This survey reviews deep learning architectures for transaction and financial fraud detection published strictly after 2024, using the Multi-task CNN Behavioural Embedding Model (MTCNN) proposed by Qu et al.[1] in 2024 as a conceptual anchor rather than as one of the post-2024 studies under review. MTCNN's core ideas —...
Dr. S. Jeyalaksshmi2 Ms. S. Jayanthi1*· World Journal of Pharmacy an...· 0 citations
This survey reviews deep learning architectures for transaction and financial fraud detection published strictly after 2024, using the Multi-task CNN Behavioural Embedding Model (MTCNN) proposed by Qu et al.[1] in 2024 as a conceptual anchor rather than as one of the post-2024 studies under review. MTCNN's core ideas —...
Dr. S. Jeyalaksshmi2 Ms. S. Jayanthi1*· World Journal of Pharmacy an...· 0 citations
uptake of generative AI may have influenced health administration, workflow, electronic charting, disease interrogation for information and learning, utility of AI or the notion of autonomous microsurgery is still somewhat remote. 4 Is it thus time to revisit the role of machine advances with digital innovation, AI and...
Sanju Lama, Hani J. Marcus, Garnette R. Sutherland· Frontiers in Robotics and AI· 0 citations
Generative Systems Theory is a foundational inquiry and metaphysics concerning systems theory and complexity science. It focuses on how concepts regarded as basic elements—such as nodes, relations, compatibility, attractors, information, and so on—come into being in the first place, and on what grounds they can be said...
Lucas Li· Zenodo (CERN European Organi...· 0 citations
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A structured view of current advances, persistent gaps, and future directions in AI-enabled pharmaceutical innovation is offered, showing growing convergence between AI and precision therapeutics, but real-world application demands robust validation, collaboration, explainable AI, and global standards.
M. Fareed, S. Shityakov· Quantum Machine Intelligence· 0 citations
Two AI systems can reach the same scientific conclusion for different reasons: one may generate the candidate sooner, another may check it more cheaply, and a third may obtain decisive evidence earlier. An end-to-end score records success while hiding which interface made success possible, which resource an interventio...
Alex Li· Zenodo (CERN European Organi...· 0 citations
This article presents a narrative review of Explainability and Interpretability of Black-Box Models in the context of Artificial Intelligence. The literature on this topic has expanded substantially over recent decades, yet it remains fragmented across subfields, methods, and national research traditions. Drawing on an...
Zen Revista, 10 IA· Zenodo (CERN European Organi...· 0 citations
The increasing biological complexity and heterogeneity of cancer have driven a shift in oncology drug discovery from single-target approaches toward system-level strategies capable of capturing multilayered disease regulation. Multi-omics technologies, including genomics, transcriptomics, proteomics, metabolomics, epig...
Deval Koshti, N. Khandale, Jignesh Shah et al.· AAPS PharmSciTech· 0 citations
A robust and explainable cybersecurity framework for IoV in IIoT Cyber-Physical Systems (CPS) is proposed, in which implementation and validation using the RT-IoT2022 (Real-Time Internet of Things) dataset is performed.
T. Zhukabayeva, Zulfiqar Ahmad, N. Karabayev et al.· Discover Artificial Intellig...· 0 citations
This work distil ten recurring gaps into an impact-feasibility matrix and proposes EPA-CarbonNet, a six-layer architecture that fuses market series with policy text by cross-attention and calibrated intervals alongside policy-attributed explanations.
Summaiya Unnisa Begum, Mohammed N. Ullah, Mohammed Abdul Ghani Khan· 0 citations
A self-referential retrosynthesis framework for explainable AI provenance forensics under a fixed-generator setting that leverages a jointly optimized encoder-decoder pair to implement a self-embedding mechanism that enables round-trip consistency verification.
Yi-Jie Lin, Ching-Chun Chang, Isao Echizen et al.· 0 citations
This paper introduces contrastive explanations for Quantitative Bipolar Argumentation Frameworks (QBAFs), one such formalism, and introduces a general form of contrastive attribution functions (CAFs) and establishes a set of general properties they should satisfy.
Xiang Yin, Nico Potyka, Antonio Rago et al.· 0 citations
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 Building trustworthy AI: The role of AI harnesses, intent contracts and evals appeared first on GPT-Lab.
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
MIT News · Artificial Intelligence· news.mit.eduOct 13, 2026
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.
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