Results 91 to 100 of about 59,770 (264)
His‐MMDM: Multi‐Domain and Multi‐Omics Translation of Histopathological Images with Diffusion Models
His‐MMDM is a diffusion model‐based framework for scalable multi‐domain and multi‐omics translation of histopathological images, enabling tasks from virtual staining, cross‐tumor knowledge transfer, and omics‐guided image editing. ABSTRACT Generative AI (GenAI) has advanced computational pathology through various image translation models.
Zhongxiao Li +13 more
wiley +1 more source
Long‐Tea‐CLIP (Contrastive Language‐Image Pre‐training) presents a multimodal AI framework that integrates visual, metabolomic, and sensory knowledge to grade green tea across appearance, soup color, aroma, taste, and infused leaf. By combining expert‐guided modeling with CLIP‐supervised learning, the system delivers fine‐grained quality evaluation and
Yanqun Xu +9 more
wiley +1 more source
AutoGeTS: Knowledge-based Automated Generation of Text Synthetics for Improving Text Classification
When developing text classification models for real world applications, one major challenge is the difficulty to collect sufficient data for all text classes. In this work, we address this challenge by utilizing large language models (LLMs) to generate synthetic data and using such data to improve the performance of the models without waiting for more ...
Xue, Chenhao +4 more
openaire +2 more sources
In a randomized clinical trial, we test the potential of combined nicotinamide (NAM) and pyridoxine (PN) to improve muscle recovery through muscle stem cell (MuSC) activity. Daily oral NAM and PN supplementation after high intensity muscle contractions enhances MuSC activation and differentiation, and accelerates muscle regeneration, providing new ...
Grith Højfeldt +14 more
wiley +1 more source
BackgroundSelf-narratives about traumatic experiences and symptoms are informative for early identification of potential patients; however, their use in clinical screening is limited.
Yuzhuo Yuan +4 more
doaj +1 more source
An Automated Text Document Classification Framework using BERT
Momna Ali Shah +3 more
openaire +1 more source
Categorizing Children: Automated Text Classification of CHILDES files
In this paper we present the application of machine learning text classification methods to two tasks: categorization of children’s speech in the CHILDES Database according to gender and age. Both tasks are binary. For age, we distinguish two age groups between the age of 1.9 and 3.0 years old.
Opsomer, Rob +4 more
openaire +1 more source
Genetic Diagnosis and Discovery Enabled by Large Language Models
We demonstrate that large language models (LLMs) can facilitate genetic diagnosis and discovery. LLMs were used to solve four types of genetic problems of sequentially increased complexity. An LLM‐based pipeline could analyze genetic variants in the genomic sequences of human hearing loss or rare genetic disease patients and assist in identifying ...
Tao Tu +25 more
wiley +1 more source
This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong +7 more
wiley +1 more source
Our study identifies selenium deficiency as a hallmark of MASH pathogenesis. Dietary selenium supplementation enhances hepatic fatty acid oxidation (FAO) and attenuates MASH progression by activating the PPARα pathway via selenoprotein H (SELENOH). This selenium‐SELENOH‐PPARα nexus redefines the functional scope of selenoproteins, moving from redox ...
Yuwei Zhang +11 more
wiley +1 more source

