Results 91 to 100 of about 43,712,030 (248)
Text Mining on Big and Complex Biomedical Literature
, 2018 Driven by the rapidly advancing techniques and increasing interests in biology and medicine, about 2,000 to 4,000 references are added daily to MEDLINE, the US national biomedical bibliographic database.
Di Wu, Boya Xie, Qin Ding
core +1 more source
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 +4 more
wiley +1 more source
LINNAEUS: A species name identification system for biomedical literature
BMC Bioinformatics, 2010 Background The task of recognizing and identifying species names in biomedical literature has recently been regarded as critical for a number of applications in text and data mining, including gene name recognition, species-specific document retrieval ...
Nenadic Goran +2 more
doaj +1 more source
The @Note biomedical text mining workbench [PDF]
, 2019 [Excerpt] Biomedical Text Mining. i.e., the field that deals with the automatic: retrieval and processing of biomedical literature, is perhaps one of today's most promising research fields.
Ferreira, Eugénio C. +8 more
core
Semi-supervised prediction of protein interaction sentences exploiting semantically encoded metrics [PDF]
, 2009 Protein-protein interaction (PPI) identification is an integral component of many biomedical research and database curation tools. Automation of this task through classification is one of the key goals of text mining (TM).
Polajnar, T. +3 more
core +1 more source
Advanced Intelligent Discovery, EarlyView.An ultra‐fast small‐sample AI consensus pipeline combines co‐folding and docking to target structure‐lacking p53 monomers. Its optimal mini‐protein binder shows robust interfacial affinity and promising druggability, supplying unprecedented antitumor p53 templates.
Ningyao Li +9 more
wiley +1 more source
A Generative AI Framework to Predict Cardiomyocyte Contraction Function From Single Static Images
Advanced Intelligent Discovery, EarlyView.A single static hiPSC‐cardiomyocyte image is fed into a U‐Net‐GAN framework, which directly predicts a pixel‐resolved contraction heatmap without time‐lapse imaging. StyleGAN2‐generated synthetic cell–heatmap pairs augment training, improving prediction fidelity (SSIM = 0.84).
Andrew Kowalczewski +5 more
wiley +1 more source
A syndrome differentiation model of TCM based on multi-label deep forest using biomedical text mining. [PDF]
Front Genet, 2023 Gong L, Jiang J, Chen S, Qi M.
europepmc +1 more source
Ontology of core data mining entities [PDF]
, 2014 In this article, we present OntoDM-core, an ontology of core data mining entities. OntoDM-core defines themost essential datamining entities in a three-layered ontological structure comprising of a specification, an implementation and an application ...
Dzeroski, S, Soldatova, L, Panov, P
core +1 more source
Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers
Advanced Intelligent Systems, EarlyView.Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica +38 more
wiley +1 more source