AI Medical Compendium Journal:
Radiography (London, England : 1995)

Showing 31 to 40 of 53 articles

The ethical matrix as a method for involving people living with disease and the wider public (PPI) in near-term artificial intelligence research.

Radiography (London, England : 1995)
INTRODUCTION: The rapid pace of research in the field of Artificial Intelligence in medicine has associated risks for near-term AI. Ethical considerations of the use of AI in medicine remain a subject of much debate. Concurrently, the Involvement of ...

Artificial intelligence-supported applications in head and neck cancer radiotherapy treatment planning and dose optimisation.

Radiography (London, England : 1995)
INTRODUCTION: The aim of this review is to describe how various AI-supported applications are used in head and neck cancer radiotherapy treatment planning, and the impact on dose management in regards to target volume and nearby organs at risk (OARs)...

Strong semantic segmentation for Covid-19 detection: Evaluating the use of deep learning models as a performant tool in radiography.

Radiography (London, England : 1995)
INTRODUCTION: With the increasing number of Covid-19 cases as well as care costs, chest diseases have gained increasing interest in several communities, particularly in medical and computer vision. Clinical and analytical exams are widely recognized ...

The effect of Gaussian noise on pneumonia detection on chest radiographs, using convolutional neural networks.

Radiography (London, England : 1995)
INTRODUCTION: Chest X-rays (CXR) with under-exposure increase image noise and this may affect convolutional neural network (CNN) performance. This study aimed to train and validate CNNs for classifying pneumonia on CXR as normal or pneumonia acquired...

Digital skills of therapeutic radiographers/radiation therapists - Document analysis for a European educational curriculum.

Radiography (London, England : 1995)
INTRODUCTION: It is estimated that around 50% of cancer patients require Radiotherapy (RT) at some point during their treatment, hence Therapeutic Radiographers/Radiation Therapists (TR/RTTs) have a key role to play in patient management. It is essen...

Radiographers' knowledge, attitudes and expectations of artificial intelligence in medical imaging.

Radiography (London, England : 1995)
INTRODUCTION: Artificial intelligence (AI) is increasingly utilised in medical imaging systems and processes, and radiographers must embrace this advancement. This study aimed to investigate perceptions, knowledge, and expectations towards integratin...

Development of lumbar spine MRI referrals vetting models using machine learning and deep learning algorithms: Comparison models vs healthcare professionals.

Radiography (London, England : 1995)
INTRODUCTION: Referrals vetting is a necessary daily task to ensure the appropriateness of radiology referrals. Vetting requires extensive clinical knowledge and may challenge those responsible. This study aims to develop AI models to automate the ve...

Automated detection of COVID-19 cases from chest X-ray images using deep neural network and XGBoost.

Radiography (London, England : 1995)
INTRODUCTION: In late 2019 and after the COVID-19 pandemic in the world, many researchers and scholars tried to provide methods for detecting COVID-19 cases. Accordingly, this study focused on identifying patients with COVID-19 from chest X-ray image...

Detection of metallic objects on digital radiographs with convolutional neural networks: A MRI screening tool.

Radiography (London, England : 1995)
INTRODUCTION: Screening for metallic implants and foreign bodies before magnetic resonance imaging (MRI) examinations, are crucial for patient safety. History of health are supplied by the patient, a family member, screening of electronic health reco...

A muggles guide to deep learning wizardry.

Radiography (London, England : 1995)
OBJECTIVES: Growing interest in the applications of artificial intelligence (AI) and, in particular, deep learning (DL) in nuclear medicine and radiology partitions the professional community. At one end of the spectrum are our expert DL wizards deve...