Metal organic frameworks (MOFs) have emerged as promising electrode materials for supercapacitor (SC) due to their high surface areas, tunable porosity, and redox active sites. However, the vast chemical space of MOFs leads to millions of possible structures, makes experimental trial and error discovery inefficient. Th...
Achal Siddharth Fulmali, H. Panda· Journal of Materials Science...· 0 citations
To improve integration, stakeholders should begin any new POCUS AI development project by first examining the different domains where POCUS AI applications are most needed, including education, clinical practice, workflow, research, and administration.
Robinson M. Ferre, Rachel B. Liu, HF Samuel Lam et al.· Journal of the American Coll...· 0 citations
This survey explores recent innovations in IoT-based Water Quality Monitoring Systems (IoT-WQMS) integrated with Machine Learning (ML) and Deep Learning (DL) to enable real-time, automated water quality assessment.
Kumar S. Ashok, Radhakrishnan C. V.· International Journal of Sci...· 0 citations
The experimental results show that the proposed Explainable AI-Based Deep Learning System for prediction of customer churn in telecommunication industry has high prediction accuracy, reliability and interpretability, and thus it is a valuable decision-support tool for telecom organizations that aim to reduce customer a...
K. Teja, M. Arathi· International Journal for Re...· 0 citations
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This article explains how ontology-based semantic layers work and advocates for their use as versatile enterprise tools. They add shared meaning, context, and governance to data, improving integration, analytics, oversight, and AI reliability across organizational systems.
Sally Hubbard, Elena Loukoianova, Hsiao-Ying Lin· Computer· 0 citations
Artificial intelligence has moved convincingly beyond proof-of-concept in AMR diagnostics and discovery, but its path to the clinic now depends less on further algorithmic refinement than on prospective validation, equitable data representation, and interpretability standards that clinicians can reasonably trust.
Digital Twin (DT) technologies enable the creation of virtual replicas of learning environments, supporting personalized and real-time educational interventions. However, the integration of Artificial Intelligence (AI) within DT-enabled e-learning introduces critical challenges related to explainability, security, and...
Edrees A. Alkinani· IEEE Communications Standard...· 1 citation
Digital twin (DT) technology real-time digital counterparts of physical assets has advanced rapidly across critical sectors. In the 6G era, the integration of DTs with ultra-low latency communication, edge intelligence, and artificial intelligence (AI) promises predictive control, enhanced collaboration, and resilient...
The quick development of financial technologies and digital transactions has made fraud detection and regulatory compliance more difficult. This study introduces a Financial Digital Twin with Explainable AI over 6G (FinDT-XAI6G) to enhance real-time fraud detection and compliance monitoring in financial systems. The pr...
Digital twins (DTs) are rapidly emerging as foundational enablers of 6G smart cities, offering real time monitoring, predictive analytics, and autonomous control across transportation, energy, healthcare, and industrial domains. Large scale DT adoption faces critical barriers including cybersecurity vulnerabilities, pr...
Li Wang, Xiuming Cheng· IEEE Communications Standard...· 2 citations
Combining hybrid ensemble learning, two-stage feature selection, and XAI approaches provides a computationally efficient, dependable, and interpretable method for PCOS diagnosis and practitioners may find this model to be a useful decision-support tool that improves the accuracy of diagnosis and lessens the need for hu...
Md Rakibul Hasan Efty, M. Rohman, K. M. Uddin et al.· Health Science Reports· 0 citations
AI-based models, particularly CNN-based DL architectures, demonstrate clinically relevant diagnostic performance with high sensitivity, specificity, and diagnostic odds ratios, supporting their potential role as adjunctive tools in CBCT-based differentiation of OKCs from other odontogenic lesions.
R. Shoorgashti, S. Lesan, S. S. Ehsani et al.· Health Science Reports· 0 citations
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
MIT News · Artificial Intelligence· news.mit.eduOct 15, 2026
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
