Results 201 to 210 of about 21,160 (284)

DeepRelaxo: Fast Mono‐Exponential Magnitude Brain R2* Mapping With Reduced Echoes Using Self‐Supervised Deep Learning

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose We introduce DeepRelaxo, a fast and generalizable deep learning method for estimating brain R2* maps from multi‐echo gradient echo (ME‐GRE) acquisitions with arbitrary echo configurations, including shortened echo trains for accelerated scans.
Samiha Prima, Zhuang Xiong, Alan H. Wilman, Hongfu Sun   +3 more
wiley   +1 more source

Explainable Ensemble Learning and Multilayer Perceptron Modeling for Compressive Strength Prediction of Ultra-High-Performance Concrete. [PDF]

Biomimetics (Basel)
Aydın Y, Cakiroglu C, Bekdaş G, Geem ZW.   +3 more
europepmc   +1 more source

Physics‐Guided Neural Network for Quantitative Parameter Mapping Using Balanced Steady State Free Precession MRI

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To propose a new method using a physics‐guided neural network for quantitative parameter mapping in balanced steady‐state free precession (bSSFP) imaging. Theory and Methods We trained physics‐guided neural networks with a multilayer perceptron using simulated bSSFP signals generated from tissue parameters (T1$$ {T}_1 $$, T2$$ {T}_2 $$,
Hye‐Ryeong Choi, Huan Minh Luu, Sung‐Hong Park   +2 more
wiley   +1 more source

Experimental Modal Analysis‐Driven Gaussian Process Regression Modeling of Rectangular Steel Beams With Various Hole Geometries

International Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT Understanding the dynamic behavior of structural components is crucial for optimizing performance and ensuring structural integrity. This study presents a new method that combines a systematic experimental investigation of four distinct hole geometries (circular, square, compact rectangular, and long rectangular) with varying hole counts, all ...
Amir Hossein Rabiee, Majid Rajaei, Mohammad Hossein Mahdavi Nasab, Parsa Shafiei   +3 more
wiley   +1 more source

Machine learning methods for designing a carbon dot based photoluminescent multimodal nanosensor. [PDF]

Sci Rep
Chugreeva G, Laptinskiy K, Guskov A, Kupriyanov G, Isaev I, Dolenko S, Dolenko T.   +6 more
europepmc   +1 more source

Machine learning‐based predictive models versus traditional risk scores in hemodialysis patients with comorbid urolithiasis

Precision Medical Sciences, EarlyView.
Machine learning‐based predictive models outperform traditional risk scores in hemodialysis patients with comorbid urolithiasis by capturing nonlinear, dialysis‐specific interactions. These approaches enable more accurate prediction of stone recurrence, sepsis, hospitalization, and mortality, supporting personalized risk stratification and precision ...
Dipal Chaulagain, Muhammad Riaz, Mirza Muhammad Hadeed Khawar, Jawad Hameed, Malik Sohail Riaz   +4 more
wiley   +1 more source

Associations Between Thyroid Function and Periodontitis: A Machine Learning Approach Using NHANES. [PDF]

Int Dent J
Wang H, Tian S, Bai S, Yang C, Jiang Z, Li N.   +5 more
europepmc   +1 more source

A composite‐loss graph neural network for the multivariate post‐processing of ensemble weather forecasts

Quarterly Journal of the Royal Meteorological Society, EarlyView.
The dual graph neural network (dualGNN), trained with a composite loss combining the energy score (ES) and variogram score (VS), consistently outperformed models optimized solely for ES or the continuous ranked probability score in the multivariate setting, as well as empirical copula approaches.
Mária Lakatos
wiley   +1 more source

Using artificial intelligence to predict posttransplant diabetes mellitus: a new step toward personalized medicine. [PDF]

Kidney Res Clin Pract
Chung BH.
europepmc   +1 more source

Polar‐low track prediction using machine‐learning methods

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Machine‐learning models are developed to produce reliable and efficient forecasts of polar‐low (PL) trajectories 12 hours ahead. A temporal model (RLSTM) benefiting from the rolling‐forecast strategy, improves overall prediction accuracy and is suitable for quick experimentation, while a spatiotemporal model (PL‐UNet), incorporating both historical and
Ziying Yang, Rune Grand Graversen, Filippo Maria Bianchi, Jiping Liu, Ruibo Lei   +4 more
wiley   +1 more source