An international research team, with significant involvement from the Medical University of Vienna, has developed a new AI-based analysis method that can accurately classify brain tumors using genetic ...
Researchers used 16S rRNA sequencing and machine learning to identify gut microbiome patterns associated with insulin resistance severity in people with type 2 diabetes. XGBoost models showed that ...
High school students gain PhD-led mentorship, publish original research, and build real-world AI models through ...
Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
AZoSensors on MSN
Low-power sensor node brings machine learning to the edge of environmental monitoring
A new low-power sensor node framework combines sensing and machine learning, with the potential to enhance real-time environmental monitoring while optimizing energy efficiency.
Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...
Background: The proposed Architecture will provide the processing and analysis essential to accurate and reliable detection of brain tumors from MRI, for timely diagnosis and evidence-based decisions.
Abstract: Deep learning-based approaches to hyperspectral image analysis have attracted large attention and exhibited high performance in image classification tasks. However, deployment of deep ...
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