The analysis of histopathological images is an important method of diagnosing cancer. Deep learning models, such as convolutional neural networks and transformer-based models have demonstrated great potential in automated cancer detection. However, they are black-box and cannot be understood in a clinical context. In t...
Anandhi K., Krithiga T.· Indian Journal of Computer S...· 0 citations
Computational Chemical Engineering Explained: Models & Simulation serves as an open educational resource (OER) curriculum framework and foundational reference manual connecting first-principles transport phenomena, numerical methods, and modern data-driven architectures to chemical process design and control. Developed...
Prep4Uni.Online· Zenodo (CERN European Organi...· 0 citations
Precision medicine is transforming drug response from a population level assumption into an individualised biochemical event. Pharmacometabolomics, which profiles metabolic signatures associated with drug exposure and response, offers a mechanistic basis for explaining interindividual variability in therapeutic efficac...
Okechukwu Paul-Chima Ugwu, Maria Edet Umo, Richard A. Akwagiobe et al.· Frontiers in Pharmacology· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
Computational Chemical Engineering Explained: Models & Simulation serves as an open educational resource (OER) curriculum framework and foundational reference manual connecting first-principles transport phenomena, numerical methods, and modern data-driven architectures to chemical process design and control. Developed...
Prep4Uni.Online· Zenodo (CERN European Organi...· 0 citations
Abstract AI-enabled applications have achieved widespread adoption for complex problem-solving and informed decision-making. However, growing concerns regarding AI system failures that lead to bias, inequalities, and untrustworthy outcomes necessitate a move beyond performance evaluation to ensure trustworthy, equitabl...
AI and Big Data Analytics for Business Management: Concepts, Tools and Strategies explores how artificial intelligence and big data analytics are transforming modern business decision-making and management practices. The book explains key concepts, analytical tools, technologies, and strategies used to collect, process...
Dr.B. Gopi, G. Radha Krishna Murthy, Medishetti Swetha et al.· Zenodo (CERN European Organi...· 0 citations
AI information service platforms must allocate heterogeneous requests across models, memory, clarification, and human review under joint resource constraints. We develop CAST, a cognition-aware five-action service-triage framework; CAST-ERM learns group-level empirical allocations, and CAST-DRO adds a configurable mean...
Hengyu Sha, Yanjie Song, Xiaoshuai Hao et al.· Information Processing & Man...· 0 citations
Data management plan for an industrial doctorate on evaluative AI for strategic decision-making in SMEs, produced with CORA.eiNa DMP (CSUC) using the UOC doctoral-student template. It is maintained as a living document, revised when the facts change rather than filed once. The plan covers data collection from public UK...
Gines Molina-Abril· Zenodo (CERN European Organi...· 0 citations
Human-computer interaction has become fundamental to modern society. Improvements in this field have extensive potential across a number of important application domains, such as the capacity to augment human efficiency in the industry sector, evolve technology consumption in recreational settings, and transform learni...
Thomas Simpson· Research Portal (Queen's Uni...· 0 citations
Explainability offers a powerful lens for understanding and improving the robustness of Machine Learning (ML) models. This work demonstrates how eXplainable AI (XAI) techniques can be used not only to interpret model behaviour, but also to develop robust training algorithms that encourage the learning of semantically m...
Jeff Norman Mitchell· Research Portal (Queen's Uni...· 0 citations
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.
MIT News · Artificial Intelligence· news.mit.eduOct 6, 2026
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
