Results 121 to 130 of about 157,658 (286)

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, Gerner Martin, Bergman Casey M   +2 more
doaj   +1 more source

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

Advanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan, Ankeer Abuduhebaier, Haojin Zhou, Jiaqi Wang   +3 more
wiley   +1 more source

Learning the Structure of Biomedical Relationships from Unstructured Text.

PLoS Computational Biology, 2015
The published biomedical research literature encompasses most of our understanding of how drugs interact with gene products to produce physiological responses (phenotypes).
Bethany Percha, Russ B Altman
doaj   +1 more source

A tool for the automatic and manual annotation of biomedical documents [PDF]

, 2008
The techniques developed within the field of Biomedical Text Mining (BioTM) have been mainly tested and evaluated over a set of known corpora built by a few researchers with a specific goal or to support scientific competitions.
Carneiro, S., Carreira, Rafael, Ferreira, E. C., Lourenço, Anália, Rocha, I., Rocha, Miguel   +5 more
core  

ChatCFD: A Large Language Model‐Driven Agent for End‐to‐End Computational Fluid Dynamics Automation with Structured Knowledge and Reasoning

Advanced Intelligent Discovery, EarlyView.
Chat computational fluid dynamics (CFD) introduces an large language model (LLM)‐driven agent that automates OpenFOAM simulations end‐to‐end, attaining 82.1% execution success and 68.12% physical fidelity across 315 benchmarks—far surpassing prior systems.
E Fan, Kang Hu, Zhuowen Wu, Jiangyang Ge, Jiawei Miao, Yuzhi Zhang, He Sun, Weizong Wang, Tianhan Zhang   +8 more
wiley   +1 more source

Accelerated variant curation from scientific literature using biomedical text mining. [PDF]

MicroPubl Biol, 2022
Mallick R, Arnaboldi V, Davis P, Diamantakis S, Zarowiecki M, Howe K.   +5 more
europepmc   +1 more source

Benchmarking biomedical text mining web servers at BioCreative V.5: the technical Interoperability and Performance of annotation Servers - TIPS track [PDF]

, 2017
The TIPS track consisted in a novel experimental task under the umbrella of the BioCreative text mining challenges with the aim to, for the first time ever, carry out a text mining challenge with particular focus on the continuous assessment of ...
Blanco-Míguez, Aitor, Fdez-Riverola, Florentino, Krallinger, Martin, Lourenço, Anália, Pérez-Pérez, Martin, Pérez-Rodríguez, Gael, Valencia, Alfonso   +6 more
core  

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

A Web Application for Biomedical Text Mining of Scientific Literature Associated with Coronavirus-Related Syndromes: Coronavirus Finder. [PDF]

Diagnostics (Basel), 2022
Armenta-Medina D, Brambila-Tapia AJL, Miranda-Jiménez S, Rodea-Montero ER.   +3 more
europepmc   +1 more source