Imaging Informatics: Page 34

AI improves evaluations of knee osteoarthritis on x-rays
By Will Morton
A commercially available AI algorithm improved the performance of junior radiologists when grading knee osteoarthritis on x-rays.
July 9, 2024
An example of the study platform as seen by a reader receiving assistance from the AI tool. On the left is the overlay generated by the AI tool. On the right is the grading panel. Note that the grading fields are prefilled with the outputs of the AI tool. In this study, the left knee was to be graded. When the right was to be graded, the grading panel was on the left. The size of some user interface elements, primarily text and buttons, have been enhanced to improve legibility. JSN = joint space narrowing, KL = Kellgren-Lawrence, OST = osteophytes, PA = posteroanterior, SCL = subchondral sclerosis. Image and caption courtesy of Radiology.
Direct imaging inputs improve performance of large language models
By Amerigo Allegretto
Using direct radiologic image inputs can improve the diagnostic accuracy of large language models.
July 9, 2024
Artificial Intelligence Ai Hand
AI increases breast MRI's cancer detection 4-fold
By Amerigo Allegretto
An AI approach for supplemental breast MRI is about four times more efficient at detecting breast cancers than traditional methods.
July 9, 2024
(A) Case A was a 13-mm large BI-RADS 4 finding on MRI that corresponded to a 13-mm large invasive cancer as diagnosed in the surgical specimen. (B) Case B was a 9-mm large BI-RADS 4 finding on MRI that corresponded to an 8-mm invasive cancer and 14-mm ductal cancer in situ. (C) Case C was three suspicious lesions within a total area of 60 mm, BI-RADS 5 finding on MRI, that corresponded to a 50-mm multifocal invasive lobular cancer. (D) Case D was two suspicious lesions, the largest 13 mm, BI-RADS 3 on MRI, which corresponded to a 10-mm invasive lobular cancer with 85-mm extent including ductal cancer in situ. Images courtesy of Nature Medicine. Licensed under CC BY 4.0.
Radiology departments can adopt responsible frameworks to deploy AI
By Amerigo Allegretto
Adopting a responsible framework could help overcome challenges in applying AI to medical imaging.
July 8, 2024
Screenshot (1346)
Machine learning with echo improves heart tumor diagnosis
By Amerigo Allegretto
Machine learning can help improve echocardiography interpretation of heart tumors.
July 2, 2024
Heart Artificial Intelligence Ai 400
Large language models help patients understand radiology reports
By Amerigo Allegretto
Large language models can generate summaries that could help patients better understand their radiology reports.
July 2, 2024
Radiological Report
SIIM: How to tackle the challenge of equity in IT, AI
By Erik L. Ridley
Kadija Ferryman, PhD, of Johns Hopkins in Baltimore discussed new ways to address health equity challenges in IT and AI in the opening general session at SIIM 2024.
June 27, 2024
Kadija Ferryman, PhD.
Ultrasound-based nomogram predicts ALNM in breast cancer patients
By Amerigo Allegretto
Combining ultrasound features and immune-inflammatory markers could help predict axillary lymph node metastasis (ALNM) in breast cancer patients.
June 26, 2024
Ultrasound Exam Transducer
The PACSman Pontificates: Is radiology ready for AI and vice versa?
By Michael J. Cannavo
In a new column, Michael J. Cannavo, aka the PACSman, assesses the current readiness of the radiology AI market.
June 26, 2024
The PACSman, Mike Cannavo.
ChatGPT can provide patients with radiation protection info
By Erik L. Ridley
A new study concluded that ChatGPT could provide patients with answers to radiation protection questions, even if it was a little wordy.
June 25, 2024
Chat Gpt
Rady Children's Hospital to offer 3D visualization software at no cost
By Amerigo Allegretto
Rady Children’s Hospital in San Diego is making its Arc Viewer available to hospitals across the U.S.
June 25, 2024
Rady Children's Hospital is making its Arc Viewer, a 3D modeling software developed by the 3D Innovations Lab within the hospital, available to use by other U.S. hospitals at no cost.
The deep-learning triple threat transforming medical imaging
By Kelly Londy
In a new column, Kelly Londy of GE HealthCare describes how radiology AI technology could impact planning, imaging acquisition, and diagnosis.
June 24, 2024
Kelly Londy of GE HealthCare.
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