSTRACT Energy storage is essential in accelerating the global transition toward clean and sustainable energy across various sectors. Lithium‐ion batteries (LIBs) have become increasingly significant for energy storage due to their high energy density, low ...
Yongxiu Chen +5 more
wiley +1 more source

