Publications by authors named "H K Goh"
This research presents the design and analysis of a compact metamaterial (MTM)-based star-shaped split-ring resonator (SRR) enclosed in a square, constructed on a cost-effective substrate for liquid chemical sensing applications. The designed structure has dimensions of 10 × 10 mm and is optimized for detecting adulteration in edible oils. When the sample holder is filled with different percentages of oil samples, the resonance frequency of the MTM-based SRR sensor shift significantly.
View Article and Find Full Text PDFBackground: Identifying patients with gm is crucial to facilitate screening strategies, preventive measures and the usage of targeted therapeutics in their management. This review examines the evidence for the latest predictive and therapeutic approaches in -associated cancers.
Clinical Description: Data supports the use of adjuvant olaparib in patients with gm high-risk HER2-negative breast cancer.
In this study, we present a groundbreaking approach utilizing metal-free, visible light-mediated organic photoredox catalyzed atom transfer radical polymerization (O-ATRP) to synthesize cellulose-based stimuli-responsive polymers. Our method resulted in the successful synthesis of innovative metal-free poly(N-tertiary-butylacrylamide)-graft-hydroxypropyl cellulose (PNTBAM-g-HPC) polymers with exceptional control over molecular weight and narrow dispersity index (Đ) and explored their applications in organo-photocatalytic reactions. This approach addresses the limitations of traditional atom transfer radical polymerization method, which suffer from metal contamination and toxicity related problems.
View Article and Find Full Text PDFImportance: This diagnostic study describes the merger of domain knowledge (Kramer principle of dermal advancement of icterus) with current machine learning (ML) techniques to create a novel tool for screening of neonatal jaundice (NNJ), which affects 60% of term and 80% of preterm infants.
Objective: This study aimed to develop and validate a smartphone-based ML app to predict bilirubin (SpB) levels in multiethnic neonates using skin color analysis.
Design, Setting, And Participants: This diagnostic study was conducted between June 2022 and June 2024 at a tertiary hospital and 4 primary-care clinics in Singapore with a consecutive sample of neonates born at 35 or more weeks' gestation and within 21 days of birth.
Article Synopsis
- The study aimed to improve pain management by predicting which women undergoing cesarean delivery would experience significant postoperative pain after receiving spinal morphine, highlighting the issue of fragmented clinical information.
- Researchers analyzed medical records from 6561 patients, using 120 clinical variables to train various predictive models, ultimately identifying the Ridge regression model as the most effective in forecasting patient pain levels.
- Results indicated a 7.9% incidence of significant pain, with Ridge regression achieving the highest accuracy (AUC of 0.719) when using a selected set of clinical features, particularly focusing on previous pain scores and maximum pain levels in the initial hours post-surgery.