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Explainable and reliable kidney CT image classification using self-supervised DeiT-Tiny transformer

Sai Sri Hemantha Konala, Srinivas Koppu • Frontiers in Medicine (2026)

IntroductionKidney-related disorders are one of the global health concerns that require timely detection to prevent severe health complications. The use of computed tomography (CT) images for accurate classification of kidney diseases is im...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmed.2026.1893419

Recurrent Neural Networks Based Online Behavioural Malware Detection Techniques for Cloud Infrastructure

Jeffrey C. Kimmel, Andrew D. Mcdole, Mahmoud Abdelsalam, Maanak Gupta et al. • IEEE Access (2021)

Several organizations are utilizing cloud technologies and resources to run a range of applications. These services help businesses save on hardware management, scalability and maintainability concerns of underlying infrastructure. Key clou...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2021.3077498

Deep Learning: A Critical Appraisal

Gary Marcus • arXiv (Cornell University) (2018)

Although deep learning has historical roots going back decades, neither the term "deep learning" nor the approach was popular just over five years ago, when the field was reignited by papers such as Krizhevsky, Sutskever and Hinton's now cl...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1801.00631

Machine Learning in Healthcare

Hafsa Habehh, Suril Gohel • Current Genomics (2021)

Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) technology have brought on substantial strides in predicting and identifying health emergencies, disease populations, and disease state and immune response, among...

OPENALEX Open Access DOI: https://doi.org/10.2174/1389202922666210705124359 PMC: 8822225

Interpretable machine learning

Parliamentary Office of Science and Technology, Lorna Christie (2020)

Machine learning (ML, a type of artificial intelligence) is increasingly being used to support decision making in a variety of applications including recruitment and clinical diagnoses. While ML has many advantages, there are concerns that ...

OPENALEX Open Access DOI: https://doi.org/10.58248/pn633

Interpretable Machine Learning

Valerie Chen, Jeffrey Li, Joon Sik Kim, Gregory Plumb et al. • Queue (2021)

The emergence of machine learning as a society-changing technology in the past decade has triggered concerns about people's inability to understand the reasoning of increasingly complex models. The field of IML (interpretable machine learni...

OPENALEX cc-by DOI: https://doi.org/10.1145/3511299

A machine learning based scheme for enhancing the detection of position falsification attacks in vehicular ad hoc networks

Eslam Abdelkreem, Sherif Hussein, Ashraf Tammam • Scientific Reports (2026)

Abstract Vehicular Ad Hoc Networks (VANETs) are wireless networks established between vehicles and their surrounding infrastructure, enabling the exchange of information. Consequently, many applications that can enhance passengers’ safety a...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-39867-9

A Prediction Model for Spot LNG Prices Based on Machine Learning Algorithms to Reduce Fluctuation Risks in Purchasing Prices

Sun-Feel Yang, So-Won Choi, Eul-Bum Lee • Energies (2023)

The ongoing Russia–Ukraine conflict has exacerbated the global crisis of natural gas supply, particularly in Europe. During the winter season, major importers of liquefied natural gas (LNG), such as South Korea and Japan, were directly affe...

DOAJ Open Access (DOAJ) DOI: 10.3390/en16114271

On Artificial Intelligence and Manipulation

Marcello Ienca • Topoi (2023)

Abstract The increasing diffusion of novel digital and online sociotechnical systems for arational behavioral influence based on Artificial Intelligence (AI), such as social media, microtargeting advertising, and personalized search algorit...

OPENALEX cc-by DOI: https://doi.org/10.1007/s11245-023-09940-3

Artificial intelligence in radiotherapy

Sarkar Siddique, James C. L. Chow • Reports of Practical Oncology & Radiotherapy (2020)

Artificial intelligence (AI) has already been implemented widely in the medical field in the recent years. This paper first reviews the background of AI and radiotherapy. Then it explores the basic concepts of different AI algorithms and ma...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.rpor.2020.03.015 PMC: 7321818

The Effects of Large Language Models on the Generation of Multiple-choice Questions in Medical Education: A Scoping Review

Baleegh Elsir Ahmed Mohammed, Tanzeel Elsir Ahmed Mohammed, Anthony Paul Breitbach • Sudan Journal of Medical Sciences (2026)

Background: Constructing high-quality multiple-choice questions (MCQs) is critical yet resource-intensive in medical education. Large language models (LLMs), such as ChatGPT, have become promising tools for generating MCQs in medical educat...

DOAJ Open Access (DOAJ) DOI: 10.18502/sjms.v21i2.19868

Artificial Intelligence, Discretion, and Bureaucracy

Justin B. Bullock • The American Review of Public Administration (2019)

This essay highlights the increasing use of artificial intelligence (AI) in governance and society and explores the relationship between AI, discretion, and bureaucracy. AI is an advanced information communication technology tool (ICT) that...

OPENALEX DOI: https://doi.org/10.1177/0275074019856123

Artificial intelligence in Internet of things

Ashish Kumar Ghosh, Debasrita Chakraborty, Anwesha Law • CAAI Transactions on Intelligence Technology (2018)

Functioning of the Internet is persistently transforming from the Internet of computers (IoC) to the ‘Internet of things (IoT)’. Furthermore, massively interconnected systems, also known as cyber‐physical systems (CPSs), are emerging from t...

OPENALEX cc-by-nd DOI: https://doi.org/10.1049/trit.2018.1008