AIMC Topic: Time Factors

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Metabolomic biomarkers could be molecular clocks in timing stroke onset.

Scientific reports
The preferred treatment for acute ischaemic stroke (AIS) is intravenous thrombolysis (IVT) administered within 4.5 hours (h) of symptom onset. This study aimed to identify metabolomic biomarkers for distinguishing AIS patients within 4.5 h of symptom...

From laser-on time to lithotripsy duration: improving the prediction of lithotripsy duration with 'Kidney Stone Calculator' using artificial intelligence.

World journal of urology
INTRODUCTION: "Kidney Stone Calculator" (KSC) helps to plan flexible ureteroscopy, providing the stone volume (SV) and an estimated duration of laser lithotripsy (eLD). eLD is calculated from in vitro ablation rates and SV. KSC's accuracy has been de...

Quantitative and automatic plan-of-the-day assessment to facilitate adaptive radiotherapy in cervical cancer.

Physics in medicine and biology
To facilitate implementation of plan-of-the-day (POTD) selection for treating locally advanced cervical cancer (LACC), we developed a POTD assessment tool for CBCT-guided radiotherapy (RT). A female pelvis segmentation model (U-Seg3) is combined with...

High-definition motion-resolved MRI using 3D radial kooshball acquisition and deep learning spatial-temporal 4D reconstruction.

Physics in medicine and biology
To develop motion-resolved volumetric MRI with 1.1 mm isotropic resolution and scan times <5 min using a combination of 3D radial kooshball acquisition and spatial-temporal deep learning 4D reconstruction for free-breathing high-definition (HD) lung ...

Time-Gated Raman Spectroscopy Combined with Deep Learning for Rapid, Label-Free Histopathological Discrimination of Gastric Cancer.

Analytical chemistry
Gastric cancer is one of the most common malignant tumors of the digestive system, with a high mortality rate due to late-stage diagnosis. Current clinical diagnosis relies on endoscopic biopsy and histopathological analysis, which are highly depende...

A systematic comparison of short-term and long-term mortality prediction in acute myocardial infarction using machine learning models.

BMC medical informatics and decision making
BACKGROUND AND OBJECTIVE: The machine learning (ML) models for acute myocardial infarction (AMI) are considered to have better predictive ability for mortality compared to conventional risk scoring models. However, previous ML prediction models have ...

Uncovering nonlinear patterns in time-sensitive prehospital breathing emergencies: an exploratory machine learning study.

BMC medical informatics and decision making
BACKGROUND: Timely prehospital care is crucial for patients presenting with high-risk time-sensitive (HRTS) conditions. However, the interplay between response time and demographic factors in patients with breathing problems remains insufficiently un...

Unlocking the Potential of Wear Time of a Wearable Device to Enhance Postpartum Depression Screening and Detection: Cross-Sectional Study.

JMIR formative research
BACKGROUND: Postpartum depression (PPD) is a mood disorder affecting 1 in 7 women after childbirth that is often underscreened and underdetected. If not diagnosed and treated, PPD is associated with long-term developmental challenges in the child and...