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 Apr 23, 2025
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 Factors Treatment Outcome Predictive Value of Tests Percutaneous Coronary Intervention Coronary Artery Disease Aged Male Middle Aged Risk Assessment Decision Support Techniques Female Humans Reproducibility of Results Machine Learning Risk Factors
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Towards real-time conformal palliative treatment of spine metastases: A deep learning approach for Hounsfield Unit recovery of cone beam CT images.

Medical physics Apr 21, 2025
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.
Palliative Care Radiotherapy, Conformal Spinal Neoplasms Time Factors Humans Cone-Beam Computed Tomography Deep Learning Image Processing, Computer-Assisted Radiotherapy Planning, Computer-Assisted
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Deep learning unlocks the true potential of organ donation after circulatory death with accurate prediction of time-to-death.

Scientific reports Apr 19, 2025
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...
Humans Neural Networks, Computer Intensive Care Units Tissue and Organ Procurement Middle Aged Deep Learning Time Factors Female Death Aged Adult Male
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Framingham Risk Score Prediction at 12 Months in the STANDFIRM Randomized Control Trial.

Journal of the American Heart Association Apr 16, 2025
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...
Middle Aged Risk Assessment Time Factors Predictive Value of Tests Stroke Ischemic Attack, Transient Female Risk Factors Humans Aged Machine Learning Male
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Estimated glucose disposal rate outperforms other insulin resistance surrogates in predicting incident cardiovascular diseases in cardiovascular-kidney-metabolic syndrome stages 0-3 and the development of a machine learning prediction model: a nationwide prospective cohort study.

Cardiovascular diabetology Apr 16, 2025
BACKGROUND: The American Heart Association recently introduced the concept of cardiovascular-kidney-metabolic (CKM) syndrome, highlighting the increasing importance of the complex interplay between metabolic, renal, and cardiovascular diseases (CVD)....
Time Factors Insulin Resistance Longitudinal Studies Metabolic Syndrome Kidney Diseases Predictive Value of Tests Risk Assessment Humans China Machine Learning Blood Glucose Decision Support Techniques Incidence Aged Prognosis Female Risk Factors Male Prospective Studies Cardiovascular Diseases Biomarkers Middle Aged
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Depth-of-interaction encoding techniques for pixelated PET detectors enabled by machine learning methods and fast waveform digitization.

Physics in medicine and biology Apr 14, 2025
. 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...
Image Processing, Computer-Assisted Positron-Emission Tomography Machine Learning Time Factors
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Improved prediction and risk stratification of major adverse cardiovascular events using an explainable machine learning approach combining plasma biomarkers and traditional risk factors.

Cardiovascular diabetology Apr 2, 2025
BACKGROUND: Cardiovascular diseases (CVD) remain the leading cause of morbidity and mortality globally. Traditional risk models, primarily based on established risk factors, often lack the precision needed to accurately predict new-onset major advers...
Decision Support Techniques Biomarkers Prognosis Female Humans Machine Learning Risk Assessment Time Factors Metabolomics Predictive Value of Tests Aged Male Cardiovascular Diseases Middle Aged Heart Disease Risk Factors United Kingdom
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Prediction of Chromatographic Retention Time of a Small Molecule from SMILES Representation Using a Hybrid Transformer-LSTM Model.

Journal of chemical information and modeling Mar 28, 2025
Accurate retention time (RT) prediction in liquid chromatography remains a significant consideration in molecular analysis. In this study, we explore the use of a transformer-based language model to predict RTs by treating simplified molecular input ...
Small Molecule Libraries Neural Networks, Computer Time Factors Chromatography, High Pressure Liquid Chromatography, Reverse-Phase
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Stability of Jurkat cells during short-term liquid storage analyzed by flow imaging microscopy.

European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V Mar 26, 2025
The viability of cell-based medicinal products (CBMPs) is a critical quality attribute and must be assessed throughout the product lifecycle to contribute to a safe and potent drug product. In this study, we investigated the impact of short-term liqu...
Humans Flow Cytometry Dimethyl Sulfoxide Microscopy Drug Storage Jurkat Cells Temperature Time Factors Culture Media Cell Survival
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Machine Learning Identification of Patient Phenoclusters in Aortic Regurgitation.

JACC. Cardiovascular imaging Mar 26, 2025
BACKGROUND: Current treatment paradigms assume aortic regurgitation (AR) patients to be a homogenous population, but varied courses of disease progression and outcomes are observed clinically.
Phenotype Disease Progression Prognosis Severity of Illness Index Humans Reproducibility of Results Male Retrospective Studies Aortic Valve Insufficiency Time Factors Machine Learning Ventricular Function, Left Risk Factors Female United States Magnetic Resonance Imaging, Cine Middle Aged Decision Support Techniques Aged Aortic Valve Risk Assessment Adult Unsupervised Machine Learning Predictive Value of Tests Sex Factors
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