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Research on Personalized Recommendation Algorithm Integrating Cross-Grained Sentiment and Rating Interaction Features

Bing Li, Jiangtao Dong, Xile Wang, Yuqi Hou et al. • IEEE Access (2025)

To investigate the impact of cross-grained sentiments on user feature representation and address the issue of data sparsity, this paper proposes a Personalized Recommendation Algorithm Integrating Cross-Grained Sentiment and Rating Interact...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3530431

Artificial intelligence in clinical medicine: a state-of-the-art overview of systematic reviews with methodological recommendations for improved reporting

Giovanni Morone, Giovanni Morone, Luigi De Angelis, Luigi De Angelis et al. • Frontiers in Digital Health (2025)

Medicine has become increasingly receptive to the use of artificial intelligence (AI). This overview of systematic reviews (SRs) aims to categorise current evidence about it and identify the current methodological state of the art in the fi...

DOAJ Open Access (DOAJ) DOI: 10.3389/fdgth.2025.1550731

Machine Learning and Natural Language Processing in Mental Health: Systematic Review

Aziliz Le Glaz, Yannis Haralambous, Deok-Hee Kim-Dufor, Philippe Lenca et al. • Journal of Medical Internet Research (2020)

BACKGROUND: Machine learning systems are part of the field of artificial intelligence that automatically learn models from data to make better decisions. Natural language processing (NLP), by using corpora and learning approaches, provides ...

OPENALEX cc-by DOI: https://doi.org/10.2196/15708 PMC: 8132982

Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review

Seyedmostafa Sheikhalishahi, Riccardo Miotto, Joel T. Dudley, Alberto Lavelli et al. • JMIR Medical Informatics (2019)

BACKGROUND: Novel approaches that complement and go beyond evidence-based medicine are required in the domain of chronic diseases, given the growing incidence of such conditions on the worldwide population. A promising avenue is the seconda...

OPENALEX cc-by DOI: https://doi.org/10.2196/12239 PMC: 6528438

Natural language processing in Alzheimer's disease research: Systematic review of methods, data, and efficacy

Arezo Shakeri, Mina Farmanbar • Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring (2025)

Abstract INTRODUCTION Alzheimer's disease (AD) prevalence is increasing, with no current cure. Natural language processing (NLP) offers the potential for non‐invasive diagnostics, social burden assessment, and research advancements in AD. M...

DOAJ Open Access (DOAJ) DOI: 10.1002/dad2.70082

Methods for Analyzing the Contents of Social Media for Health Care: Scoping Review

Jiaqi Fu, Chaixiu Li, Chunlan Zhou, Wenji Li et al. • Journal of Medical Internet Research (2023)

BackgroundGiven the rapid development of social media, effective extraction and analysis of the contents of social media for health care have attracted widespread attention from health care providers. As far as we know, most of the reviews ...

DOAJ Open Access (DOAJ) DOI: 10.2196/43349

Repurposing a commercial artificial intelligence vision platform for automated surgical instrument identification: a proof-of-concept study

Simon Stoerzer, Klinto Xhemo, Felix Gronau, Linda Feldbruegge et al. • Patient Safety in Surgery (2026)

Abstract Background Retained surgical items are classified as never events but continue to occur, and the count meant to prevent them is often recorded as correct even when an item is retained. Computer vision could provide an independent c...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13037-026-00512-z

AI and Chatbot-Supported Interventions for Physical Activity and Obesity-Related Lifestyle Behaviors: Scoping Review With Attention to Family Involvement

Qianxia Jiang, Xiayu Summer Chen, Dev Patel, Keith Brazendale et al. • JMIR Pediatrics and Parenting (2026)

Abstract BackgroundAI-enabled chatbots and related conversational systems can facilitate human–computer interaction through natural language, personalization, and automated support. In pediatric health promotion, these tools hav...

DOAJ Open Access (DOAJ) DOI: 10.2196/98889

Deep-learning–based non-contrast CT for detecting acute ischemic stroke: a systematic review and HSROC meta-analysis of patient-level diagnostic accuracy

Kalab Yigermal Gete, Asnakew Achaw Ayele • BMC Neurology (2025)

Abstract Background Non-contrast CT (NCCT) is first-line imaging for suspected acute ischemic stroke (AIS) but has limited early sensitivity; deep learning (DL) may improve patient-level detection. Objectives To estimate the diagnostic accu...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12883-025-04528-3

A Machine Learning-Oriented Survey on Tiny Machine Learning

Luigi Capogrosso, Federico Cunico, Dong Seon Cheng, Franco Fummi et al. • IEEE Access (2024)

The emergence of Tiny Machine Learning (TinyML) has positively revolutionized the field of Artificial Intelligence by promoting the joint design of resource-constrained IoT hardware devices and their learning-based software architectures. T...

OPENALEX cc-by DOI: https://doi.org/10.1109/access.2024.3365349

Real time identification of phishing attacks through machine learning enhanced browser extensions

Monika Dandotiya, Nikhil Kumar Goyal, Ajay Khunteta, Babita Tiwari • Scientific Reports (2026)

Abstract Phishing attack continues to rank among the deadliest online threats. They create phony websites in an attempt to obtain personal data. This study offers a framework for a browser extension that uses machine learning to examine URL...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-35655-7

Machine Learning in Action

Peter de B. Harrington (2012)

SummaryMachine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to bui...

OPENALEX

Anti-corruption laws as a pillar of national security protection: wartime peculiarities

Tetiana Madryha, Olena Berezovska-Chmil, Yuliia Kobets, Valerii Bortnikov et al. • Ius Humani (2025)

The analysis focuses on how anti-corruption rules ensure both national security and support it during times of war when corruption endangers stability. Our study checks if existing anti-corruption rules and institution systems help protect ...

DOAJ Open Access (DOAJ) DOI: 10.31207/ih.v14i1.415

Development and Validation of Student Enablers and Barriers in Online Learning Scale: A Confirmatory Factor Analysis Approach

Johar Amir, Wirawan Setialaksana, Ambo Dalle • ELT Worldwide: Journal of English Language Teaching (2024)

The evolution of technology has reshaped the educational landscape, with online learning emerging as a prominent and accessible alternative. Online learning offers broader access to education, allowing individuals to pursue learning opportu...

DOAJ Open Access (DOAJ) DOI: 10.26858/eltww.v11i2.66999

Artificial Intelligence-Driven Salivary Biomarkers for Detection and Risk Stratification of Oral Potentially Malignant Disorders and OSCC: A Protocol for a Systematic Review

Shazia Fathima J.H, Mohammed Sibgatullah, Mohmed Isaqali Karobari • International Journal of Qualitative Methods (2026)

Objective This systematic review protocol aims to synthesize evidence on artificial intelligence-driven analysis of salivary biomarkers for the detection, risk stratification and differentiation of OPMDs and OSCC, with particular attention ...

DOAJ Open Access (DOAJ) DOI: 10.1177/16094069261504893

Validity and reliability of the Chinese translation of the attitude scale towards the use of artificial intelligence technologies in nursing (ASUAITIN)- a cross-sectional study

Rong Hu, Yan-fei Ma, Chun-yan Wang, Xiao-ya Li et al. • BMC Nursing (2025)

Abstract Aim This study aimed to test the psychometric properties of the Attitudes Toward Artificial Intelligence in Nursing Scale (ASUAITIN) in Chinese culture. Methods A convenience sampling method was employed to recruit 499 clinical nur...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12912-025-03322-3

The Use of Artificial Intelligence Tools in Assessing Content Validity: A Comparative Study with Human Experts

Hatice Gürdil, Hatice Özlem Anadol, Yeşim Beril Soğuksu • Ankara Üniversitesi Eğitim Bilimleri Fakültesi Dergisi (2026)

This study investigated whether artificial intelligence (AI) systems could evaluate the content validity of B1-level English reading comprehension items in a manner comparable to human experts. A 25-item multiple-choice test was developed a...

DOAJ Open Access (DOAJ) DOI: 10.30964/auebfd.1807153