Dataset Information

Breast Cancer Subtype Prediction Model Employing Artificial Neural Network and ¹⁸F-Fluorodeoxyglucose Positron Emission Tomography/ Computed Tomography.

ABSTRACT:

Introduction

Although positron emission tomography/computed tomography (PET/CT) is a common tool for measuring breast cancer (BC), subtypes are not automatically classified by it. Therefore, the purpose of this research is to use an artificial neural network (ANN) to evaluate the clinical subtypes of BC based on the value of the tumor marker.

Materials and methods

In our nuclear medical facility, 122 BC patients (training and testing) had ¹⁸F-fluoro-D-glucose (¹⁸F-FDG) PET/CT to identify the various subtypes of the disease. ¹⁸F-FDG-18 injections were administered to the patients before the scanning process. We carried out the scan according to protocol. Based on the tumor marker value, the ANN's output layer uses the Softmax function with cro

SUBMITTER: Hossain A

PROVIDER: S-EPMC11309150 | biostudies-literature | 2024 Apr-Jun

REPOSITORIES: biostudies-literature

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Dataset Information

Breast Cancer Subtype Prediction Model Employing Artificial Neural Network and ¹⁸F-Fluorodeoxyglucose Positron Emission Tomography/ Computed Tomography.

Introduction

Materials and methods

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Breast Cancer Subtype Prediction Model Employing Artificial Neural Network and 18F-Fluorodeoxyglucose Positron Emission Tomography/ Computed Tomography.

Introduction

Materials and methods

OmicsDI is part of the ELIXIR infrastructure

Tweets

Breast Cancer Subtype Prediction Model Employing Artificial Neural Network and ¹⁸F-Fluorodeoxyglucose Positron Emission Tomography/ Computed Tomography.