Abstract Library

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

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ENETS Abstract Search

#4600 Artificial intelligence in predicting neuroendocrine tumour (NET) outcomes: A model-based prognostic approach

Introduction: Neuroendocrine tumours (NETs) vary widely in clinical behaviour, complicating prognosis. Traditional models often struggle with accuracy due to the complexity of NETs. Artificial intelligence (AI) offers tools for enhanced prognostic precision by analysing complex datasets. This study explores an AI-driven approach to predict outcomes in NET patients at Cantonment General Hospital, Pakistan.

Conference:

Presenting Author: Fatima A

Authors: Fatima A,

Keywords: artificial intelligence, machine learning, Precision medicine, Personalised treatment,

#4578 Dissecting the role of collagen quantitation via tissue-tethered digital analysis in small bowel neuroendocrine tumours and related mesenteric tumour deposits

Introduction: Small bowel neuroendocrine tumours (sb-NETs) and related mesenteric tumour deposits (MTDs) can present dense collagen and fibrosis. Despite well-known clinical consequences of this characteristic (bowel obstruction and ischemia), the relationship between SB-NETs and MTDs collagen deposition has been poorly evaluated.

Conference:

Presenting Author: Ali M

Authors: Ali M, Gambella A, Checchin F, Malerba D, Sambuceti V,

Keywords: neuroendocrine tumour, small intestine, collagen, fibrosis,

#4554 Base on deep learning-integrated multimodal diagnostic framework for enhanced early detection of neuroendocrine tumours

Introduction: Neuroendocrine tumours (NETs) are a heterogeneous group of malignant neoplasms originating from neuroendocrine cells, commonly found in the digestive system, lungs, pancreas, and other organs. Due to their diverse clinical presentations and overlap with common diseases, the early diagnosis of NETs is challenging, often leading to misdiagnosis or delayed diagnosis at advanced stages.

Conference:

Presenting Author:

Authors: Ding Z, Li H, Tang Z, Chen Y, Li H,

Keywords: Neuroendocrine Tumour, Early Disease Screening, Multimodal Medical Data Analysis,

#4542 Results of active observation of pancreatic non-functioning neuroendocrine tumours – Medical registry data

Introduction: Algorithm for stage T1 pancreatic neuroendocrine tumours (PNETs) treatment requires clarification.

Conference:

Presenting Author:

Authors: Salimgereeva D, Feidorov I, Konyakhina A, Petrova A,

Keywords: Neuroendocrine tumour, PNET, pancreatic NET, management, active observation, follow-up, registry, CHEK2, oestrogen,

#4512 A deep learning-integrated multimodal diagnostic framework for enhanced early detection of neuroendocrine tumours

Introduction: Neuroendocrine tumours (NETs) are a heterogeneous group of malignant neoplasms originating from neuroendocrine cells, commonly found in the digestive system, lungs, pancreas, and other organs. Due to their diverse clinical presentations and overlap with common diseases, the early diagnosis of NETs is challenging, often leading to misdiagnosis or delayed diagnosis at advanced stages. While current imaging techniques and biomarkers are useful in certain cases, their diagnostic sensitivity and specificity remain limited when used in isolation.

Conference:

Presenting Author:

Authors: Ding Z, Li H, Tang Z, Chen Y, Li H,

Keywords: Neuroendocrine Tumour, Multimodal Diagnostic algorithm, Deep Learning, Early Disease Screening,