AIMC Topic: Radiologists

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Current Radiology workforce perspective on the integration of artificial intelligence in clinical practice: A systematic review.

Journal of medical imaging and radiation sciences
INTRODUCTION: Artificial Intelligence (AI) represents the application of computer systems to tasks traditionally performed by humans. The medical imaging profession has experienced a transformative shift through the integration of AI. While there hav...

Enhancing Radiologists' Performance in Detecting Cerebral Aneurysms Using a Deep Learning Model: A Multicenter Study.

Academic radiology
RATIONALE AND OBJECTIVES: This study aimed to develop a deep learning (DL)-based model for detecting and diagnosing cerebral aneurysms in clinical settings, with and without human assistance.

Using Machine Learning on MRI Radiomics to Diagnose Parotid Tumours Before Comparing Performance with Radiologists: A Pilot Study.

Journal of imaging informatics in medicine
The parotid glands are the largest of the major salivary glands. They can harbour both benign and malignant tumours. Preoperative work-up relies on MR images and fine needle aspiration biopsy, but these diagnostic tools have low sensitivity and speci...

Clinical Impact of Radiologist's Alert System on Patient Care for High-risk Incidental CT Findings: A Machine Learning-Based Risk Factor Analysis.

Academic radiology
RATIONALE AND OBJECTIVES: Efficient communication between radiologists and clinicians ordering computed tomography (CT) examinations is crucial for managing high-risk incidental CT findings (ICTFs). Herein, we introduced a Radiologist's Alert and Pat...

Impact of artificial intelligence assistance on pulmonary nodule detection and localization in chest CT: a comparative study among radiologists of varying experience levels.

Scientific reports
The study aimed to evaluate the impact of AI assistance on pulmonary nodule detection rates among radiology residents and senior radiologists, along with assessing the effectiveness of two different commercialy available AI software systems in improv...

The legal regulation of artificial intelligence in the European Union: A practical guide for radiologists.

Radiologia
The European Union is taking the lead globally on the regulation of Artificial Intelligence (AI) and developing important legislation, namely the AI Act. The purpose of this article is to describe this regulation and examine three implications that w...

Evolution of radiology staff perspectives during artificial intelligence (AI) implementation for expedited lung cancer triage.

Clinical radiology
AIMS: To investigate radiology staff perceptions of an AI tool for chest radiography triage, flagging findings suspicious for lung cancer to expedite same-day CT chest examination studies.

AI-based lumbar central canal stenosis classification on sagittal MR images is comparable to experienced radiologists using axial images.

European radiology
OBJECTIVES: The assessment of lumbar central canal stenosis (LCCS) is crucial for diagnosing and planning treatment for patients with low back pain and neurogenic pain. However, manual assessment methods are time-consuming, variable, and require axia...

Comparison between artificial intelligence solution and radiologist for the detection of pelvic, hip and extremity fractures on radiographs in adult using CT as standard of reference.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to compare the diagnostic performance of an artificial intelligence (AI) solution for the detection of fractures of pelvic, proximal femur or extremity fractures in adults with radiologist interpretation of radi...