PURPOSE: To examine whether there is a significant difference in image quality between the deep learning reconstruction (DLR [AiCE, Advanced Intelligent Clear-IQ Engine]) and hybrid iterative reconstruction (HIR [AIDR 3D, adaptive iterative dose redu...
Breast cancer is the most commonly diagnosed cancer among women worldwide. Breast cancer patients experience significant distress relating to their diagnosis and treatment. Managing this distress is critical for improving the lifespan and quality of ...
The tumor microenvironment (TME) plays a fundamental role in tumorigenesis, tumor progression, and anti-cancer immunity potential of emerging cancer therapeutics. Understanding inter-patient TME heterogeneity, however, remains a challenge to efficien...
AIMS: To examine whether natural language processing (NLP) using a clinically based large language model (LLM) could be used to predict patient selection for total hip or total knee arthroplasty (THA/TKA) from routinely available free-text radiology ...
. This study examines the value of ventricular repolarization using QT dynamicity for two different types of atrial fibrillation (AF) prediction.. We studied the importance of QT-dynamicity (1) in the detection and (2) the onset prediction (i.e. fore...
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Jul 1, 2024
Transthyretin cardiac amyloidosis (ATTR CA) is increasingly recognized as a cause of heart failure in older patients, with Tc-pyrophosphate imaging frequently used to establish the diagnosis. Visual interpretation of SPECT images is the gold standard...
Fairness (also known as equity interchangeably) in machine learning is important for societal well-being, but limited public datasets hinder its progress. Currently, no dedicated public medical datasets with imaging data for fairness learning are ava...
BACKGROUND AND AIM: Acute pancreatitis (AP) is potentially fatal. Therefore, early identification of patients at a high mortality risk and timely intervention are essential. This study aimed to establish an explainable machine-learning model for pred...
BACKGROUND: Gastrointestinal stromal tumors (GISTs) and leiomyomas are the most common submucosal tumors of the upper digestive tract, and the diagnosis of the tumors is essential for their treatment and prognosis. However, the ability of endoscopic ...
International journal of medical informatics
Jun 30, 2024
OBJECTIVES: This study aims to evaluate the fairness performance metrics of Machine Learning (ML) models to predict hospitalization and emergency department (ED) visits in heart failure patients receiving home healthcare. We analyze biases, assess pe...
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