Abstract Library

#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,

#4550 The relationship between MEN1 germline mutations and SSTR2 expression in neuroendocrine tumours

Introduction: Multiple endocrine neoplasia type 1 (MEN1) is a rare hereditary disease characterised by the development of multiglandular parathyroid disease, pituitary tumours, and duodenopancreatic neuroendocrine tumours (NETs). Germline mutations in the tumour suppressor gene MEN1 are the underlying cause. Somatostatin receptor 2 (SSTR2) is commonly expressed by NETs. However, the expression of SSTR2 in patients with MEN1 remains unclear.

Conference:

Presenting Author: Chi Y

Authors: Sun Y, Tan H, Wang H, Shi S, Dong L,

Keywords: multiple endocrine neoplasia type 1, somatostatin receptor 2, neuroendocrine tumour,

#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,

#4509 Epidemiological characteristics and prognosis analysis of gastric cancer (GC) with neuroendocrine differentiation (NED)

Introduction: GC with NED exhibits distinct biological characteristics, yet research on its clinical features and prognosis remains limited.

Conference:

Presenting Author: Zhang J

Authors: Huang Z, Li J, Wang C, Shen Y, Rao S,

Keywords: gastric cancer, neuroendocrine differentiation, Epidemiological characteristics, prognosis,

#4501 Efficacy and safety of surufatinib in unresectable or metastatic grade 3 neuroendocrine tumours (NET G3): A national multi-centre, retrospective study

Introduction: Currently, there are limited treatment options for NET G3 and therapeutics for NET G1/2 may be considered as alternatives.

Conference:

Presenting Author: Hao J

Authors: Wang J, Zhang N, Liang Y, Long J, Chi Y,

Keywords: surufatinib, NET G3,