9 papers · ranked by Valyu relevance
Amélie Barozet, Vincent Cabeli, Jean Ogier du Terrail, Alexey Rukhovich + 6 more
The development of climate-resilient crops would be greatly accelerated by models able to reason directly over plant genomic sequences and to pinpoint trait-associated regions or loci. Anticipating the impact of DNA base changes (variants) remains challenging, and understanding regulatory mechanisms is still an active…
Huihai Wu, Ashleigh Lister, Iain Macaulay, Katie Long + 10 more
Single-cell and spatial transcriptomics are transforming our understanding of cellular heterogeneity and tissue organization, yet their analytical complexity remains a major bottleneck. Here, we present EISCA and EISTA, two standardized, end-to-end pipelines for single-cell RNA- seq and imaging-based spatial…
Zichao Jin, Jiaoru Wang, Wenjiang Huang, Jingcheng Zhang + 2 more
Accurate, reliable, large-scale disease predictions are essential to ensure rice production. Existing disease prediction models often face a trade-off between interpretability and predictive capability, necessitating the integration of mechanistic knowledge and data-driven learning within a modelling framework.…
Julius F. Witte, Artur Lissin, Isabel Schober, Christian Ebeling + 16 more
The vast amount of existing data on microbial strains holds immense potential to revolutionize bioindustry through the application of Artificial Intelligence (AI). However, the training of robust predictive AI models requires large-scale, unified, and non-redundant microbial datasets, which is currently severely…
James Stewart-Evans, Emma Wilson, Tessa Langley, Angela Hands + 2 more
Objective: The objective of this scoping review was to map the body of knowledge on net gain and no-net-loss (net-outcome) objectives and approaches applicable to health in spatial planning and development policies and practice. Introduction: There is an established body of academic and gray literature addressing…
Atilio Barreda II, Carrie Diaz Eaton, Sam Hansen, Joseph E. Hibdon Jr. + 10 more
Mathematics researchers are becoming more involved with research questions at the interface of data science and social justice. This type of research needs to be grounded in the needs of the community in order to have significant impact. In this paper, we examine two examples of community-research partnerships in data…
Yilan Wu, Dun Jack Fu, Yukun Zhou, Siegfried K Wagner + 2 more
Background Large language model (LLM) agents capable of generating and executing statistical code from natural language may broaden access to clinical data analysis, yet which pipeline stages they perform reliably and which require expert oversight remain poorly defined. Objective This study aimed to evaluate the…
Panagiotis Douris, George Kodovazenitis
The integration of artificial intelligence (AI) into dentistry is reshaping clinical workflows, opening new possibilities for population-level public health monitoring. Machine learning approaches, such as convolutional neural networks and other deep learning architectures, are becoming more and more capable to exhibit…
Akemi Morohashi, Satoshi Yamashita, Takahiro Imaizumi, Takuto Sano + 3 more
1## Introduction The use of real-world data (RWD) to generate real-world evidence (RWE) has expanded globally to support regulatory decision-making, postmarketing surveillance, and clinical research . Indeed, regulatory authorities worldwide have increasingly used RWE derived from routine electronic health records…