A deep learning model using retinal images obtained during retinopathy of prematurity (ROP) screening may be used to predict diagnosis of bronchopulmonary dysplasia (BPD) and pulmonary hypertension ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known ...

Deep learning analysis of FDG PET-CT improves survival prediction in non-metastatic breast cancer, outperforming standard staging and single modality models while supporting interpretable and ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting expertise.From neural networks to N ...

Model predicts effect of mutations on sequences up to 1 million base pairs in length and is adept at tackling complex ...

Across the physical world, many intricate structures form via symmetry breaking. When a system with inherent symmetry ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

Recent survey delivers the first systematic benchmark of TSP solvers spanning end-to-end deep learners, hybrid methods and brand-new LLM-based hybrids, revealing that hybrids give best-in-class routes ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

A new study published in the Journal of the American Medical Association showed that using retinal scans of premature infants ...