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Artificial intelligence and machine learning

Niklas Kühl, Max Schemmer, Marc Goutier, Gerhard Satzger • Electronic Markets (2022)

Abstract Within the last decade, the application of “artificial intelligence” and “machine learning” has become popular across multiple disciplines, especially in information systems. The two terms are still used inconsistently in academia ...

OPENALEX cc-by DOI: https://doi.org/10.1007/s12525-022-00598-0

Artificial Intelligence, Automation and Work

Daron Acemoğlu, Pascual Restrepo • National Bureau of Economic Research (2018)

We summarize a framework for the study of the implications of automation and AI on the demand for labor, wages, and employment.Our task-based framework emphasizes the displacement effect that automation creates as machines and AI replace la...

OPENALEX Open Access DOI: https://doi.org/10.3386/w24196

An automated deep learning framework for brain tumor classification using MRI imagery

Muhammad Aamir, Ziaur Rahman, Uzair Aslam Bhatti, Waheed Ahmed Abro et al. • Scientific Reports (2025)

Abstract The precise and timely diagnosis of brain tumors is essential for accelerating patient recovery and preserving lives. Brain tumors exhibit a variety of sizes, shapes, and visual characteristics, requiring individualized treatment s...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-02209-2

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

A physics-informed spatiotemporal graph neural network for photovoltaic power forecasting and micro-anomaly localization

Mortatha Faleh Majed, Ali S. Abed Al Sailawi, Hassan A. Hameed Al-Hamzawi • Next Energy (2026)

Accurate power forecasting and precise fault diagnosis are critical for the reliable operation of large-scale photovoltaic systems. However, existing data-driven models often fail to capture complex spatiotemporal dependencies and lack phys...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.nxener.2026.101127

Creativity and Artificial Intelligence

Francisco C. Pereira (2007)

Creativity and Artificial Intelligence: A Conceptual Blending Approach takes readers into a computationally plausible model of creativity. Inspired by a thorough analysis of work on creativity from the areas of philosophy, psychology, cogni...

OPENALEX DOI: https://doi.org/10.1515/9783110198560

Artificial Intelligence with Uncertainty

Deyi Li, Yi Du • CRC Press eBooks (2017)

This book develops a framework that shows how uncertainty in Artificial Intelligence (AI) expands and generalizes traditional AI. It explores the uncertainties of knowledge and intelligence. The authors focus on the importance of natural la...

OPENALEX DOI: https://doi.org/10.1201/9781315366951

Current Signature-Based Bearing Fault Severity Classification Using a Robust Multilevel Cascaded Framework

Korawege N. C. Jayasena, Battur Batkhishig, Babak Nahid-Mobarakeh, Ali Emadi • IEEE Access (2025)

Bearing faults are a critical concern in electrical machines, particularly permanent magnet synchronous motors (PMSMs), commonly used in electric vehicles. Early and accurate classification of bearing fault severity is essential for predict...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3589750

A review of optimization strategies for deep and machine learning in diabetic macular edema

A. M. Mutawa, Khalid Sabti, Bibin Shalini Sundaram Thankaleela, Seemant Raizada • Frontiers in Artificial Intelligence (2026)

Diabetic macular edema (DME) is a primary contributor to visual impairment in diabetic patients, necessitating precise and prompt analysis for optimal treatment. Recent breakthroughs in deep learning (DL) and machine learning (ML) have yiel...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2026.1684752

An Instructional Optimization Method Based on Bidirectional Transformer and Reinforcement Learning

Ran Zhang, Xiaoping Wu, Xude Zhang, Li Xu • IEEE Access (2025)

With the rapid development of information technology, personalized education has become a key direction for improving the quality of online learning and optimizing individualized learning paths. However, accurately recommending appropriate ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3576878

Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas

Anirban Chaudhuri, Graham Pash, David A. Hormuth, David A. Hormuth et al. • Frontiers in Artificial Intelligence (2023)

We develop a methodology to create data-driven predictive digital twins for optimal risk-aware clinical decision-making. We illustrate the methodology as an enabler for an anticipatory personalized treatment that accounts for uncertainties ...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2023.1222612

How artificial intelligence will change the future of marketing

Thomas H. Davenport, Abhijit Guha, Dhruv Grewal, Timna Breßgott • Journal of the Academy of Marketing Science (2019)

Abstract In the future, artificial intelligence (AI) is likely to substantially change both marketing strategies and customer behaviors. Building from not only extant research but also extensive interactions with practice, the authors propo...

OPENALEX cc-by DOI: https://doi.org/10.1007/s11747-019-00696-0

Designing novel linagliptin analogs through combined generative artificial intelligence, molecular docking, molecular dynamics simulation, and binding energy estimation for targeting fibroblast activation protein

Mingsong Shi, Mingsong Shi, Zhi Yang, Yuhan Yang et al. • Frontiers in Chemistry (2026)

Fibroblast activation protein (FAP) is a highly specific biomarker overexpressed in cancer-associated fibroblasts, making it a promising diagnostic target. Developing novel high-affinity molecular probes for FAP-targeted diagnostics remains...

DOAJ Open Access (DOAJ) DOI: 10.3389/fchem.2026.1848970

التحديات التي تثيرها الأسلحة ذاتية التشغيل كأحد تقنيات الذكاء الاصطناعي

هاني محمد خليل إبراهيم العزازي • Al-Maǧallah Al-Qānūniyyaẗ (2024)

صاحب التطور في تكنولوجيا الذكاء الاصطناعي تطوراً مماثلاً في أساليب ووسائل القتال, فظهرت أسلحة جديدة قادرة في ذاتها على تحديد أهدافها والاشتباك معها دون حاجة إلى تدخل بشري, ولذلك أطلق عليها "نظم الأسلحة ذاتية التشغيل" Autonomous Weapons Syst...

DOAJ Open Access (DOAJ) DOI: 10.21608/jlaw.2024.354448