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Artificial Intelligence-Enhanced Risk Stratification of Cancer Therapeutics-Related Cardiac Dysfunction Using Electrocardiographic Images.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: Risk stratification strategies for cancer therapeutics-related cardiac dysfunction (CTRCD) rely on serial monitoring by specialized imaging, limiting their scalability. We aimed to examine an application of artificial intelligence (AI) to...

Prediction of delayed breastfeeding initiation among mothers having children less than 2 months of age in East Africa: application of machine learning algorithms.

Frontiers in public health
BACKGROUND: Delayed breastfeeding initiation is a significant public health concern, and reducing the proportion of delayed breastfeeding initiation in East Africa is a key strategy for lowering the Child Mortality rate. However, there is limited evi...

Shot-Noise Limited Nonlinear Optical Imaging Excited With GHz Femtosecond Pulses and Denoised by Deep-Learning.

Journal of biophotonics
Multiphoton fluorescence microscopy excited with femtosecond pulses at high repetition rates, particularly in the range of 100's MHz to GHz, offers an alternative solution to suppress photoinduced damage to biological samples, for example, photobleac...

Delay learning based on temporal coding in Spiking Neural Networks.

Neural networks : the official journal of the International Neural Network Society
Spiking Neural Networks (SNNs) hold great potential for mimicking the brain's efficient processing of information. Although biological evidence suggests that precise spike timing is crucial for effective information encoding, contemporary SNN researc...

Hybrid clinical-radiomics model based on fully automatic segmentation for predicting the early expansion of spontaneous intracerebral hemorrhage: A multi-center study.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: Early prediction of hematoma expansion (HE) is important for the development of therapeutic strategies for spontaneous intracerebral hemorrhage (sICH). Radiomics can help to predict early hematoma expansion in intracerebral hemorrhage. Ho...

Impact of artificial intelligence assisted compressed sensing technique on scan time and image quality in musculoskeletal MRI - A systematic review.

Radiography (London, England : 1995)
INTRODUCTION: Magnetic Resonance Imaging (MRI) has revolutionized the diagnosis and treatment of musculoskeletal disorders. Parallel imaging (PI) and compressed sensing (CS) techniques reduce scan time, but higher acceleration factors decrease image ...

Relaxed stability criteria of delayed neural networks using delay-parameters-dependent slack matrices.

Neural networks : the official journal of the International Neural Network Society
This note aims to reduce the conservatism of stability criteria for neural networks with time-varying delay. To this goal, on the one hand, we construct an augmented Lyapunov-Krasovskii functional (LKF), incorporating some delay-product terms that ca...

Time-series domain adaptation via sparse associative structure alignment: Learning invariance and variance.

Neural networks : the official journal of the International Neural Network Society
Domain adaptation on time-series data, which is often encountered in the field of industry, like anomaly detection and sensor data forecasting, but received limited attention in academia, is an important but challenging task in real-world scenarios. ...

Deep learning model for intravascular ultrasound image segmentation with temporal consistency.

The international journal of cardiovascular imaging
This study was conducted to develop and validate a deep learning model for delineating intravascular ultrasound (IVUS) images of coronary arteries.Using a total of 1240 40-MHz IVUS pullbacks with 191,407 frames, the model for lumen and external elast...