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1,892 papers
In present times, the rise of electronic healthcare has made vast amounts of public health data available, including clinical health records, laboratory results, genomic datasets, and public health–monitoring data. These datasets give significant opportunities for artificial intelligence (AI) to strengthen healthcare b...
The combination of artificial intelligence (AI) and precision medicine could potentially change the way medicine is practiced. In this scenario, advances in precision medicine technology will enable healthcare providers to identify the phenotype of each patient who has a unique β-cell response to treatment, as well as...
EL-RAKHAWI BIO-COGNITIVE ENGINEERING: EXECUTIVE SUMMARY This treatise establishes the El-Rakhawi Doctrine of Comprehensive Bio-Cognitive Engineering, integrating three post-AlphaFold pillars: 1. **Causal Bio-Ontological Knowledge Graph (CBOKG)**: Merges bio-ontologies with Hidden Markov Models and stochastic grammars (...
Deep learning has been a key component of recent advancements in medical image processing, but traditional centralized learning models raise serious questions about data privacy in health data. Federated Learning (FL) is a novel paradigm for training models across institutions without sharing any raw medical data. In t...
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Mobile learning scenarios in adult education impose mutually constraining technical requirements regarding real‑time interaction performance, recommendation accuracy, and data privacy protection. Neither cloud‑centric centralized inference nor device‑only local com‑ putation can adequately satisfy these demands. In thi...
[1] N. J. Sarna, F. A. Rithen, U. S. Jui, S. Belal, Al Amin, T. K. Oishee, and A. K. M. Muzahidul Islam, “AI Driven Fraud Detection Models in Financial Networks: A Comprehensive Systematic Review,” IEEE Access, vol. 13, pp. 141204–141233, 2025, doi: 10.1109/ACCESS.2025.3596060. [2] A. A. Almazroi and N. Ayub, “Online P...
The pharmaceutical industry faces persistent challenges in discovering and developing safe, effective, and affordable medicines. Artificial intelligence (AI) has emerged as a transformative computational technology capable of supporting multiple stages of the drug-development pipeline. Machine learning, deep learning,...
The El-Rakhawi Theory of Symbiotic Urban Intelligence and Regenerative Industrial Ecosystems (DOI: 10.5281/zenodo.23192881) integrates urban metabolism, sovereign digital governance, and precision manufacturing into a unified self-healing national ecosystem. Three pillars: (1) Regenerative Urban Metabolism with genetic...
The IDERHA ( I ntegration of Heterogeneous D ata and E vidence towards R egulatory and H TA A cceptance) project aims to enhance medical research by establishing one of Europe’s first pan-European, disease-agnostic health data spaces. Aligned with the European Health Data Space (EHDS) principles, IDERHA addresses criti...
The rapid progress in digitization of core industries has increased the size of the threat horizon to the point where cybersecurity measures must be more articulate, adaptive, and intelligent. As cyber-attacks are increasingly evolving and become more complex, attempts to secure networks with traditional methods are be...
Agricultural crops experience environmental and physiological stressors that evolve across space and time. These processes are only indirectly observable through imaging and are frequently monitored across geographically distributed sites with heterogeneous conditions and restricted data sharing. This study formulates...
A new machine-learning approach broke records for weather forecasting for an important time frame in emergency planning.
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.
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
Learn more about our approach to safety and security for Gemini 4 Argon.
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.
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
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