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Different hybrid machine intelligence techniques for handling IoT‐based imbalanced data

Gaurav Mohindru, Koushik Mondal, Haider Banka • CAAI Transactions on Intelligence Technology (2021)

Abstract In the era of automatic task processing or designing complex algorithms, to analyse data, it is always pertinent to find real‐life solutions using cutting‐edge tools and techniques to generate insights into the data. The data‐drive...

DOAJ Open Access (DOAJ) DOI: 10.1049/cit2.12032

Natural Language Processing-Based Financial Time Series Forecasting: Utilizing Sentiment Analysis for Improved Stock Price Prediction

Albert Ntumba Nkongolo, Yae Olatoundji Gaba, Kafunda Katalay Pierre, Esther Matendo Mabela et al. • Journal of Innovation Information Technology and Application (2025)

This study explores the application of natural language processing (NLP) techniques in financial time series forecasting, specifically in predicting stock prices. Historical stock price data and textual data from financial news articles and...

DOAJ Open Access (DOAJ) DOI: 10.35970/jinita.v7i1.2290

Ensembles machine learning for short duration rainfall intensity forecasting

Susilowati, Aprizal, Dyah Indriana Kusumastuti • Discover Artificial Intelligence (2026)

Abstract This study introduces an ensemble machine learning (EML) framework to enhance short-duration rainfall-intensity prediction under limited-data conditions. By integrating multiple base learners within a stacking architecture, the pro...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44163-026-01772-5

Using 311 data to develop an algorithm to identify urban blight for public health improvement.

Jessica Athens, Setu Mehta, Sophie Wheelock, Nupur Chaudhury et al. • PLoS ONE (2020)

The growth of administrative data made available publicly, often in near-real time, offers new opportunities for monitoring conditions that impact community health. Urban blight-manifestations of adverse social processes in the urban enviro...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0235227

Detecting Fake News in Urdu Language Using Machine Learning, Deep Learning, and Large Language Model-Based Approaches

Muhammad Shoaib Farooq, Syed Muhammad Asadullah Gilani, Muhammad Faraz Manzoor, Momina Shaheen • Information (2025)

Fake news is false or misleading information that looks like real news and spreads through traditional and social media. It has a big impact on our social lives, especially in politics. In Pakistan, where Urdu is the main language, finding ...

DOAJ Open Access (DOAJ) DOI: 10.3390/info16070595

Development and External Validation of a Machine Learning Model for Automated Feedback Quality Assessment in Chinese Anesthesiology Residency Training

Yao L, Chen Y, Shen J, Zhang J et al. • Advances in Medical Education and Practice (2026)

Lifeng Yao, Yijun Chen, Jing Shen, Junge Zhang, Yiwei Zhang, Guojin Liang, Yiqin Ji Department of Anesthesiology, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, People’s Republic of ChinaCorrespondence: Yijun Chen, De...

DOAJ Open Access (DOAJ)

Fast Exploring Literature by Language Machine Learning for Perovskite Solar Cell Materials Design

Lei Zhang, Yiru Huang, Leiming Yan, Jinghao Ge et al. • Advanced Intelligent Systems (2024)

Making computers automatically extract latent scientific knowledge from literature is highly desired for future materials and chemical research in the artificial intelligence era. Herein, the natural language processing (NLP)‐based machine ...

DOAJ Open Access (DOAJ) DOI: 10.1002/aisy.202300678

A systematic literature review on spam content detection and classification

Sanaa Kaddoura, Ganesh Chandrasekaran, Daniela Elena Popescu, Jude Hemanth Duraisamy • PeerJ Computer Science (2022)

The presence of spam content in social media is tremendously increasing, and therefore the detection of spam has become vital. The spam contents increase as people extensively use social media, i.e., Facebook, Twitter, YouTube, and E-mail. ...

DOAJ Open Access (DOAJ) DOI: 10.7717/peerj-cs.830

Machine learning with persistent homology and chemical word embeddings improves prediction accuracy and interpretability in metal-organic frameworks

Aditi S. Krishnapriyan, Joseph Montoya, Maciej Haranczyk, Jens Hummelshøj et al. • Scientific Reports (2021)

Abstract Machine learning has emerged as a powerful approach in materials discovery. Its major challenge is selecting features that create interpretable representations of materials, useful across multiple prediction tasks. We introduce an ...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-021-88027-8

Diminished Auditory Responses during NREM Sleep Correlate with the Hierarchy of Language Processing.

Meytal Wilf, Michal Ramot, Edna Furman-Haran, Anat Arzi et al. • PLoS ONE (2016)

Natural sleep provides a powerful model system for studying the neuronal correlates of awareness and state changes in the human brain. To quantitatively map the nature of sleep-induced modulations in sensory responses we presented participa...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0157143

Cracking the code: AI’s role in mapping evidence syntheses to the United Nations sustainable development goals

Bianca Pilla, Jennifer Stone, Zoe Jordan • Archives of Public Health (2025)

Abstract Background Understanding the alignment and contributions of research to the United Nations Sustainable Development Goals (UN SDGs) is essential for guiding global progress toward these critical targets. Several SDG mapping approach...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13690-025-01784-0

Analysis and Classification of Word Co-Occurrence Networks From Alzheimer’s Patients and Controls

Tristan Millington, Saturnino Luz • Frontiers in Computer Science (2021)

In this paper we construct word co-occurrence networks from transcript data of controls and patients with potential Alzheimer’s disease using the ADReSS challenge dataset of spontaneous speech. We examine measures of the structure of these ...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcomp.2021.649508

Artificial intelligence-based masked face detection: A survey

Khalid M. Hosny, Nada AbdElFattah Ibrahim, Ehab R. Mohamed, Hanaa M. Hamza • Intelligent Systems with Applications (2024)

The COVID-19 virus is causing a global pandemic. The total number of new coronavirus cases worldwide by the end of November 2020 had already surpassed 60 million. The World Health Organization (WHO) has determined that wearing masks is a cr...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.iswa.2024.200391

An image based application in Matlab for automated modelling and morphological analysis of insect wings

Shahab Eshghi, Fatemeh Nabati, Shaghayegh Shafaghi, Vahid Nooraeefar et al. • Scientific Reports (2022)

Abstract Despite extensive research on the biomechanics of insect wings over the past years, direct mechanical measurements on sensitive wing specimens remain very challenging. This is especially true for examining delicate museum specimens...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-022-17859-9

Artificial Intelligence in Routine IVF Practice

Grzegorz Mrugacz, Aleksandra Mospinek, Małgorzata Jagielska, Dariusz Miszczak et al. • Biology (2025)

Background: Artificial Intelligence (AI) has emerged as a transformative tool in in vitro fertilization (IVF) as it has done in other sectors. In IVF, AI offers advancements in embryo selection, treatment personalization, and outcome predic...

DOAJ Open Access (DOAJ) DOI: 10.3390/biology15010042

Identification of camouflage military individuals with deep learning approaches DFAN and SINETV2

Ali Haider, Ghulam Muhammad, Talha Ahmed Khan, Kushsairy Kadir et al. • Scientific Reports (2025)

Abstract Camouflaged object detection particularly is considered as challenging and crucial because these objects are designed to either mimic their environment or be completely hidden within it. The goal of camouflage patterns utilization ...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-18886-y