Abstract Library

#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,

#4462 Clustering of gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN) using machine learning (ML) and comparison with tumour, node, metastasis (TNM) staging: A population-based study using surveillance, epidemiology, and end results (SEER)

Introduction: TNM 8 is the staging system for GEP-NEN, guiding prognosis and treatment. However, it does not include important prognostic factors such as age, sex, race, and morphology.

Conference:

Presenting Author: Mortagy M

Authors: Mortagy M, El Asmar M, White B, Chandrakumaran K, Ramage J,

Keywords: Clustering, Machine learning, GEP-NEN, TNM Staging, Survival Analysis, SEER,

#4458 Survival and optimal follow-up cut-off of lung neuroendocrine tumours after surgery: Experience of a high-volume centre over 25 years

Introduction: Surgery is the curative therapy for lung neuroendocrine tumours (NET). Follow-up protocols after surgery are not evidence based and factors affecting survival are not clear.

Conference:

Presenting Author: Mortagy M

Authors: Mortagy M, El Asmar M, Nonaka D, Dolly S, Srirajaskanthan R,

Keywords: Lung NET, Lung NET Surgery, Follow-up after surgery,

#4403 Ki-67 index cut-off values and survival prognostication in neuroendocrine neoplasms: Machine learning-based insights

Introduction: The current grading system for gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN) is based on Ki-67 index and/or mitotic rate. By definition, high-grade NEN (neuroendocrine tumour grade 3 [NET G3] and neuroendocrine carcinoma [NEC]) have a Ki-67 >20%, while NET G1 have a Ki-67

Conference:

Presenting Author:

Authors: Melhorn P, Berchtold L, Mazal P, Raderer M, Kiesewetter B,

Keywords: neuroendocrine neoplasm, prognosis, ki-67 index,

#4076 Machine learning model: Predicting prognosis in neuroendocrine tumors

Introduction: Neuroendocrine tumors (NETs) have a heterogeneous clinical course. Even with similar Ki-67 proliferative index/morphology, the course varies in patients with similar pathological characterization.

Conference:

Presenting Author:

Authors: Varghese D, Naimian A, Yazdian P, Lokre O, Perk T,

Keywords: Neuroendocrine tumor, artificial intelligence, DOTATATE scan,