AIMC Topic: Time Factors

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Comparison of machine learning models with conventional statistical methods for prediction of percutaneous coronary intervention outcomes: a systematic review and meta-analysis.

BMC cardiovascular disorders
INTRODUCTION: Percutaneous coronary intervention (PCI) has been the main treatment of coronary artery disease (CAD). In this review, we aimed to compare the performance of machine learning (ML) vs. logistic regression (LR) models in predicting differ...

Time series compression using quaternion valued neural networks and quaternion backpropagation.

Neural networks : the official journal of the International Neural Network Society
We propose a novel quaternionic time series compression methodology where we divide a long time series into segments of data, extract the min, max, mean and standard deviation of these chunks as representative features and encapsulate them in a quate...

Towards real-time conformal palliative treatment of spine metastases: A deep learning approach for Hounsfield Unit recovery of cone beam CT images.

Medical physics
BACKGROUND: The extension of onboard cone-beam CT (CBCT) imaging for real-time treatment planning is constrained by limitations in image quality. Synthetic CT (sCT) generation using deep learning provides a potential solution to these limitations.

Machine learning-based return-to-work assessment system for acute myocardial infarction patients within 12 months.

Heart & lung : the journal of critical care
BACKGROUND: Returning to work is a critical indicator of recovery after acute myocardial infarction (AMI), and accurate identification of patients with low return-to-work rates is critical for timely intervention.

Deep learning unlocks the true potential of organ donation after circulatory death with accurate prediction of time-to-death.

Scientific reports
Increasing the number of organ donations after circulatory death (DCD) has been identified as one of the most important ways of addressing the ongoing organ shortage. While recent technological advances in organ transplantation have increased their s...

Framingham Risk Score Prediction at 12 Months in the STANDFIRM Randomized Control Trial.

Journal of the American Heart Association
BACKGROUND: The STANDFIRM (Shared Team Approach Between Nurses and Doctors for Improved Risk Factor Management; ANZCTR registration ACTRN12608000166370) trial was designed to test the effectiveness of chronic disease care management for modifying the...

Depth-of-interaction encoding techniques for pixelated PET detectors enabled by machine learning methods and fast waveform digitization.

Physics in medicine and biology
. Pixelated detectors with single-ended readout are routinely used by commercial positron emission tomography scanners owing to their good energy and timing resolution and optimized manufacturing, but they typically do not provide depth-of-interactio...

Recognition of beef aging time using a miniaturized near-infrared spectrometer in tandem with support vector machine.

Food chemistry
Consumers increasingly demand sustainable production practices and high-quality standards. Near-infrared (NIR) spectroscopy presents a non-invasive and efficient tool for addressing these concerns. This study aimed to evaluate vacuum-aged beef across...