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2,280 papers
The integration of artificial intelligence (AI) and deep learning with the biomedical research marks a critical inflection point, shifting the paradigm from addressing symptoms to predicting and acting at the molecular level. In many diagnostic models, the chain reaction triggered by a chronic infection is often overlo...
As the crisis of antibiotic resistance escalates, phage therapy has regained attention as an alternative strategy. Artificial intelligence (AI) technologies offer new avenues to overcome the bottlenecks inherent in traditional bacteriophage research. This review summarizes the multi-dimensional innovative applications...
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Due to persistent diagnostic delays, varied disease progression, and unpredictable therapy responses, viral hepatitis remains a major worldwide health concern despite advances in antiviral medication and vaccine. Precision hepatology is a viable strategy for overcoming these limitations through tailored, data-driven cl...
NS-MFM-DGA is introduced, a neural-symbolic multimodal foundation model that incorporates dynamic graph attention for real-time anomaly detection in SD-ICPS and provides a feasible and explainable low-latency anomaly-detection framework for supervisory monitoring in SD-ICPS.
STLC-Net (Skin Transfer Learning Classification Network) is introduced, a robust, zero-data-leakage framework for automated seven-class skin lesion classification using the benchmark HAM10000 dataset and integrated into an interactive web deployment for real-time, interpretable clinical decision support.
AI-Enabled National Water Conservation and Security System for Qatar A Research and Policy Framework for an Intelligent National Water Digital Twin, Predictive AI and ILM-Based Water Intelligence Platform Prepared as a concept paper for Qatar Government consideration Abstract Qatar’s water security challenge is fundame...
A component-level FAIR (Findable, Accessible, Interoperable, Reusable) assessment of the IEMAP platform is reported, the domain ontology that underpins its interoperability is published, and a roadmap towards native semantic querying and knowledge-graph integration is outlined.
The current three-dimensional (3D) geological implicit modelling methods are mainly based on interpolation methods, which struggle to capture the nonlinear characteristics of complex geological structures and are limited in their capacity to integrate multi-source modeling data. To overcome these limitations, we propos...
This software package contains the Model04 EIGT-Net implementation developed for the MPGSD-AEB study. The package includes the trained model parameters, PyTorch model implementation, graph definition, MATLAB/Simulink forward-inference model, and fixed-step data feeder for hardware-in-the-loop preparation. The model pro...
Predicting molecular properties is a central challenge in cheminformatics and plays a critical role in drug discovery and materials science. Lipophilicity, which describes the partitioning of a molecule between lipid and aqueous environments, is a key physicochemical property influencing drug behavior. Although quantum...
A cross-section of the MIT community convened discussions on topics ranging from data centers and super pollutants to agriculture and education.
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.
Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word.
Cryptographic code supports vital protections in modern computing systems. Learn how a new method helps verify code as developers write it while preserving speed and adaptability as it gets implemented and evolves. The post Verifying Rust cryptography in SymCrypt, from standards to code appeared first on Microsoft Research.
PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.
Climate & Sustainability
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