AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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.
Artificial intelligence-enabled approaches show promise for earlier and more objective ALS detection, but the current literature is dominated by small, retrospective, single-site studies.
Multiple sclerosis (MS) is a chronic neurological disorder affecting the central nervous system, causing a range of symptoms including vision problems, fatigue, and motor dysfunction. Early and accurate diagnosis is crucial for effective treatment and management of the disease. Magnetic Resonance Imaging (MRI) plays a...
This systematic review consolidates recent advances in ML for MS diagnosis and monitoring and proposes a task-based taxonomy linking clinical objectives to methodological families, providing a comprehensive roadmap toward building robust, data-efficient, and trustworthy ML systems for clinical decision support in MS.
Multimodal fusion architectures, particularly cross-attention transformers integrating motor, voice, and gait data, consistently outperformed unimodal approaches by 4%-8% in the area under the receiver operating characteristic curve (AUC), with the largest gains in early stage detection and differential diagnosis tasks...
Recent progress in AI-driven approaches for AD detection is discussed and the importance of interdisciplinary strategies to facilitate earlier diagnosis, improve patient outcomes, and support more effective management of Alzheimer's disease is underscored.
The MIT professors collaborated to identify the first AI-discovered antibiotic, a scientific breakthrough that is widely recognized as a milestone in AI-driven drug discovery.
Five MIT faculty members and two additional alumni are honored with fellowships to advance research on beneficial AI.
MIT professors Adam Berinsky and Chara Podimata discuss a new project to track how AI chatbots are responding to questions about the 2026 U.S. midterm elections.
Google DeepMind and UK government work together to reduce planning assessment times
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