Results 211 to 220 of about 5,636 (303)

Comparison of deep learning models for real-time neural tissue segmentation in spinal endoscopy. [PDF]

BMC Med Imaging
Rhee W, Lee HR, Chang BS, Chang SY, Kim H.   +4 more
europepmc   +1 more source

ProSiteHunter: A Unified Framework for Sequence‐Based Prediction of Protein‐Nucleic Acid and Protein‐Protein Binding Sites

Advanced Science, EarlyView.
This study proposed a unified sequence‐based framework for protein binding site prediction, which adopted a tri‐track semantic multi‐source feature fusion strategy to effectively capture diverse macromolecular interaction sites and further improved the accuracy of antibody‐antigen interaction prediction.
Dongliang Hou, Qihang Zhen, Zexin Lv, Xinyue Cui, Suhui Wang, Minghua Hou, Zhan Zhou, Xiaogen Zhou, Guijun Zhang   +8 more
wiley   +1 more source

Enhancing brain tumor segmentation using attention based convolutional UNet on MRI images. [PDF]

Sci Rep
Abrar M, Salam A, Ullah F, Ullah F, Al Ghamdi AS.   +4 more
europepmc   +1 more source

COMPARISON OF GOOGLE NET CONVOLUTIONAL NEURAL NETWORK TO VISUAL GEOMETRY GROUP CONVOLUTIONAL NEURAL NETWORK

, 2022
Pepple, Mc-Kelly, Ikeremo, EFIYESEIMOKUMO   +1 more
openaire   +2 more sources

Construction of Sabatier Volcanoes for CO2 Hydrogenation to C1‐2 Oxygenates Using Data‐Efficient Machine Learning

Advanced Science, EarlyView.
A new data‐efficient framework combining DFT calculations, a neural network model, and automated graph analysis of catalytic reaction networks is proposed and applied to CO2 hydrogenation on transition metal nanoparticles. The analysis shows how efficient C2 oxygenate production requires a balance between CHx formation, C–C coupling, protonation, and ...
Mikhail V. Polynski, Sergey M. Kozlov
wiley   +1 more source

GAN-based bone suppression using a combined loss function. [PDF]

Front Artif Intell
Jochymek L, Vašinková M, Doleží V, Gajdoš P.   +3 more
europepmc   +1 more source

Accurately Deciphering Tissue Heterogeneity From Spatial Multi‐Modal and Multi‐Omics With STransformer

Advanced Science, EarlyView.
STransformer is a unified deep learning framework designed to seamlessly accommodate a comprehensive landscape of spatial data. By simultaneously capturing short‐range cellular interactions and tissue‐wide semantic patterns, it extracts robust representations to accurately dissect complex tissue heterogeneity.
Xingyi Li, Jialuo Xu, Gaoyuan Du, Xiangting Jia, Dongmin Zhao, Chunyan Zhou, Kexin Xiao, Jia Gu, Junnan Zhu, Xuequn Shang   +9 more
wiley   +1 more source

Cardio-Dense: Diagnosis of Cardiac Abnormalities Based on Phonocardiogram Using Improved Swin Transformer Through Lightweight Dense Blocks. [PDF]

Diagnostics (Basel)
Ahmed AES, Ibrahim MEA, Daadaa Y.
europepmc   +1 more source

AI‐Physics‐Experiment Trinity for Integrated Protein Dynamics Modeling

Advanced Science, EarlyView.
This review unites experiments, physics‐based simulations, and AI as a synergistic triad for protein dynamics modeling. It highlights integrative strategies, resolves sampling and forcefield bottlenecks, and outlines challenges and future directions for accurate, interpretable conformational ensemble prediction.
Chen Shi, Minying Low, Peng Xiu, Kresten Lindorff‐Larsen, Yong Wang   +4 more
wiley   +1 more source

Metaheuristic optimization of deep CNNs for multi-class diagnosis of cervical cancer and lymphoma. [PDF]

Sci Rep
Abdelhay EH, Elgamily KM, Badr WOE.
europepmc   +1 more source