Frontiers

Advancing Deep Learning Frameworks for Enhanced Cervical Cancer Diagnosis, Staging and Treatment

Cervical cancer detection and diagnosis are undergoing a transformation with the integration of advanced deep learning (DL) technologies. Despite ...
Morning Overview on MSN

Scientists build a ‘periodic table’ for AI models

Scientists are trying to tame the chaos of modern artificial intelligence by doing something very old fashioned: drawing a table. Instead of chemical elements, the new chart arranges learning ...
Beebom

What is Deep Learning in AI? Understanding How AI Really Works

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
C&EN

Deep Learning-Based Shape Classification for Hyperspectral-Imaged Microplastics

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...
ascopubs.org

Deep-Learning Model for Real-Time Prediction of Recurrence in Early-Stage Non–Small Cell Lung Cancer: A Multimodal Approach (RADAR CARE Study)

Physiologically Based Pharmacokinetic Model to Assess the Drug-Drug-Gene Interaction Potential of Belzutifan in Combination With Cyclin-Dependent Kinase 4/6 Inhibitors A total of 14,177 patients were ...
GitHub

Multimodal deep learning integration of cryo-EM and AlphaFold3 for high-accuracy protein structure determination

Cryo-electron microscopy (cryo-EM) is a key technology for determining the structures of proteins, particularly large protein complexes. However, automatically building high-accuracy protein ...
C&EN

A Deep Learning Framework for the Electronic Structure of Water: Toward a Universal Model

Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 90871, P. R. China HEDPS, CAPT, College of Engineering, Peking University, Beijing 100871 ...
pv magazine International

Hybrid deep learning model for PV forecasting in scenarios with considerable fluctuations

Researchers in China conceived a new PV forecasting approach that integrates causal convolution, recurrent structures, attention mechanisms, and the Kolmogorov–Arnold Network (KAN). Experimental ...