Sheng Wong

According to our database, Sheng Wong authored at least 12 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

PRISM-CTG: A Foundation Model for Cardiotocography Analysis with Multi-View SSL.

Sheng Wong, Ravi Shankar, Beth Albert, Hao Fei, Lin Li, Imane Ben M'Barek, Manu Vatish, Gabriel Davis Jones

CoRR, May, 2026

Evaluating the Presence of Sex Bias in Clinical Reasoning by Large Language Models.

Isabel Tsintsiper, Sheng Wong, Beth Albert, Shaun P. Brennecke, Gabriel Davis Jones

CoRR, February, 2026

CleanCTG: A deep learning model for multi-artefact detection and reconstruction in Cardiotocography.

Sheng Wong, Beth Albert, Manu Vatish, Gabriel Davis Jones

Biomed. Signal Process. Control., 2026

2025

Large language models surpass domain-specific architectures for antepartum electronic fetal monitoring analysis.

Sheng Wong, Ravi Shankar, Beth Albert, Gabriel Davis Jones

CoRR, September, 2025

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare.

Ravi Shankar, Sheng Wong, Lin Li, Magdalena Bachmann, Alex Silverthorne, Beth Albert, Gabriel Davis Jones

CoRR, September, 2025

CleanCTG: A Deep Learning Model for Multi-Artefact Detection and Reconstruction in Cardiotocography.

Sheng Wong, Beth Albert, Gabriel Davis Jones

CoRR, August, 2025

Channel-annotated deep learning for enhanced interpretability in EEG-based seizure detection.

Sheng Wong, Anj Simmons, Jessica Rivera-Villicana, Scott Barnett, Shobi Sivathamboo, Piero Perucca, Zongyuan Ge, Patrick Kwan, Levin Kuhlmann, Terence J. O'Brien

Biomed. Signal Process. Control., 2025

2024

Fine-Tuning or Fine-Failing? Debunking Performance Myths in Large Language Models.

Scott Barnett, Zach Brannelly, Stefanus Kurniawan, Sheng Wong

CoRR, 2024

A Novel Vision-Based Transformer for Seizure Detection with Multi-biosignals.

Sheng Wong, Scott Barnett, Shobi Sivathamboo, Piero Perucca, Zongyuan Ge, Patrick Kwan, Levin Kuhlmann, Terence J. O'Brien

Proceedings of the Data Science and Machine Learning, 2024

2023

Estimating Patient-Level Uncertainty in Seizure Detection Using Group-Specific Out-of-Distribution Detection Technique.

Sheng Wong, Anj Simmons, Jessica Rivera-Villicana, Scott Barnett

Sensors, October, 2023

MLGuard: Defend Your Machine Learning Model!

Sheng Wong, Scott Barnett, Jessica Rivera-Villicana, Anj Simmons, Hala Abdelkader, Jean-Guy Schneider, Rajesh Vasa

Proceedings of the 1st International Workshop on Dependability and Trustworthiness of Safety-Critical Systems with Machine Learned Components, 2023

2020

Computationally Efficient Epileptic Seizure Prediction based on Extremely Randomised Trees.

Sheng Wong, Levin Kuhlmann

Proceedings of the Australasian Computer Science Week, 2020