Results 81 to 90 of about 90,813 (262)
Biomedical Text Mining for Disease Gene Discovery
EMBnet.journal, 2012 Motivation and Objectives Because of the amount of electronic literature now available, it is challenging for biologists to search biomedical corpuses for any kind of desired information beyond simple text retrieval. Several tools have been developed to make text mining easier for them. Some of these tools focus on extracting biomedical terms; such as
Sarah ElShal, Jesse Davis, Yves Moreau
openaire +2 more sources
Deploying and sharing U-Compare workflows as web services [PDF]
, 2013 BACKGROUND: U-Compare is a text mining platform that allows the construction, evaluation and comparison of text mining workflows. U-Compare contains a large library of components that are tuned to the biomedical domain.
Ananiadou, Sophia +4 more
core +3 more sources
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 +4 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali +5 more
wiley +1 more source
Europe PMC annotated full-text corpus for gene/proteins, diseases and organisms
Scientific Data, 2023 Named entity recognition (NER) is a widely used text-mining and natural language processing (NLP) subtask. In recent years, deep learning methods have superseded traditional dictionary- and rule-based NER approaches.
Xiao Yang +5 more
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.This study presents an automated system integrating a capillary force gripper and machine learning‐based object detection for sorting and placing submillimeter objects. The system achieved stable and simultaneous manipulation of four object types, with an average task time of 86.0 seconds and a positioning error of 157 ± 84 µm, highlighting its ...
Satoshi Ando +4 more
wiley +1 more source
eLife, 2017 Staff from the National Center for Biotechnology Information in the US describe recent improvements to the PubMed search engine and outline plans for the future, including a new experimental site called PubMed Labs.
Nicolas Fiorini +2 more
doaj +1 more source
Figure mining for biomedical research [PDF]
, 2009 Motivation: Figures from biomedical articles contain valuable information difficult to reach without specialized tools. Currently, there is no search engine that can retrieve specific figure types.
Iossifov, I., Rodriguez-Esteban, R.
core +1 more source
Artificial Intelligence for Bone: Theory, Methods, and Applications
Advanced Intelligent Discovery, EarlyView.Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan +3 more
wiley +1 more source
Deep Learning‐Assisted Coherent Raman Scattering Microscopy
Advanced Intelligent Discovery, EarlyView.The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source