Results 91 to 100 of about 90,813 (262)

Convolutional Neural Networks for Toxic Comment Classification

, 2018
Flood of information is produced in a daily basis through the global Internet usage arising from the on-line interactive communications among users. While this situation contributes significantly to the quality of human life, unfortunately it involves ...
Aggarwal Charu C, Bottou LÃl'on, dos Santos Cicero, Drakopoulos G., Gal Yarin, Lai Siwei, Mikolov Tomas, van der Maaten Laurens   +7 more
core   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

What the papers say: Text mining for genomics and systems biology

Human Genomics, 2010
Keeping up with the rapidly growing literature has become virtually impossible for most scientists. This can have dire consequences. First, we may waste research time and resources on reinventing the wheel simply because we can no longer maintain a ...
Harmston Nathan, Filsell Wendy, Stumpf Michael PH   +2 more
doaj   +1 more source

Advancing Chinese biomedical text mining with community challenges

Journal of Biomedical Informatics
Objective: This study aims to review the recent advances in community challenges for biomedical text mining in China. Methods: We collected information of evaluation tasks released in community challenges of biomedical text mining, including task description, dataset description, data source, task type and related links.
Hui Zong, Rongrong Wu, Jiaxue Cha, Weizhe Feng, Erman Wu, Jiakun Li, Aibin Shao, Liang Tao, Zuofeng Li, Buzhou Tang, Bairong Shen   +10 more
openaire   +3 more sources

Collective Classification of Textual Documents by Guided Self-Organization in T-Cell Cross-Regulation Dynamics

, 2011
We present and study an agent-based model of T-Cell cross-regulation in the adaptive immune system, which we apply to binary classification. Our method expands an existing analytical model of T-cell cross-regulation (Carneiro et al. in Immunol Rev 216(1):
Abi-Haidar, Alaa, Rocha, Luis M.
core   +1 more source

Accelerating Primary Screening of USP8 Inhibitors from Drug Repurposing Databases with Tree‐Based Machine Learning

Advanced Intelligent Discovery, EarlyView.
This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng, Sharon Ai Er Lam, Wei Chun Lim, Hannah Hui Min Toh, Shi Jun Ang   +4 more
wiley   +1 more source

Concept annotation in the CRAFT corpus

BMC Bioinformatics, 2012
Background Manually annotated corpora are critical for the training and evaluation of automated methods to identify concepts in biomedical text. Results This paper presents the concept annotations of the Colorado Richly Annotated Full-Text (CRAFT) Corpus,
Bada Michael, Eckert Miriam, Evans Donald, Garcia Kristin, Shipley Krista, Sitnikov Dmitry, Baumgartner William A, Cohen K, Verspoor Karin, Blake Judith A, Hunter Lawrence E   +10 more
doaj   +1 more source

Machine Learning‐Enhanced Random Matrix Theory Design for Human Immunodeficiency Virus Vaccine Development

Advanced Intelligent Discovery, EarlyView.
This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah, Muhammad Zulqarnain Zeb, Muhammad Husnain Zeb, Babar Shabbir   +3 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, Gerner Martin, Bergman Casey M   +2 more
doaj   +1 more source

Implementing a Portable Clinical NLP System with a Common Data Model - a Lisp Perspective

, 2018
This paper presents a Lisp architecture for a portable NLP system, termed LAPNLP, for processing clinical notes. LAPNLP integrates multiple standard, customized and in-house developed NLP tools.
Luo, Yuan, Szolovits, Peter
core   +1 more source