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On the use of aspect-based sentiment analysis of Twitter data to explore the experiences of African Americans during COVID-19

Meghna Chaudhary, Kristin Kosyluk, Sylvia Thomas, Tempestt Neal • Scientific Reports (2023)

Abstract According to data from the U.S. Center for Disease Control and Prevention, as of June 2020, a significant number of African Americans had been infected with the coronavirus disease, experiencing disproportionately higher death rate...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-023-37592-1

Machine learning in breast MRI

Beatriu Reig, Laura C. Heacock, Krzysztof J. Geras, Linda P. Moy • Journal of Magnetic Resonance Imaging (2019)

Machine-learning techniques have led to remarkable advances in data extraction and analysis of medical imaging. Applications of machine learning to breast MRI continue to expand rapidly as increasingly accurate 3D breast and lesion segmenta...

OPENALEX DOI: https://doi.org/10.1002/jmri.26852 PMC: 7085409

Proactive caching in cloud and D2D assisted multi-tier cellular networks

Ayaz Ahmad, Fawad Ahmad, Muhammad Suleman Khan, Adel Aldalbahi • PeerJ Computer Science (2026)

Proactive caching in multi-tier cellular networks (MTCNs) is an efficient technique for alleviating heavy data traffic on backhaul links, thereby reducing content latency and increasing the overall cache hit ratio (CHR) and user satisfactio...

DOAJ Open Access (DOAJ) DOI: 10.7717/peerj-cs.4004

A cascaded classification approach using transfer learning and feature engineering for improved breast cancer classification

Chokri Ferkous, Ouissal Fadel, Abderrahmane Kefali, Hayet-Farida Merouani • IJAIN (International Journal of Advances in Intelligent Informatics) (2026)

The primary objective of this study is to design a cascaded classification framework that integrates deep-learning representations with handcrafted and clinical features to enhance the reliability and accuracy of breast cancer detection in ...

DOAJ Open Access (DOAJ) DOI: 10.26555/ijain.v12i1.1670

Key factors and serial mediation analysis of anxiety and depression among university students: a cross-sectional study

Tan Jiang, Shijia Zhang, Shijia Zhang, Deyou Jiang • Frontiers in Psychiatry (2026)

BackgroundAnxiety and depressive symptoms are prevalent among university students; however, their risk factors are unlikely to operate in isolation. Instead, they may be organized in a multilevel structure that progressively approaches emot...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpsyt.2026.1809332

CViewer: a Java-based statistical framework for integration of shotgun metagenomics with other omics datasets

Orges Koci, Richard K. Russell, M. Guftar Shaikh, Christine Edwards et al. • Microbiome (2024)

Abstract Background Shotgun metagenomics for microbial community survey recovers enormous amount of information for microbial genomes that include their abundances, taxonomic, and phylogenetic information, as well as their genomic makeup, t...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40168-024-01834-9

MARKETING ACTIVITIES OF IT COMPANIES: INFORMATION AND ORGANISATIONAL CAPABILITIES FOR DIGITAL PRODUCT DEVELOPMENT

Kostiantyn Fuks • Green, Blue and Digital Economy Journal (2024)

The purpose of this article is to provide a comprehensive examination of the informational and organisational capabilities of marketing activities in the market for digital products and services. It highlights the importance of data analysi...

DOAJ Open Access (DOAJ) DOI: 10.30525/2661-5169/2024-1-4

Introduction to Machine Learning

Yves Kodratoff • CERN Document Server (European Organization for Nuclear Research) (1988)

1 Why Machine Learning and AI: The Contributions of AI to Learning Techniques 2 Theoretical Foundations for Machine Learning 3 Representation of Complex Knowledge by Clauses 4 Representation of Knowledge about Actions and the Addition of Ne...

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Human behavior analysis on political retweets using machine learning algorithms

Het Patel, Aditya Kansara, Boppuru Rudra Prathap, Kukatlapalli Pradeep Kumar • Measurement: Sensors (2023)

The exponential rise in the use of social media has resulted in a massive increase in the volume of unstructured text created. This content is presented through messages, conversations, postings, and blogs. Microblogging has become a popula...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.measen.2023.100768

Machine learning in cardiovascular medicine: are we there yet?

Khader Shameer, Kipp W. Johnson, Benjamin Scott Glicksberg, Joel T. Dudley et al. • Heart (2018)

Artificial intelligence (AI) broadly refers to analytical algorithms that iteratively learn from data, allowing computers to find hidden insights without being explicitly programmed where to look. These include a family of operations encomp...

OPENALEX DOI: https://doi.org/10.1136/heartjnl-2017-311198

Efficacy of ChatGPT in Cantonese Sentiment Analysis: Comparative Study

Ziru Fu, Yu Cheng Hsu, Christian S Chan, Chaak Ming Lau et al. • Journal of Medical Internet Research (2024)

BackgroundSentiment analysis is a significant yet difficult task in natural language processing. The linguistic peculiarities of Cantonese, including its high similarity with Standard Chinese, its grammatical and lexical uniqueness, and its...

DOAJ Open Access (DOAJ) DOI: 10.2196/51069

Machine learning in pain research

Jörn Lötsch, Alfred Ultsch • Pain (2017)

1. Introduction Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence.14 It has been accepted that pain is a complex phenomenon.2,32,72 Contemporary methods of compu...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1097/j.pain.0000000000001118 PMC: 5895117