Abstract Alzheimer's disease (AD) often remains undetected until memory loss and cognitive decline become clinically apparent, at which point substantial neurological damage has already occurred. Early and reliable diagnosis therefore, remains one of the most pressing challenges in dementia care. This study presents a...
Dr. K R Shylaja, Chaitra Shree K· Journal of Zhejiang Universi...· 0 citations
The study demonstrates that AI integration in pesantren is an epistemically and institutionally negotiated process in which technological affordances are selectively incorporated through established structures of knowledge, authority, and ethical formation.
M. Qulyubi, S. Bahri, Hayaturrohman Hayaturrohman et al.· Munaddhomah: Jurnal Manajeme...· 0 citations
This narrative review synthesises clinically relevant evidence on AI-enabled early diagnostics, precision therapeutic pathways, and the principal structural barriers to responsible adoption to find AI is best positioned as an augmentation of clinical judgement rather than a replacement for it.
M. Ahmad, Muhammad Ibrahim Ahmed, Ahmad Sajjad Ashraf· Journal of Advances in Medic...· 0 citations
An integrated model synthesizing the technology acceptance model (TAM) and social exchange theory is developed and tested to explain the context-dependent drivers of sustainable knowledge sharing in the AI era, demonstrating the context-dependent role of core constructs like “perceived cost.”
Fenix Xin Feng, Jiang-Fei Chen, Yi-Qiao Liu et al.· VINE Journal of Information...· 0 citations
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The findings demonstrated that the accuracy and completeness of chatbot-generated information significantly influence perceived usefulness, while information format influences perceived ease of use, while information format influences perceived ease of use.
Ghada ElSayad, Nor Hasliza Md. Saad· Journal of Applied Research...· 0 citations
The model is based on the principles of interpretivist epistemology, construct-validity theory, and human-in-the-loop (HITL) AI principles and redefines AI as an enhancement tool and not an autonomous interpreter, which sets a conceptual background to future empirical verification of AI systems run by humans.
E. Oladunmoye, M. A. Adewusi· WAMDEVIN International Journ...· 0 citations
Machine Learning techniques were the most commonly applied AI methods in pharmacovigilance, followed by natural language processing, deep learning, neural networks, and symbolic and explainable AI.
Gita Kusnadi, Grace Wangge, Ari A. Perdana· International Journal of Pub...· 0 citations
Artificial intelligence (AI) systems do more than alter choice architecture: they select, explain, personalise and repeatedly reinforce options. This conceptual paper develops a cognitive–behavioural pathway model explaining when AI-assisted decision-making may narrow the intention–behaviour gap in environmentally sust...
This study investigates the transferability of adversarial attacks across XGBoost and LightGBM models in IDS and uses Explainable AI (XAI) techniques to identify features that influence model decisions and shows that feature-importance patterns can be used to examine model vulnerability under adversarial perturbations.
Abdlelah Abdlatef, Marwa D. Abdulkareem, Duygu Çakır· International Journal of Inf...· 1 citation
The HPA framework is introduced, a capability-centred evaluative framework that integrates perspectives from cognitive ergonomics, work design, and human-centred AI through four dimensions: Optimisation, Retention, Expansion, and Engagement.
Lisa Diamond, M. Oppermann· Proceedings of the 2026 Euro...· 0 citations
The findings suggest that trustworthy AI integration requires addressing pre-existing structural failures before introducing algorithmic decision support, and offer design recommendations for AI-supported appraisal systems, with implications for HCI research and organizational practice.
Andreas Harnindito, Akshat Sawarni· Proceedings of the 2026 Euro...· 0 citations
EASCI (Experience, Articulation, Structuring, Consolidation, Innovation), a five-stage framework that separates cognitive tasks and restricts AI involvement, is introduced, to mitigate working-memory overload.
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
AI is moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post AI Has Grown Up. Have We? appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
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