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Clinic Image Interpretation Radiologist 
AuntMinnie
FEBRUARY 26, 2025
VIENNA Generative AI may have novel applications in the clinic, but using the technology comes with its share of challenges and future directions, according to a presentation given February 26 at ECR 2025. Behind him is an image created by one such generative AI model, which illustrates humans working alongside AI.
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AuntMinnie
FEBRUARY 28, 2025
The finding is from a preliminary analysis of 23 patients enrolled in an ongoing clinical trial, noted Giorgio Brembilla, MD, PhD, of the IRCCS San Raffaele Scientific Institute in Milan, Italy. Interpretation accuracy is compared with biopsy results. Giorgio Brembilla, MD, PhD.
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AuntMinnie
NOVEMBER 21, 2024
Frequent AI use is associated with an increased risk of radiologist burnout, particularly among those with high workloads and low AI acceptance, suggests a study published November 22 in JAMA Network Open. In China, the annual growth rate of medical imaging data is 7.5 times that of radiologists, they wrote. were female and 64.7%
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AuntMinnie
APRIL 2, 2025
A significant percentage of imaging studies ordered by office-based healthcare providers are self-interpreted rather than referred to radiologists for reading, according to researchers from the Harvey L. of office-based studies were interpreted by the ordering provider, and 58.5% Neiman Health Policy Institute (HPI).
AuntMinnie
MAY 29, 2024
Proponents of AI in radiology highlight the technology’s potential in assistant radiologists with image interpretation as well as improving patient care. “Biased data results in biased AI models,” Yahyavi said.
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AuntMinnie
APRIL 17, 2024
Detecting rib fractures in pediatric x-rays is challenging, as they can be obliquely oriented to the imaging detector or obscured by other structures, the authors explained. Even expert, specialized radiologists performing their first reads on x-rays can miss up to two-thirds of all rib fractures, they added.
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AuntMinnie
FEBRUARY 4, 2025
Radiologists highly prefer patient clinical histories generated by large language models (LLMs) for oncologic imaging requisitions to those typically produced by referring physicians,according to research published February 4 in Radiology.
AuntMinnie
OCTOBER 31, 2023
Systematic approaches to image interpretation are generally regarded as a cornerstone in the education of trainees. As a potential alternative, researchers have begun to explore the use of AI for artificially generating clinical cases.
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AuntMinnie
DECEMBER 14, 2023
A team led by Nilgun Guldogan, MD, from Acibadem Altunizade Hospital in Istanbul, Turkey, found that an AI method showed comparable performance to that of radiologists and can help avoid unnecessary biopsies and follow-up exams. “By considering AI-assigned BI-RADS 2 as safe, we could potentially avoid 11% of benign lesion biopsies and 46.2%
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AuntMinnie
JULY 25, 2024
Researchers led by Seyed Tabatabaei, MD, from Massachusetts General Hospital and Harvard Medical School in Boston, in their clinical perspective outlined these pitfalls and made suggestions on AI model training and validation, as well as using diverse datasets. The radiologist made a correct interpretation upon assessment of the entire exam.
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AuntMinnie
APRIL 11, 2025
Under scrutiny As medical imaging platforms evolve, even subtle changes in how images are rendered on new viewers can alter how they appear to radiologists, despite the underlying data remaining unchanged. These variations, while often imperceptible to the untrained eye, can influence clinical interpretation.
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AuntMinnie
MARCH 22, 2024
“These functionalities indicate the tool's potential to improve radiological workflows by pre-screening and categorizing ultrasound images,” Sultan told AuntMinnie.com. This technology, if implemented in clinical practice, will have great potential in enhancing medical image interpretation and healthcare outcomes.”
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AuntMinnie
MARCH 22, 2024
“These functionalities indicate the tool's potential to improve radiological workflows by pre-screening and categorizing ultrasound images,” Sultan told AuntMinnie.com. This technology, if implemented in clinical practice, will have great potential in enhancing medical image interpretation and healthcare outcomes.”
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AuntMinnie
OCTOBER 25, 2024
A commercially available AI model was on par with radiologists when detecting abnormalities on chest x-rays, and eliminated a gap in accuracy between radiologists and nonradiologist physicians, according to a study published October 24 in Scientific Reports. Chest-CAD is a deep-learning algorithm approved by the U.S.
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AuntMinnie
JANUARY 30, 2024
AI improves chest x-ray imaging interpretation by nonradiologist practitioners, which could be useful in low-resource settings, according to research published January 29 in Chest. That last part can be challenging for nonradiologists who do not constantly interpret diagnostic imaging exams.
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AuntMinnie
OCTOBER 31, 2024
ChatGPT demonstrates modest accuracy when assigning BI-RADS scores for mammograms and breast ultrasound exams, according to research published October 30 in Clinical Imaging. Previous reports suggest that large language models can correctly recommend appropriate imaging modalities for patients based on their clinical presentation.
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AuntMinnie
DECEMBER 17, 2024
A diagnostic radiologist who recently joined Ochsner clinic in New Orleans, LA, after partnering at Southeast Radiology in Pennsylvania, Rubin expects consolidation in radiology to continue. Depending on the data source used, the radiology specialty may see a net decrease in the number of radiologists in the U.S.
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AuntMinnie
JULY 1, 2024
In some interventional radiology practices, advanced practice providers -- including PAs and NPs -- provide nonprocedural evaluation and management services, including consultations and clinic visits. But it also appears that the volume of PICC placements, paracentesis, and thoracentesis performed by PAs and NPs increased by 10.5%
Imaging Technology
NOVEMBER 14, 2024
The American College of Radiology (ACR), a professional medical society representing radiologists, has also joined the Healthcare AI Challenge Collaborative as a founding member to ensure its 42,000 members have access to the Healthcare AI Challenge. Additional member institutions will be announced in subsequent phases.
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Aidoc
FEBRUARY 16, 2025
The rising demand for imaging services, coupled with an aging population and ever-increasing shortage of radiologists, creates the perfect storm for backlogs on a reading list. At seven days post-imaging, nearly half had unreported brain and chest CT scans, while 59% had unreported chest radiographs.
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Imaging Technology
DECEMBER 2, 2024
The collaboration aims to unify diagnostic workflows, improving access to critical insights and driving better outcomes across clinical specialties. By automating routine tasks and optimizing workflows, clinicians would be able to dedicate more time to image interpretation, consultations and patient interactions.
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Ben White
JUNE 20, 2023
That means dictating a report before looking at the wording of the prior report to see how you describe something versus another radiologist or if you made all of the findings. Critically review your own work and identify areas where you can improve, such as image interpretation accuracy or communication skills.
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Future Teleradiology
NOVEMBER 30, 2023
Teleradiology & Radiology data for artificial intelligence (AI) Introduction: Embark on a thought-provoking exploration into the realm of radiology, challenging a prevailing myth that suggests the best radiologists are easily fooled. Discuss the cognitive expertise required for accurate image interpretation and diagnosis.
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Ben White
APRIL 12, 2023
Radiologists (or clinicians of any stripe) need to constantly regulate and bring to consciousness balanced decision-making between observation and synthesis (putting together multiple findings to reach a conclusion) and anchoring on initial observations in ways that can impair objective analysis. But some aren’t.
130 
Ben White
APRIL 23, 2023
One of his tweets: #RGchat T1: the ABR certification exam is intended to test knowledge as it relates to competence, and critical thinking as it relates to image interpretation. A lot of radiologists have suggested that a multiple-choice exam simply can’t test for the soft skills that the oral boards could (which is undeniable).
130 
Future Teleradiology
NOVEMBER 24, 2023
Discuss how remote image interpretation has brought specialized radiological expertise to underserved communities, reducing the need for patients to travel long distances for diagnostic services. Emergency Imaging Response: Highlight a success story where teleradiology played a crucial role in emergency situations.
Imaging Technology
APRIL 2, 2024
As patient procedures grow in number and complexity throughout a variety of care areas, today’s staffing shortages and other clinical challenges are expected to become more significant. This includes MIMneuro , which offers quantification solutions for dopamine transporter imaging and amyloid imaging. iii Immerzeel J.,
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Future Teleradiology
DECEMBER 1, 2023
Introduction: Radiologists play a crucial role in modern healthcare by interpreting medical images to diagnose and guide patient treatment. To enhance diagnostic accuracy, reduce malpractice risk, and provide the highest level of patient care, radiologists employ search patterns in their image interpretation processes.
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Future Teleradiology
DECEMBER 1, 2023
To minimize such errors and reduce malpractice risk, radiologists rely on search patterns, a structured approach to image interpretation. In this article, we’ll explore why search patterns are essential in radiology, how they help reduce malpractice risk, and how radiologists can effectively use them in their practice.
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Imaging Technology
NOVEMBER 24, 2023
This capability fills an information gap that enables radiologists to provide the objective, data-driven information that could materially inform diagnosis and treatment options. He added, “CT LVAS allows radiologists to provide a whole new dimension of lung health information to referring clinicians needing answers.”
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Vesta Teleradiology
JUNE 4, 2024
Radiologists, either independently or in collaboration with non-radiologists, primarily reported these examinations. Sources: radiologybusiness.com ncbi.nlm.nih.gov acc.org openai.com The post Latest in Cardiac Imaging and Interpretation Challenges first appeared on Vesta Teleradiology. fold increase in MRIs and a 4.5-fold
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Future Teleradiology
NOVEMBER 24, 2023
Artificial Intelligence-Powered Interpretation: Discuss the integration of artificial intelligence (AI) in teleradiology for enhanced image interpretation. Explore how AI algorithms assist radiologists in detecting abnormalities, improving efficiency, and contributing to more accurate diagnoses.
Median
MARCH 20, 2024
Project Manager II at Median Technologies, the discussion was about how variability in imaging interpretation can lead to discrepancies in oncology clinical trial results. This is an excerpt from our podcast “Shaping Results through Imaging: Addressing Variability in Oncology Trials”. Hosted by Connor Anderson , U.S.
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Future Teleradiology
NOVEMBER 21, 2023
AI in Radiology: Revolutionizing Image Interpretation and Diagnostic Precision: Discuss the transformative impact of AI in radiology. Explore how the collaboration aims to leverage AI to revolutionize image interpretation, enhance diagnostic precision, and streamline radiological workflows.
Future Teleradiology
NOVEMBER 25, 2023
AI-Powered Image Analysis: Explore the integration of Artificial Intelligence (AI) in teleradiology for advanced image analysis. Discuss how AI algorithms are evolving to assist radiologists in detecting subtle abnormalities, improving diagnostic accuracy, and expediting image interpretation.
Imaging Technology
JULY 20, 2023
The Image Interpretation Session, moderated by C. will host “Oncology Imaging and Interventions: The Radiology Jeopardy,” a lively interactive game show experience, on Nov. 30, will focus on successful collaboration between radiologists and physicists in technical developments and clinical translations in medical imaging.
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Vesta Teleradiology
JULY 16, 2023
It connects radiologists with healthcare facilities, allowing them to interpret and analyze medical images remotely, regardless of geographical locations. These companies facilitate the transmission of medical images and reports, enabling timely diagnoses, expert consultations, and improved access to radiology services.
Future Teleradiology
OCTOBER 12, 2023
Automated image analysis assists radiologists in identifying patterns and abnormalities, improving accuracy and efficiency. Advanced Visualization Technologies: Teleradiology solutions leverage advanced visualization tools for detailed image interpretation.
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Future Teleradiology
NOVEMBER 22, 2023
Emphasize the transformative impact on diagnostic accessibility, allowing radiologists to reach patients in diverse locations and settings. Versatile Mobile Reading Stations: Discuss the features and versatility of the mobile diagnostic reading stations from Imaging Solutions.
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Future Teleradiology
OCTOBER 12, 2023
Automated image analysis assists radiologists in identifying patterns and abnormalities, leading to more accurate and efficient diagnoses. Advanced Visualization Technologies: Teleradiology solutions leverage advanced visualization tools for in-depth image interpretation.
Vesta Teleradiology
JULY 3, 2024
Mobile radiology companies play a vital role in modern healthcare by bringing diagnostic imaging services directly to patients, whether at home, in nursing facilities, or at remote medical clinics. mobile imaging services market was valued at approximately USD 5.3
Future Teleradiology
DECEMBER 25, 2023
Radiologist Shortages : Algeria, like many countries, faces a shortage of radiologists. This shortage can lead to delays in interpreting medical images, affecting patient care, particularly in emergencies. This expedites image analysis, reduces diagnostic delays, and ultimately enhances patient outcomes.
Future Teleradiology
DECEMBER 25, 2023
Radiologist Shortages : The shortage of radiologists is a global issue, and Algeria is no exception. This shortage can lead to delays in interpreting medical images, impacting patient care, particularly in emergency situations. Access to specialized medical expertise is often limited in these areas.
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Aidoc
AUGUST 1, 2024
By leveraging advanced algorithms, machine learning can identify trends and make connections that were previously unrecognizable, thereby enhancing clinical decision-making and patient care. Machine Learning in Healthcare Examples Machine learning applications are transforming various care settings and clinical operation workflows.
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