At a moment when the AI industry is obsessed with bigger models and higher scores, Professor Ganna Pogrebna opened the ...
Although large language models (LLMs) have the potential to transform biomedical research, their ability to reason accurately across complex, data-rich domains remains unproven. To address this ...
A new peer-reviewed study published in the journal Algorithms signals a major shift in how humanitarian logistics can be ...
Models using established cardiovascular disease risk factors had satisfactory predictive performance for 5-year CVD risk in ...
The ChatGPT o1 Pro can accurately identify glaucoma from visual field and optical coherence tomography data, a study shows.
Researchers at örebro University have developed two new AI models that can analyze the brain's electrical activity and accurately distinguish between healthy individuals and patients with dementia, ...
Abstract: The abstract is an imperfect defect detection model meant to classify various defects of castings. It presents an excellent precision, recall, and $\mathbf{F 1}$-score of six classes of ...
This paper presents ConvAttentionNet, a lightweight and high performing deep learning model developed for accurate and efficient classification of Polarimetric Synthetic Aperture Radar (PolSAR) ...
Abstract: Quantum Neural Networks (QNN) and Quantum Long Short-Term Memory (QLSTM) models are emerging as powerful tools in quantum machine learning. The effectiveness of these models is largely ...
ABSTRACT: A degenerative neurological condition called Parkinson disease (PD) that evolves progressively, making detection difficult. A neurologist requires a clear healthcare history from the ...
Researchers have developed an AI model that uses epigenetic DNA signatures to identify tumors with over 99% accuracy, potentially replacing risky biopsies with safer, faster diagnoses. Credit: ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results