Results 221 to 230 of about 367,129 (284)
Cross‐Modal Denoising and Integration of Spatial Multi‐Omics Data with CANDIES
In this paper, we introduce CANDIES, which leverages a conditional diffusion model and contrastive learning to effectively denoise and integrate spatial multi‐omics data. We conduct extensive evaluations on diverse synthetic and real datasets, CANDIES shows superior performance on various downstream tasks, including denoising, spatial domain ...
Ye Liu +5 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
Autodelineation of Treatment Target Volume for Radiation Therapy Using Large Language Model-Aided Multimodal Learning. [PDF]
Rajendran P +13 more
europepmc +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
Bridging vision and touch: advancing robotic interaction prediction with self-supervised multimodal learning. [PDF]
Li L, Thuruthel TG.
europepmc +1 more source
Stable Diffusion Models Reveal a Persisting Human–AI Gap in Visual Creativity
This study examines visual creativity in humans and generative AI using the TCIA framework. Human artists outperform AI overall, yet structured human guidance substantially improves AI outputs and evaluations. Findings reveal that alignment with human creativity depends critically on contextual framing, highlighting both the promise and current ...
Silvia Rondini +8 more
wiley +1 more source
In this work, a bioinspired all‐in‐one underwater quality evaluation metamaterial, combining sound attenuation, diffuse reflection, and mechanical robustness, is proposed based on jumping spider locomotion and human skeletal biomechanics. Meanwhile, a CNN‑driven quality evaluation framework is established for theoretically dimension‐reduced ...
Hongze Li +8 more
wiley +1 more source
Discovering Interpretable Semantics from Radio Signals for Contactless Cardiac Monitoring
This study presents a semantic representation framework for clinically interpretable cardiac monitoring from contactless radio signals. It formulates radio semantic learning as an information‐bottleneck problem and approximates the objective via intra‐modal compression and cross‐modal alignment, structuring radio measurements into meaningful semantic ...
Jinbo Chen +10 more
wiley +1 more source
MULTIMODAL LEARNING TO IMPROVE CARDIAC LATE MECHANICAL ACTIVATION DETECTION FROM CINE MR IMAGES. [PDF]
Xing J +4 more
europepmc +1 more source
This study presents a wireless, non‐invasive strategy for neural repair by developing a biodegradable piezoelectric dural patch that, under transcranial ultrasound, generates localized electrical fields to drive endogenous neural stem cells toward neuronal differentiation and functional integration.
Pengbo Zhou +7 more
wiley +1 more source

