Results 111 to 120 of about 316,892 (282)
Query-Based Named Entity Recognition
In this paper, we propose a new strategy for the task of named entity recognition (NER). We cast the task as a query-based machine reading comprehension task: e.g., the task of extracting entities with PER is formalized as answering the question of "which person is mentioned in the text ?".
Yuxian Meng +3 more
openaire +2 more sources
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 +4 more
wiley +1 more source
Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents
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 +3 more
wiley +1 more source
LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler +7 more
wiley +1 more source
Named Entity Recognition with Bidirectional LSTM-CNNs
Jason P.C. Chiu, Eric Nichols
doaj +1 more source
Entity Span Suffix Classification for Nested Chinese Named Entity Recognition
Named entity recognition (NER) is one of the fundamental tasks in building knowledge graphs. For some domain-specific corpora, the text descriptions exhibit limited standardization, and some entity structures have entity nesting.
Jianfeng Deng +3 more
doaj +1 more source
Named Entity Recognition for Mongolian Language [PDF]
This paper presents a pioneering work on building a Named Entity Recognition system for the Mongolian language, with an agglutinative morphology and a subject-object-verb word order. Our work explores the fittest feature set from a wide range of features and a method that refines machine learning approach using gazetteers with approximate string ...
Zoljargal Munkhjargal +3 more
openaire +1 more source
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source
TourismNER: A Tourism Named Entity Recognition method based on entity boundary joint prediction
Tourism named entity recognition is indispensable in tourism information extraction, and plays a crucial role in constructing tourism knowledge map and enhancing tourism knowledge quiz system.
Kai Gao +3 more
doaj +1 more source
A low‐cost, portable point‐of‐care platform for rapid Mpox detection using loop‐mediated isothermal amplification is reported. The device integrates fluorescence readout and mobile monitoring. A machine‐learning model analyzes temperature data and correlates thermal changes with DNA concentration, enabling sensitive and reliable molecular diagnosis in ...
Nazente Atceken +4 more
wiley +1 more source

