AIMC Topic: Neuroendocrine Tumors
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Automated AI-based grading of neuroendocrine tumors using Ki-67 proliferation index: comparative evaluation and performance analysis.
Medical & biological engineering & computing
Feb 27, 2024
Early detection is critical for successfully diagnosing cancer, and timely analysis of diagnostic tests is increasingly important. In the context of neuroendocrine tumors, the Ki-67 proliferation index serves as a fundamental biomarker, aiding pathol...
Robotic pancreatic tumor enucleation by the double bipolar technique using the da Vinci SP system: An initial case report with a technical detail.
Asian journal of endoscopic surgery
Dec 11, 2023
Pancreatic tumor enucleation is a procedure that can preserve pancreatic function and is sometimes performed using a minimally invasive approach. Recently, a single-port robotic platform called da Vinci SP has been developed. However, the technical d...
Machine Learning Methods Based on CT Features Differentiate G1/G2 From G3 Pancreatic Neuroendocrine Tumors.
Academic radiology
Dec 4, 2023
RATIONALE AND OBJECTIVES: To identify CT features for distinguishing grade 1 (G1)/grade 2 (G2) from grade 3 (G3) pancreatic neuroendocrine tumors (PNETs) using different machine learning (ML) methods.
Algorithms
Retrospective Studies
Tomography, X-Ray Computed
Humans
Machine Learning
Neuroendocrine Tumors
Middle Aged
Support Vector Machine
Diagnosis, Differential
Female
Adult
Pancreatic Neoplasms
Aged
Sensitivity and Specificity
Neoplasm Grading
Male
Radiographic Image Interpretation, Computer-Assisted
The use of deep learning models to predict progression-free survival in patients with neuroendocrine tumors.
Future oncology (London, England)
Jul 27, 2023
The RAISE project assessed whether deep learning could improve early progression-free survival (PFS) prediction in patients with neuroendocrine tumors. Deep learning models extracted features from CT scans from patients in CLARINET (NCT00353496) (n...
Predicting the survival of patients with pancreatic neuroendocrine neoplasms using deep learning: A study based on Surveillance, Epidemiology, and End Results database.
Cancer medicine
May 11, 2023
BACKGROUND: The study aims to evaluate the performance of three advanced machine learning algorithms and a traditional Cox proportional hazard (CoxPH) model in predicting the overall survival (OS) of patients with pancreatic neuroendocrine neoplasms ...
Implementation of robot-assisted curative resection for rare anorectal tumours on the basis of individualised treatment.
The international journal of medical robotics + computer assisted surgery : MRCAS
Nov 14, 2021
PURPOSE: To evaluate the validity of robot-assisted curative operation for rare anorectal tumours, characterised by biological heterogeneity and anatomical complexity.
Exploration of machine learning techniques to examine the journey to neuroendocrine tumor diagnosis with real-world data.
Future oncology (London, England)
May 19, 2021
Machine learning reveals pathways to neuroendocrine tumor (NET) diagnosis. Patients with NET and age-/gender-matched non-NET controls were retrospectively selected from MarketScan claims. Predictors (e.g., procedures, symptoms, conditions for which...
Imaging and liquid biopsy in the prediction and evaluation of response to PRRT in neuroendocrine tumors: implications for patient management.
European journal of nuclear medicine and molecular imaging
Apr 26, 2021
PURPOSE: The aim of this narrative review is to give an overview on current and emerging imaging methods and liquid biopsy for prediction and evaluation of response to PRRT. Current limitations and new perspectives, including artificial intelligence,...
Improving the accuracy of gastrointestinal neuroendocrine tumor grading with deep learning.
Scientific reports
Jul 6, 2020
The Ki-67 index is an established prognostic factor in gastrointestinal neuroendocrine tumors (GI-NETs) and defines tumor grade. It is currently estimated by microscopically examining tumor tissue single-immunostained (SS) for Ki-67 and counting the ...
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