Latest AI and machine learning research in nuclear medicine for healthcare professionals.
The purpose of this paper is to provide an overview of the cutting-edge applications of artificial i...
BACKGROUND: Fluorodeoxyglucose positron emission tomography (FDG PET) with suppression of myocardial...
Medical image classification using convolutional neural networks (CNNs) is promising but often requi...
PURPOSE: This study aimed to investigate a deep learning model to classify amyloid plaque deposition...
The standard method for identifying active Brown Adipose Tissue (BAT) is [F]-Fluorodeoxyglucose ([F]...
This review explores the potential applications of Large Language Models (LLMs) in nuclear medicine,...
We develop a machine learning (ML) model using electrocardiography (ECG) to predict myocardial blood...
BACKGROUND: Natural language processing (NLP) techniques can be used to analyze large amounts of ele...
PURPOSE: The objective of this study is to assess the prognostic efficacy of F-fluorodeoxyglucose (F...
This pioneering work explores the immense potential of young coconut waste, a continuously marginali...
. Approximately 57% of non-small cell lung cancer (NSCLC) patients face a 20% risk of brain metastas...
This systematic review aimed to evaluate the potential of deep learning algorithms for converting lo...
OBJECTIVES: To develop and identify machine learning (ML) models using pretreatment 2-deoxy-2-[F]flu...
Groundnut oil is known as a good source of essential fatty acids which are significant in the physio...
BACKGROUND: To evaluate the clinical performance of two deep learning methods, one utilizing real cl...
RATIONALE AND OBJECTIVE: To compare the performance of large language model (LLM) based Gemini and G...
BACKGROUND: Deep learning is the primary method for conducting automated analysis of SPECT bone scin...
The current study aimed to predict lymphovascular invasion (LVI) using multiple machine learning alg...
PURPOSE: This study demonstrates the feasibility and benefits of using a deep learning-based approac...
Alzheimer disease (AD) exhibits spatially heterogeneous 3- or 4-repeat tau deposition across partici...
We propose strongly unrealistic data augmentation to improve the robustness of convolutional neural ...