Abstract Library

Welcome to the open-access search for all ENETS abstracts presented at the Annual ENETS Conferences.

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Participants of the 2025 ENETS Conference enjoy full access to the 2025 conference digital resources through myENETS: the abstract booklet, e-posters and videos, slide decks of talks, the poster carousel, and more.

ENETS Abstract Search

#4580 Improving diagnosis of neuroendocrine tumours using large language models

Introduction: Neuroendocrine tumours (NETs) are a heterogeneous group of cancers that can be difficult to diagnose due to their variable clinical presentation and non-specific symptoms. Accurate diagnosis often requires integrating a wide range of clinical, radiological, and pathological information. Large language models (LLMs) have shown promise in processing and understanding complex medical text, making them a valuable tool for improving diagnostic accuracy in oncology.

Conference:

Presenting Author:

Authors: Tang Z, Chen P, Tang J, Li H, Chen Y,

Keywords: Neuroendocrine Tumour (NET), Large Language Model (LLM), Medical Natural Language Processing (NLP), Clinical Decision Support,

#4522 Leveraging large language models for enhanced diagnosis of neuroendocrine tumours

Introduction: Neuroendocrine tumours (NETs) are a heterogeneous group of cancers that are difficult to diagnose due to their variable clinical presentation and non-specific symptoms. Accurate diagnosis often requires integrating a wide range of clinical, radiological, and pathological information. However, clinicians may struggle to synthesise these diverse data sources effectively. Large language models (LLMs) have shown promise in processing and understanding complex medical text, making them a valuable tool for improving diagnostic accuracy in oncology.

Conference:

Presenting Author:

Authors: Tang Z, Tang J, Cheng F, Li H, Chen Y,

Keywords: Neuroendocrine Tumour (NET), Large Language Model (LLM), Medical Natural Language Processing (NLP), Clinical Decision Support,