Publications by authors named "R Sudha"
Article Synopsis
- Traditional COVID-19 detection using CT scans can be challenging and inconsistent, leading to variability in results.
- This study introduces an automated method to detect and classify COVID-19 using chest X-ray images by employing deep convolutional neural networks (DCNN) with enhanced pre-processing techniques.
- The findings suggest that applying image pre-processing significantly improved classification accuracy, particularly with the VGG16 model, potentially easing the workload for healthcare professionals in clinical settings.
This investigation attempts to propose a novel Wavelet and Local Binary Pattern-based Xception feature Descriptor (WLBPXD) framework, which uses a deep-learning model for classifying chronic infection amongst other infections. Chronic infection (COVID-19 in this study) is identified via RT-PCR test, which is time-consuming and requires a dedicated laboratory (materials, equipment, etc.) to complete the clinical results.
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- This study aimed to validate the Good Outcome Following Attempted Resuscitation (GO-FAR) score in patients without Do Not Attempt Resuscitation (DNAR) orders, focusing on those who experienced in-hospital cardiac arrest at Al Ain Hospital from January 2017 to December 2019.
- Out of 366 patients analyzed, the majority were male with a median age of 70; most had non-shockable rhythms and cardiac/respiratory causes for their arrests, resulting in a low survival rate and variable neurological outcomes.
- Findings suggest that a GO-FAR score below 4 is a reliable predictor of survival with good neurological function, indicating its usefulness in a diverse patient
Article Synopsis
- * A comprehensive search of studies from PUBMED, EMBASE, and MEDLINE from 2010 to 2023 identified 5 significant randomized controlled trials.
- * Plasmalyte closely mimics human plasma and helps prevent complications like hyperchloremic metabolic acidosis, but findings on its impact on hospital stay, recovery time, and mortality vary, indicating the need for more research.