Publications by authors named "G Soon"
Comparing Raman Spectroscopy-Based Artificial Intelligence to High-Definition White Light Endoscopy for Endoscopic Diagnosis of Gastric Neoplasia: A Feasibility Proof-of-Concept Study.
Diagnostics (Basel)
December 2024
Background: Endoscopic assessment for the diagnosis of gastric cancer is limited by interoperator variability and lack of real-time capability. Recently, Raman spectroscopy-based artificial intelligence (AI) has been proposed as a solution to overcome these limitations.
Objective: To compare the performance of the AI-enabled Raman spectroscopy with that of high-definition white light endoscopy (HD-WLE) for the risk classification of gastric lesions.
Background: Major society guidelines recommend transarterial chemoembolization (TACE) as the standard of care for intermediate-stage hepatocellular carcinoma (HCC) patients. However, predicting treatment response remains challenging.
Aims: As artificial intelligence (AI) may predict therapeutic responses, this systematic review aims to assess the performance and effectiveness of radiomics and AI-based models in predicting TACE outcomes in patients with HCC.
Article Synopsis
- Intra and inter-pathologist variability complicates the evaluation of metabolic dysfunction-associated steatohepatitis (MASH) biopsy results, hindering patient selection and assessment quality in clinical trials.
- A study analyzed 120 histology slides with and without AI assistance to evaluate its impact on pathologists' reliability in fibrosis staging, especially for early fibrosis stages.
- Results showed that AI assistance significantly improved concordance among pathologists, increasing agreement rates for clinical trial inclusion and exclusion, which could enhance the overall efficiency and reliability of MASH-related clinical research.
Background & Aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a spectrum of pathologies ranging from simple steatosis to steatohepatitis, fibrosis and cirrhosis. Patients with metabolic associated steatohepatitis (MASH) with fibrosis are at greatest risk of liver and cardiovascular complications. To identify such at-risk MASLD patients, physicians are still reliant on invasive liver biopsies.
View Article and Find Full Text PDFBackground: Hepatocellular carcinoma (HCC) is a deadly cancer with a high global mortality rate, and the downregulation of GATA binding protein 4 (GATA4) has been implicated in HCC progression. In this study, we investigated the role of GATA4 in shaping the immune landscape of HCC.
Methods: HCC tumor samples were classified into "low" or "normal/high" based on GATA4 RNA expression relative to adjacent non-tumor liver tissues.