Learning to identify new objects reshapes parts of the brain, research finds

The wiring and rewiring of the brain never ends. Neural pathways are constantly being reshaped as we interact with the world ...
RMD Open

Development and assessment of an assisted diagnosis model using machine learning for identifying adult-onset Still’s disease in fever of unknown origin: a retrospective …

Background Adult-onset Still’s disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic ...
Frontiers

Benchmarking, Evaluation, and Reproducibility in Earth Observation Machine Learning

Earth observation relies on diverse imaging systems whose varying spatial, spectral, radiometric, and temporal ...
BMJ Open

Organizational learning models in continuing health education: a scoping review protocol

Background Citizens depend on high-quality healthcare; however, significant disparities in quality persist among healthcare organisations. Healthcare services are complex organisations, making it ...
GitHub

SkySense: A Multi-Modal Remote Sensing Foundation Model Towards Universal Interpretation for Earth Observation Imagery

Prior studies on Remote Sensing Foundation Model (RSFM) reveal immense potential towards a generic model for Earth Observation. Nevertheless, these works primarily focus on a single modality without ...
C&EN

Stacking Machine Learning Models Empowered High Time-Height-Resolved Ozone Profiling from the Ground to the Stratopause Based on MAX-DOAS Observation

Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China ...
The Lancet

Validation and utility of ARDS subphenotypes identified by machine-learning models using clinical data: an observational, multicohort, retrospective analysis

aDivision of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, Stanford University, Stanford, CA, USA bDivision of Hospital Medicine, University of California, San Francisco, San ...
philstar.com

Reclaiming classroom observation as a tool for learning, not fear

For many teachers today, classroom observation no longer feels like professional support. It has become a moment of performance, something to be rehearsed, perfected, and survived. Lessons are ...
Microsoft

Optimizing Cloud-to-GPU Throughput for Deep Learning With Earth Observation Data

Training deep learning models on petabyte-scale Earth observation (EO) data requires separating compute resources from data storage. However, standard PyTorch data loaders cannot keep modern GPUs ...
IEEE

Learning to Count Grave Sites for Cemetery Observation Models With Satellite Imagery

Abstract: Understanding how people occupy open spaces is important for research in support of population modeling, policy, national security, emergency response, and sustainability. For the past ...
ZDNet

AI models know when they're being tested - and change their behavior, research shows

Several frontier AI models show signs of scheming. Anti-scheming training reduced misbehavior in some models. Models know they're being tested, which complicates results. New joint safety testing from ...
GitHub

REOBench: Benchmarking Robustness of Earth Observation Foundation Models

We introduce REOBench, a comprehensive Benchmark designed to evaluate the Robustness of Earth Observation Foundation Models. Our benchmark systematically evaluates the robustness of extensive ...