Journal of the American College of Radiology : JACR Journal of the American College of Radiology : JACR RSS feedThis is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Authors ’ Reply
We are pleased to read that Dr Baker and his colleagues at The Joint Commission (TJC) have taken interest in our article [1]. Furthermore, we agree with Baker ’s statement that the requirements for Ongoing Professional Practice Evaluation (OPPE) established by TJC do not dictate what data are collected, what metrics are established, and what thresholds are chosen for those metrics [2]. In addition to our statement that “accredited healthcare organizat ions are required to define their OPPE parameters, methods of data collection, and process for administering OPPE” [1], we discussed the potential downsides of this app...
Source: Journal of the American College of Radiology : JACR - February 12, 2024 Category: Radiology Authors: Lane F. Donnelly, Daniel J. Podberesky, Alexander J. Towbin, Ling Loh, Kathryne H. Basta, Terry S. Platchek, Michael T. Vossmeyer, Joan E. Shook Tags: Letters to the Editor Source Type: research

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(Source: Journal of the American College of Radiology : JACR)
Source: Journal of the American College of Radiology : JACR - February 1, 2024 Category: Radiology Source Type: research

The Neiman Imaging Comorbidity Index: Development and Validation in a National Commercial Claims Database
To build the Neiman Imaging Comorbidity Index (NICI), based on variables available in claims datasets, which provides good discrimination of an individual ’s chance of receiving advanced imaging (CT, MR, PET), and thus, utility as a control variable in research. (Source: Journal of the American College of Radiology : JACR)
Source: Journal of the American College of Radiology : JACR - January 24, 2024 Category: Radiology Authors: Casey E. Pelzl, Andrew B. Rosenkrantz, Elizabeth Y. Rula, Eric W. Christensen Tags: Original Article Source Type: research

Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement From the ACR, CAR, ESR, RANZCR & RSNA
Artificial intelligence (AI) carries the potential for unprecedented disruption in radiology, with possible positive and negative consequences. The integration of AI in radiology holds the potential to revolutionize healthcare practices by advancing diagnosis, quantification, and management of multiple medical conditions. Nevertheless, the ever-growing availability of AI tools in radiology highlights an increasing need to critically evaluate claims for its utility and to differentiate safe product offerings from potentially harmful, or fundamentally unhelpful ones. (Source: Journal of the American College of Radiology : JACR)
Source: Journal of the American College of Radiology : JACR - January 22, 2024 Category: Radiology Authors: Adrian P. Brady, Bibb Allen, Jaron Chong, Elmar Kotter, Nina Kottler, John Mongan, Lauren Oakden-Rayner, Daniel Pinto dos Santos, An Tang, Christoph Wald, John Slavotinek Tags: Original Article Source Type: research

Radiologists ’ Out-of-Network Billing Trends, 2007 to 2021
Given the financial hardships of surprise billing for patients, the aim of this study was to assess the degree to which radiologists effectively participate in commercial insurance networks by examining the trend in the share of radiologists ’ imaging claims that are out of network (OON). (Source: Journal of the American College of Radiology : JACR)
Source: Journal of the American College of Radiology : JACR - January 19, 2024 Category: Radiology Authors: Jay R. Parikh, Alexandra R. Drake, Mikki D. Waid, Elizabeth Y. Rula, Eric W. Christensen Tags: Original Article Source Type: research

Generative Artificial Intelligence: A Promising Instrument for Daily Living and Clinical Practice
We read with great interest the article by Gordon et  al, which aims to assess the accuracy, relevance, and readability of generative language artificial intelligence (AI) in responding to common patient questions regarding radiology reports [1]. (Source: Journal of the American College of Radiology : JACR)
Source: Journal of the American College of Radiology : JACR - January 16, 2024 Category: Radiology Authors: Gustavo Adolfo Triana Rodriguez, Mar ía M. Rojas-Rojas, Katherine Sotomayor, Juan P. Ovalle, José David Cardona Ortegón Tags: Letter to the Editor Source Type: research

Generative AI: A Promising Instrument for Daily Living and Clinical Practice
(Source: Journal of the American College of Radiology : JACR)
Source: Journal of the American College of Radiology : JACR - January 16, 2024 Category: Radiology Authors: Gustavo Adolfo Triana Rodriguez, Mar ía M. Rojas-Rojas, Katherine Sotomayor, Juan P. Ovalle, José David Cardona Ortegón Tags: Letter Source Type: research

The Application of Large Language Models for Radiologic Decision Making
Large language models (LLMs) have seen explosive growth, but their potential role in medical applications remains underexplored. Our study investigates the capability of LLMs to predict the most appropriate imaging study for specific clinical presentations in various subspecialty areas in radiology. (Source: Journal of the American College of Radiology : JACR)
Source: Journal of the American College of Radiology : JACR - January 13, 2024 Category: Radiology Authors: Hossam A. Zaki, Andrew Aoun, Saminah Munshi, Hazem Abdel-Megid, Lleayem Nazario-Johnson, Sun Ho Ahn Tags: Original Article Source Type: research

Beyond Leadership and Followership: Stewardship
(Source: Journal of the American College of Radiology : JACR)
Source: Journal of the American College of Radiology : JACR - January 13, 2024 Category: Radiology Authors: Richard B. Gunderman Tags: Opinion Source Type: research

The Application of LLMs for Radiologic Decision-Making
Large Language Models (LLMs) have seen explosive growth, but their potential role in medical applications remains underexplored. Our study investigates the capability of LLMs to predict the most appropriate imaging study for specific clinical presentations in various subspecialty areas in radiology. (Source: Journal of the American College of Radiology : JACR)
Source: Journal of the American College of Radiology : JACR - January 13, 2024 Category: Radiology Authors: Hossam A. Zaki, Andrew Aoun, Saminah Munshi, Hazem Abdel-Megid, Lleayem Nazario-Johnson, Sun Ho Ahn Source Type: research

Improving Efficiencies While Also Delivering Better Health Care Outcomes: A Role for Large Language Models
Generative artificial intelligence (AI), specifically the large language models (LLMs) that underlie impressive new applications such as ChatGPT, are already fundamentally changing medicine. Unlike more traditional AI systems that produce simple outputs such as a number (say, the predicted length of stay for a patient in the hospital) or a category (say, “malignant” or “benign” for a radiologic system), “generative AI” refers broadly to systems whose outputs take the form of more unstructured media objects, such as images and documents. (Source: Journal of the American College of Radiology : JACR)
Source: Journal of the American College of Radiology : JACR - January 12, 2024 Category: Radiology Authors: Shivdev K. Rao, Elliot K. Fishman, Ryan C. Rizk, Linda C. Chu, Steven P. Rowe Tags: Rethinking the Patient Experience Source Type: research

The Impact of Closed-Loop Imaging on  Actionable CT-Detected Breast Findings
Closed-loop imaging programs (CLIPs) are designed to ensure that patients receive appropriate follow-up, but a review of incidental CT-detected breast findings in the setting of CLIPs has not been performed. (Source: Journal of the American College of Radiology : JACR)
Source: Journal of the American College of Radiology : JACR - January 12, 2024 Category: Radiology Authors: Allison Aripoli, Madeleine Gurney, Rebecca Flynn Sourk, Ryan Ash, Christopher M. Walker, Jessica Peterson, Ashley Huppe, Camron Smith, Carissa Walter, Lauren Clark, Onalisa Winblad Tags: Original Article Source Type: research

Improving Efficiencies While Also Delivering Better Healthcare Outcomes: A Role For Large Language Models
(Source: Journal of the American College of Radiology : JACR)
Source: Journal of the American College of Radiology : JACR - January 12, 2024 Category: Radiology Authors: Shivdev K. Rao, Elliot K. Fishman, Ryan C. Rizk, Linda C. Chu, Steven P. Rowe Source Type: research

The Impact of Closed Loop Imaging on Actionable CT-Detected Breast Findings
Closed Loop Imaging Programs (CLIP) are designed to ensure that patients receive appropriate follow-up, however, review of incidental CT-detected breast findings in the setting of CLIPs has not been performed. (Source: Journal of the American College of Radiology : JACR)
Source: Journal of the American College of Radiology : JACR - January 12, 2024 Category: Radiology Authors: Allison Aripoli, Madeleine Gurney, Rebecca Flynn Sourk, Ryan Ash, Christopher M. Walker, Jessica Peterson, Ashley Huppe, Camron Smith, Carissa Walter, Lauren Clark, Onalisa Winblad Source Type: research

Radiomics Features Extracted From Pre- and Postprocedural Imaging in Early Prediction of Treatment Response in Patients Undergoing Transarterial Radioembolization of Hepatic Lesions: A Systematic Review, Meta-Analysis, and Quality Appraisal Study
This article aims to provide meta-analytic evidence and critically appraise the methodology of radiomics studies published in this regard. (Source: Journal of the American College of Radiology : JACR)
Source: Journal of the American College of Radiology : JACR - January 11, 2024 Category: Radiology Authors: Mohammad Mirza-Aghazadeh-Attari, Tara Srinivas, Arun Kamireddy, Alan Kim, Clifford R. Weiss Tags: Review Article Source Type: research