Results 81 to 90 of about 9,285,371 (201)

Detecting Opioid Misuse on Social Media via Named Entity Recognition (NER) With Deep Learning

Expert Systems, Volume 43, Issue 8, August 2026.
ABSTRACT The opioid overdose epidemic constitutes a critical public health crisis, necessitating advanced surveillance tools to enable timely intervention. Social media platforms provide a real‐time source of information on drug‐related behaviours. However, extracting structured knowledge from their informal, slang‐heavy and fragmented text presents ...
Muhammad Ahmad, Rita Orji, Fida Ullah, Ildar Batyrshin, Grigori Sidorov   +4 more
wiley   +1 more source

Deep recurrent conditional random field network for protein secondary prediction [PDF]

, 2017
Deep learning has become the state-of-the-art method for predicting protein secondary structure from only its amino acid residues and sequence profile.
Johansen, Alexander Rosenberg, Sønderby, Casper Kaae, Winther, Ole, Ole Winther, Alexander Rosenberg Johansen, Casper Kaae Sønderby, Sønderby, Søren Kaae, Søren Kaae Sønderby   +7 more
core   +1 more source

Chinese-Named Entity Recognition From Adverse Drug Event Records: Radical Embedding-Combined Dynamic Embedding–Based BERT in a Bidirectional Long Short-term Conditional Random Field (Bi-LSTM-CRF) Model

JMIR Medical Informatics, 2020
Background With the increasing variety of drugs, the incidence of adverse drug events (ADEs) is increasing year by year. Massive numbers of ADEs are recorded in electronic medical records and adverse drug reaction (ADR) reports, which are important sources of potential ADR information. Meanwhile, it is essential
Hong Wu, Jiatong Ji, Haimei Tian, Yao Chen, Weihong Ge, Haixia Zhang, Feng Yu, Jianjun Zou, Mitsuhiro Nakamura, Jun Liao   +9 more
openaire   +3 more sources

An Attention‐Assisted Machine Learning System for Deep Microorganism Image Classification

Advanced Intelligent Systems, Volume 8, Issue 7, July 2026.
An attention‐assisted DenseNet201 framework was developed for the classification of eight microorganism classes from microscopic images. The proposed model improved classification performance and achieved an accuracy of 87.38%. Advances in microbiology and environmental health fundamentally depend on precise and timely microorganism identification ...
Yujie Li, Ailing Gao, Guoxu Liu, Chunlei Chen, Yonghui Zhang, Sunkyoung Kang, M. Khosravi   +6 more
wiley   +1 more source

Cyber security named entity recognition based on deep active learning

四川大学学报. 自然科学版, 2019
To solve the problem of low accuracy in general cyber security named entity recognition (NER) model，a deep active learning method is proposed for NER in general cyber security field, which is based on character feature，BiLSTM and conditional random ...
Peng Jia-yi, Fang Yong, Huang Cheng, Liu Liang, Jiang Zheng-wei   +4 more
doaj  

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, Volume 8, Issue 7, July 2026.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

A practical guide to the implementation of AI in orthopaedic research‐Part 4: Prerequisites for a successful orthopedics AI‐driven project in terms of interdisciplinary collaboration, data management, ethical approval and technology

Journal of Experimental Orthopaedics, Volume 13, Issue 3, July 2026.
Abstract Translating artificial intelligence (AI) research in orthopedics from proof‐of‐concept studies into production‐grade clinical systems requires the systematic satisfaction of four prerequisite domains: interdisciplinary team architecture, technical data management, ethical and regulatory governance and production‐grade technology and deployment
Umile Giuseppe Longo, Mario Merone, Emiliano Schena, Benedetta Bandini, Guido Nicodemi, Bálint Zsidai, Ann‐Sophie Hilkert, Eric Hamrin Senorski, Alberto Grassi, Christophe Ley, Elmar Herbst, Michael T. Hirschmann, Sebastian Kopf, Romain Seil, Thomas Tischer, Robert Feldt, Kristian Samuelsson, Felix C. Oettl   +17 more
wiley   +1 more source

CRF combined with ShapeBM shape priors for image labeling

Dianxin kexue, 2017
Conditional random field (CRF) is a powerful model for image labeling,it is particularly well-suited to model local interactions among adjacent regions (e.g.superpixels).However,CRF doesn't consider the global constraint of objects.The overall shape of ...
Hao WANG, Lijun GUO, Yadong WANG, Rong ZHANG   +3 more
doaj   +2 more sources

Explain sentiments using Conditional Random Field and a Huge Lexical Network [PDF]

, 2020
In this paper, we focus on a particular task which consists in explaining the source and the target of sentiments expressed in social networks. We propose a method for French, which overcomes a fine syntactic parsing and successfully integrate the ...
Tapi Nzali, Sandra Bringay, Joël Maïzi, Pierre Pompidor, Mike Donald, Christian Lavergne   +5 more
core  

An abnormal traffic detection method for chain information management system network based on convolutional neural network

Frontiers in Physics
Chain information management system is widely used, providing convenience for the operation and management of enterprises. However, the problem of abnormal network traffic becomes increasingly prominent currently.
Chao Liu, Chunxiang Liu, Changrong Liu
doaj   +1 more source