AIMC Topic: Time Factors

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Short insemination during conventional in vitro fertilization increases embryo quality.

Andrology
AIM: To compare clinical outcomes using short and long co-incubation protocols in sibling oocytes based on embryo morphokinetic outcomes measured by time-lapse incubator with stratification based on a woman's age and sperm quality.

DyGraphformer: Transformer combining dynamic spatio-temporal graph network for multivariate time series forecasting.

Neural networks : the official journal of the International Neural Network Society
Transformer-based models demonstrate tremendous potential for Multivariate Time Series (MTS) forecasting due to their ability to capture long-term temporal dependencies by using the self-attention mechanism. However, effectively modeling the spatial ...

Machine Learning Model for Predicting Risk Factors of Prolonged Length of Hospital Stay in Patients with Aortic Dissection: a Retrospective Clinical Study.

Journal of cardiovascular translational research
The length of hospital stay (LOS) is crucial for assessing medical service quality. This study aimed to develop machine learning models for predicting risk factors of prolonged LOS in patients with aortic dissection (AD). The data of 516 AD patients ...

Unraveling the determinants of traffic incident duration: A causal investigation using the framework of causal forests with debiased machine learning.

Accident; analysis and prevention
Predicting the duration of traffic incidents is challenging due to their stochastic nature. Accurate predictions can greatly benefit end-users by informing their route choices and safety warnings, while helping traffic operation managers more effecti...

Correlation Fuzzy measure of multivariate time series for signature recognition.

PloS one
Distinguishing different time series, which is determinant or stochastic, is an important task in signal processing. In this work, a correlation measure constructs Correlation Fuzzy Entropy (CFE) to discriminate Chaos and stochastic series. It can be...

Adaptive wavelet-VNet for single-sample test time adaptation in medical image segmentation.

Medical physics
BACKGROUND: In medical image segmentation, a domain gap often exists between training and testing datasets due to different scanners or imaging protocols, which leads to performance degradation in deep learning-based segmentation models. Given the hi...

Predicting Individual Treatment Effects to Determine Duration of Dual Antiplatelet Therapy After Stent Implantation.

Journal of the American Heart Association
BACKGROUND: After coronary stent implantation, prolonged dual antiplatelet therapy (DAPT) increases bleeding risk, requiring personalization of DAPT duration. The aim of this study was to develop and validate a machine learning model to predict optim...

Plant-based egg washes for use in baked goods: Machine learning and visual parameter analysis.

Journal of food science
Pea protein is one potential environmentally sustainable way of recreating the functionality of eggs in coatings for baked goods. These coatings are commonly applied to enhance visual properties of baked goods that consumers desire, especially color ...

Interpretable machine learning models for the prediction of all-cause mortality and time to death in hemodialysis patients.

Therapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy
INTRODUCTION: The elevated mortality and hospitalization rates among hemodialysis (HD) patients underscore the necessity for the development of accurate predictive tools. This study developed two models for predicting all-cause mortality and time to ...