Hsiang‐Ting Chen

ORCID: 0000-0003-0873-2698 · 6 papers in corpus
article 2026
An online cross-section survey exploring the training needs of healthcare professionals learning to perform transvaginal ultrasound for endometriosis: Does artificial intelligence have a role to play?
·doi:10.1016/j.jeud.2026.100174

Background Rapid advances in transvaginal ultrasound techniques to detect endometriosis (eTVUS) require navigation of a steep learning curve. Artificial intelligence (AI) is playing an ever-increasing role in ultrasound and holds potential …

conference-paper 2026
EndoExtract: Co-Designing Structured Text Extraction from Endometriosis Ultrasound Reports
·doi:10.1145/3786579.3804934
article 2026
Evaluating local large language models for structured extraction from endometriosis-specific transvaginal ultrasound reports

In this study, we evaluate a locally-deployed large-language model (LLM) to convert unstructured endometriosis transvaginal ultrasound (eTVUS) scan reports into structured data for imaging informatics workflows. Across 49 eTVUS reports, we …

preprint 2026
Who Fails Where? LLM and Human Error Patterns in Endometriosis Ultrasound Report Extraction
·doi:10.48550/arxiv.2601.09053

In this study, we evaluate a locally-deployed large-language model (LLM) to convert unstructured endometriosis transvaginal ultrasound (eTVUS) scan reports into structured data for imaging informatics workflows. Across 49 eTVUS reports, we …

article 2026
Who Fails Where? LLM and Human Error Patterns in Endometriosis Ultrasound Report Extraction
·doi:10.1145/3772363.3798872

In this study, we evaluate locally deployed large language models (LLMs) for converting unstructured endometriosis transvaginal ultrasound (eTVUS) reports into structured data. Across 49 de-identified reports, we compared three on-premise L…

review 2023
Noninvasive diagnostic imaging for endometriosis part 2: a systematic review of recent developments in magnetic resonance imaging, nuclear medicine and computed tomography
Fertility and sterility ·doi:10.1016/j.fertnstert.2023.12.017

Endometriosis affects 1 in 9 women, taking 6.4 years to diagnose using conventional laparoscopy. Non-invasive imaging enables timelier diagnosis, reducing diagnostic delay, risk and expense of surgery. This review updates literature explori…