Results 81 to 90 of about 7,950 (213)

Harnessing Large Language Models to Advance Microbiome Research: From Sequence Analysis to Clinical Applications

Advanced Intelligent Discovery, EarlyView.
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing, He Wang, Yangyang Sun, Xiaoquan Su, Shunyao Wu   +4 more
wiley   +1 more source

Enriching Cultural Heritage Knowledge Graph Metadata from Finnish Texts with Large Language Models

Digital Humanities in the Nordic and Baltic Countries Publications
This paper introduces the Finnish Named Entity Linker (FINEL), a tool that leverages Deep Learning models, including Large Language Models (LLMs), to recognize, disambiguate, and link Named Entities in Cultural Heritage texts.
Rafael Leal, Annastiina Ahola, Eero Hyvönen   +2 more
doaj   +1 more source

Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents

Advanced Intelligent Discovery, EarlyView.
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer, Muhammad Nabeel Asim, Shan Munir, Andreas Dengel   +3 more
wiley   +1 more source

SrpCNNeL: Serbian Model for Named Entity Linking [PDF]

Annals of computer science and information systems
Milica Ikonić Nešić, Saša Petalinkar, Ranka Stanković, Miloš Utvić, Olivera Kitanović   +4 more
doaj   +1 more source

Extracting Geographical References from Finnish Literature. Fully Automated Processing of Plain-Text Corpora

Journal of Computational Literary Studies
In the Atlas of Finnish Literature 1870-1940 project, we extract geographical information from a Finnish-language corpus of literary texts published between 1870 and 1940.
Asko Nivala, Harri Kiiskinen, Jasmine Westerlund, Juhana Saarelainen   +3 more
doaj   +2 more sources

Artificial Intelligence‐Driven Network Pharmacology: A Methodological Paradigm Shift Bridging Traditional Wisdom and Modern Science

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence is redefining network pharmacology (NP). By integrating knowledge graph engineering, geometric deep learning, multiomics anchoring, and generative reasoning, AI‐driven NP (AI‐NP) transforms static target mapping into dynamic, predictive modeling.
Cong Wang, Sile Hu, Rigahai Ji, Riguna A, Siqige Hao, Ma Zhuo, Yi‐Hung Chen, Bisihalatu Hu, Ulana Bai, Xigui Hada   +9 more
wiley   +1 more source

Accelerating the Discovery of Proton Conducting Electrolytes via Machine Learning‐Enabled Literature Mining

Advanced Intelligent Discovery, EarlyView.
An end‐to‐end knowledge discovery framework is established to automate high‐precision property extraction from small, specialized literature corpora. Utilizing a domain‐specific bidirectional encoder representation from a transformer model and data augmentation, the system accurately extracts and structures electrolyte performance data, ultimately ...
Gaheun Shin, Seongho Lee, Seulchan Kim, Ho‐Il Ji, Joonhee Kang   +4 more
wiley   +1 more source

Named entity linking of geospatial and host metadata in GenBank for advancing biomedical research. [PDF]

Database (Oxford), 2017
Tahsin T, Weissenbacher D, Jones-Shargani D, Magee D, Vaiente M, Gonzalez G, Scotch M.   +6 more
europepmc   +1 more source

How does the Kids SIPsmartER program impact the sugar‐sweetened beverage intake of students: An investigation beyond total treatment effect in randomized controlled trial

American Journal of Agricultural Economics, EarlyView.
Abstract This study develops and empirically estimates a structural framework to decompose the causal pathways of multilevel behavioral interventions targeting adolescent health behaviors. We apply this framework to the Kids SIPsmartER (KSS) program, a 6‐month, school‐based intervention evaluated through a clustered randomized controlled trial in rural
Naveen Abedin, Wen You, Annie Reid, Kathleen Porter, Brittany Kirkpatrick, Jamie Zoellner   +5 more
wiley   +1 more source

IRC-Bench: Recognizing Entities from Contextual Cues in First-Person Reminiscences

Machine Learning and Knowledge Extraction
When people recount personal memories, they often refer to people, places, and events indirectly, relying on contextual cues rather than explicit names.
Yehudit Aperstein, Eden Moran, Alexander Apartsin   +2 more
doaj   +1 more source