Search Tag: Radiology AI
2025 02 May
People are far more accepting of AI being used in the NHS when they are familiar with AI in general, showing the need for greater public engagement, according to a survey of public attitudes to AI in healthcare conducted by J.L. Partners on behalf of the Royal College of Radiologists (RCR). The findings reveal broad recognition of AI's potential...Read more
2025 24 Apr
Accurate and timely interpretation of radiology reports is critical for monitoring cancer progression and informing treatment decisions. However, the free-text nature and variability of these reports often pose challenges for oncologists, especially when dealing with large volumes of patient data. Recent advancements in artificial intelligence,...Read more
2025 24 Apr
Accurate and timely interpretation of radiology reports is critical for monitoring cancer progression and informing treatment decisions. However, the free-text nature and variability of these reports often pose challenges for oncologists, especially when dealing with large volumes of patient data. Recent advancements in artificial intelligence,...Read more
2025 17 Apr
Retrieving structured information from radiology reports remains a major challenge within clinical and research settings. Traditional keyword-based systems, despite widespread use, often fail to capture the underlying clinical meaning due to their reliance on superficial lexical matches. These limitations affect radiologists attempting to locate...Read more
2025 17 Apr
Artificial Intelligence has emerged as a promising support tool for fracture diagnosis in clinical radiology, aiming to address persistent issues such as missed fractures and diagnostic variability among readers. While various AI tools have demonstrated strong technical performance, questions remain regarding how best to integrate them into clinical...Read more
2025 17 Apr
Artificial Intelligence has emerged as a promising support tool for fracture diagnosis in clinical radiology, aiming to address persistent issues such as missed fractures and diagnostic variability among readers. While various AI tools have demonstrated strong technical performance, questions remain regarding how best to integrate them into clinical...Read more
2025 25 Mar
Artificial intelligence has increasingly become integral to radiology, offering new methods to enhance diagnostic accuracy and efficiency. Among the latest advancements, DeepSeek stands out as a disruptive force. Developed by a Chinese AI startup, it introduces open-weight models designed to optimise computational efficiency and problem-solving....Read more
2025 25 Mar
The increasing volume of chest radiographs presents significant challenges for radiologists, impacting timely diagnosis and workflow efficiency. Traditional methods, while accurate, are often time-consuming and may lead to delays in patient care. The reliance on radiologists for manual interpretation can create bottlenecks in healthcare systems,...Read more
2025 10 Mar
The integration of three-dimensional cinematic reconstructions with augmented reality (AR) has introduced new possibilities for cardiovascular imaging. By enabling interaction with holographic models of computed tomography (CT) datasets, AR enhances anatomical comprehension and offers novel applications in both educational and clinical settings....Read more
2025 08 Feb
The increasing workload of radiologists has significantly contributed to a rise in reporting errors, posing risks to patient care and diagnostic accuracy. The process of generating radiology reports consists of detecting abnormalities in images and documenting these findings accurately. Errors can occur at both stages, with some resulting from misinterpretations...Read more
2025 08 Feb
The increasing workload of radiologists has significantly contributed to a rise in reporting errors, posing risks to patient care and diagnostic accuracy. The process of generating radiology reports consists of detecting abnormalities in images and documenting these findings accurately. Errors can occur at both stages, with some resulting from misinterpretations...Read more
2025 04 Feb
The rapid advancement of large language models (LLMs) has led to increasing interest in their application within medical diagnostics. While traditional text-based models have demonstrated potential in clinical decision-making, newer multimodal models such as OpenAI’s GPT-4 with vision (GPT-4V) introduce the capability to process both textual and...Read more
2025 02 Feb
Artificial intelligence is increasingly integrated into medical imaging, particularly in the field of neurology, where it has shown potential in the diagnosis and monitoring of multiple sclerosis (MS). With MRI serving as the primary tool for assessing disease activity, AI-based software solutions are designed to assist radiologists in detecting...Read more
2024 31 Jul
Integrating artificial intelligence (AI) in medical diagnostics, particularly in radiology, promises to revolutionise clinical decision-making. However, the pace at which AI technologies are being developed and commercialised significantly outstrips our understanding of their practical value for clinicians. This rapid development has created an...Read more
2024 31 Jul
Integrating artificial intelligence (AI) in medical diagnostics, particularly in radiology, promises to revolutionise clinical decision-making. However, the pace at which AI technologies are being developed and commercialised significantly outstrips our understanding of their practical value for clinicians. This rapid development has created an...Read more
2024 31 Jul
Integrating artificial intelligence (AI) in medical diagnostics, particularly in radiology, promises to revolutionise clinical decision-making. However, the pace at which AI technologies are being developed and commercialised significantly outstrips our understanding of their practical value for clinicians. This rapid development has created an...Read more
2024 03 Jul
The American College of Radiology (ACR) has recently launched the ACR Recognised Centre for Healthcare-AI (ARCH-AI), a pioneering quality assurance programme designed to enhance the implementation and oversight of artificial intelligence in radiology. This initiative represents a significant advancement in ensuring that AI technologies are integrated...Read more
2024 03 Jul
The American College of Radiology (ACR) has recently launched the ACR Recognised Centre for Healthcare-AI (ARCH-AI), a pioneering quality assurance programme designed to enhance the implementation and oversight of artificial intelligence in radiology. This initiative represents a significant advancement in ensuring that AI technologies are integrated...Read more
2024 25 Apr
Strategies for Addressing Bias in Artificial Intelligence for Medical Imaging The understanding of bias in artificial intelligence (AI) involves recognising various definitions within the AI context. Bias can refer to unequal treatment based on preexisting attitudes, with distinctions between intentional and unintentional bias. Cognitive...Read more
2024 25 Apr
Strategies for Addressing Bias in Artificial Intelligence for Medical Imaging The understanding of bias in artificial intelligence (AI) involves recognising various definitions within the AI context. Bias can refer to unequal treatment based on preexisting attitudes, with distinctions between intentional and unintentional bias. Cognitive...Read more
2024 25 Apr
Strategies for Addressing Bias in Artificial Intelligence for Medical Imaging The understanding of bias in artificial intelligence (AI) involves recognising various definitions within the AI context. Bias can refer to unequal treatment based on preexisting attitudes, with distinctions between intentional and unintentional bias. Cognitive...Read more