Search Tag: AI in radiology
2025 10 Nov
Referring physicians who rely on radiology services are central to how artificial intelligence is adopted in clinical pathways. A survey of licensed doctors in Germany explored how these clinicians view AI in radiological diagnosis, what they trust and which applications they value most. The sample included internists, surgeons and general practitioners,...Read more
2025 10 Nov
Referring physicians who rely on radiology services are central to how artificial intelligence is adopted in clinical pathways. A survey of licensed doctors in Germany explored how these clinicians view AI in radiological diagnosis, what they trust and which applications they value most. The sample included internists, surgeons and general practitioners,...Read more
2025 10 Nov
Referring physicians who rely on radiology services are central to how artificial intelligence is adopted in clinical pathways. A survey of licensed doctors in Germany explored how these clinicians view AI in radiological diagnosis, what they trust and which applications they value most. The sample included internists, surgeons and general practitioners,...Read more
2025 31 Oct
Large language models (LLMs) are increasingly used to translate technical radiology reports into patient-friendly language. A comparative evaluation of three freely accessible LLMs (ChatGPT 3.5, Google Gemini and Microsoft Copilot) assessed how they explain radiology findings to patients using a standardised prompt. Expert radiologists reviewed...Read more
2025 18 Oct
AI is transforming radiology, offering both interpretative and workflow-enhancing tools. Inspired by sectors like automotive, retail and finance, radiology can adopt AI-driven practices to improve efficiency, personalisation and cost control. From tailored reports to smart scheduling and inventory management, cross-industry innovations show great...Read more
2025 16 Oct
Accurate preoperative classification of bone tumours as benign or malignant supports timely treatment selection and better outcomes, yet interpretation of radiographs can be challenging, particularly for less experienced clinicians. A machine learning approach integrating radiomics features from knee X-ray images with routine clinical data was...Read more
2025 16 Oct
Accurate preoperative classification of bone tumours as benign or malignant supports timely treatment selection and better outcomes, yet interpretation of radiographs can be challenging, particularly for less experienced clinicians. A machine learning approach integrating radiomics features from knee X-ray images with routine clinical data was...Read more
2025 16 Oct
Accurate preoperative classification of bone tumours as benign or malignant supports timely treatment selection and better outcomes, yet interpretation of radiographs can be challenging, particularly for less experienced clinicians. A machine learning approach integrating radiomics features from knee X-ray images with routine clinical data was...Read more
2025 16 Oct
Artificial intelligence is advancing quickly in medical imaging, expanding potential users and use cases while exposing gaps in knowledge about capabilities, risks and deployment. Complex models, large data demands and distinct non-human failure modes make safe adoption challenging. A multisociety syllabus from several institutions sets out role-specific...Read more
2025 02 Sep
Artificial intelligence has become an integral part of radiology, particularly in high-demand settings such as emergency and teleradiology services. Non-contrast head CT scans are central to evaluating acute emergencies including intracranial haemorrhage, a condition with a 44% mortality rate within 30 days and a recovery rate of only 20% at six...Read more
2025 02 Sep
Artificial intelligence has become an integral part of radiology, particularly in high-demand settings such as emergency and teleradiology services. Non-contrast head CT scans are central to evaluating acute emergencies including intracranial haemorrhage, a condition with a 44% mortality rate within 30 days and a recovery rate of only 20% at six...Read more
2025 16 Aug
Artificial intelligence is increasingly shaping radiology, supporting detection, diagnosis and workflow efficiency. Its safe use, however, depends on robust evaluation of performance. Metrics must reflect clinical objectives, patient safety and real-world settings rather than theoretical accuracy alone. The European Society of Medical Imaging...Read more
2025 16 Aug
Artificial intelligence is increasingly shaping radiology, supporting detection, diagnosis and workflow efficiency. Its safe use, however, depends on robust evaluation of performance. Metrics must reflect clinical objectives, patient safety and real-world settings rather than theoretical accuracy alone. The European Society of Medical Imaging...Read more
2025 22 Jul
Large language models (LLMs) such as ChatGPT and Google Gemini are increasingly used to improve patient communication by simplifying complex medical content. In breast imaging, radiology reports are often filled with specialised terminology that can confuse patients, particularly when accessed online before physician consultation. Clearer language...Read more
2025 22 Jul
Large language models (LLMs) such as ChatGPT and Google Gemini are increasingly used to improve patient communication by simplifying complex medical content. In breast imaging, radiology reports are often filled with specialised terminology that can confuse patients, particularly when accessed online before physician consultation. Clearer language...Read more
2025 22 Jul
Large language models (LLMs) such as ChatGPT and Google Gemini are increasingly used to improve patient communication by simplifying complex medical content. In breast imaging, radiology reports are often filled with specialised terminology that can confuse patients, particularly when accessed online before physician consultation. Clearer language...Read more
2025 20 Jul
The integration of artificial intelligence into breast cancer screening holds promise for addressing workforce shortages and enhancing diagnostic accuracy. While previous studies have demonstrated that AI decision support can improve sensitivity without compromising specificity or reading time, its influence on radiologists’ visual search strategies...Read more
2025 20 Jul
The integration of artificial intelligence into breast cancer screening holds promise for addressing workforce shortages and enhancing diagnostic accuracy. While previous studies have demonstrated that AI decision support can improve sensitivity without compromising specificity or reading time, its influence on radiologists’ visual search strategies...Read more
2025 20 Jul
The integration of artificial intelligence into breast cancer screening holds promise for addressing workforce shortages and enhancing diagnostic accuracy. While previous studies have demonstrated that AI decision support can improve sensitivity without compromising specificity or reading time, its influence on radiologists’ visual search strategies...Read more
2025 20 Jul
The integration of artificial intelligence into breast cancer screening holds promise for addressing workforce shortages and enhancing diagnostic accuracy. While previous studies have demonstrated that AI decision support can improve sensitivity without compromising specificity or reading time, its influence on radiologists’ visual search strategies...Read more
2025 01 Jul
Large language models (LLMs) are increasingly integrated into interventional radiology (IR), offering support for decision-making, documentation and communication. Their effectiveness, however, depends on the quality of the inputs they receive. Prompt engineering—the practice of carefully designing these inputs—is essential for generating outputs...Read more
2025 20 Jun
Radiology departments face increasing pressure to deliver timely and accurate reports. Compounding this challenge is a global shortage of radiologists, creating a pressing need for solutions that enhance productivity without compromising quality. Generative artificial intelligence has been recognised as a promising tool in this context, offering...Read more
2025 20 Jun
Radiology departments face increasing pressure to deliver timely and accurate reports. Compounding this challenge is a global shortage of radiologists, creating a pressing need for solutions that enhance productivity without compromising quality. Generative artificial intelligence has been recognised as a promising tool in this context, offering...Read more
2025 15 Jun
Cancer-associated cachexia (CAC) is a complex syndrome marked by irreversible muscle loss, with or without fat depletion, that cannot be remedied by nutrition alone. Affecting up to 70% of patients with cancer, CAC significantly worsens outcomes by accelerating disease progression, reducing tolerance to treatment and increasing mortality. Despite...Read more
2025 17 May
The integration of artificial intelligence into radiology promises substantial improvements in diagnostics, patient outcomes and clinical efficiency. However, many healthcare institutions remain unprepared to fully harness machine learning’s potential due to operational and governance challenges. To address this, the concept of Medical Machine...Read more
2025 13 May
The accurate and timely communication of critical findings from radiology reports is vital to effective patient care. Traditionally, this task has relied on human effort, with radiologists manually identifying and reporting urgent observations. However, radiology reports are often unstructured, inconsistent and lengthy, posing significant challenges...Read more
2025 13 May
The accurate and timely communication of critical findings from radiology reports is vital to effective patient care. Traditionally, this task has relied on human effort, with radiologists manually identifying and reporting urgent observations. However, radiology reports are often unstructured, inconsistent and lengthy, posing significant challenges...Read more
2025 13 May
The accurate and timely communication of critical findings from radiology reports is vital to effective patient care. Traditionally, this task has relied on human effort, with radiologists manually identifying and reporting urgent observations. However, radiology reports are often unstructured, inconsistent and lengthy, posing significant challenges...Read more
2025 12 May
Incidental detection of pancreatic cystic lesions (PCLs) is increasingly common during abdominal imaging. While many of these lesions are benign, some carry the potential for malignancy, necessitating routine surveillance. The American College of Radiology (ACR) Incidental Findings Committee (IFC) provides a detailed algorithm to guide follow-up...Read more
2025 24 Apr
Artificial intelligence (AI) is revolutionising radiology, offering improved diagnostic precision and operational efficiency. Deep learning models, particularly within medical imaging, are at the forefront of this transformation. However, the increasing adoption of AI in radiology has introduced a complex sustainability paradox. While AI holds...Read more