RSNA names Kahn to head AI publication

Wayne Forrest
May 1, 2018
2018 05 02 17 31 3108 Kahn Charles 20180502170702

The RSNA has named Dr. Charles Kahn Jr. as editor of the new online journal Radiology: Artificial Intelligence. The society plans to launch the journal early next year as a showcase for research in the burgeoning field of artificial intelligence (AI), deep learning, and machine learning.

Dr. Charles Kahn Jr.Dr. Charles Kahn Jr. Kahn currently serves as professor and vice chair of the department of radiology at the University of Pennsylvania's Perelman School of Medicine. He has also served as an associate editor for Radiology and as an associate editor for the American Journal of Roentgenology.

The RSNA plans to launch Radiology: Artificial Intelligence early next year. The journal will be published online on a bimonthly schedule, focusing on emerging applications of machine learning and artificial intelligence across multiple imaging disciplines.

The society also plans to launch another bimonthly online journal, Radiology: Cardiothoracic Imaging, in the spring of 2019. Dr. Suhny Abbara will be the editor.

Latest in Artificial Intelligence
Fat Tissue Adipocytes
T2-weighted MRI shows promise for body composition analysis
February 21, 2025
Artificial Intelligence Ai Medical Healthcare Tools 400
Enlitic, Laitek ink data migration support agreement with GEHC
February 18, 2025
Artificial Intelligence Ai Data
Public trust in medical AI use low
February 14, 2025
Chat Gpt Gpt 4 Logo Screen Smartphone
Can LLMs help improve oncologic imaging interpretation?
February 4, 2025
        An unexpected error occurred: Network error: Response not successful: Received status code 500
      
            [
  {
    "message": "Cannot execute GraphQL operations after the server has stopped.",
    "extensions": {
      "code": "INTERNAL_SERVER_ERROR"
    }
  }
]
More in Artificial Intelligence
T2-weighted MRI shows promise for body composition analysis
By Kate Madden Yee
Using deep learning with T2-weighted MR imaging is a feasible way to assess patients' body composition, researchers have reported.
February 21, 2025
Fat Tissue Adipocytes
Enlitic, Laitek ink data migration support agreement with GEHC
By AuntMinnie.com staff writers
Enlitic and subsidiary Laitek have signed an agreement with GE HealthCare to support data migration across GE HealthCare’s delivery networks.
February 18, 2025
Artificial Intelligence Ai Medical Healthcare Tools 400
Public trust in medical AI use low
By Amerigo Allegretto
Trust is low among U.S. adults when it comes to healthcare systems using AI responsibly and protecting patients from AI-related harms.
February 14, 2025
Artificial Intelligence Ai Data
Can LLMs help improve oncologic imaging interpretation?
By Erik L. Ridley
A large-language model was found to significantly improve the quality of patient clinical histories for oncologic imaging requisitions.
February 4, 2025
Chat Gpt Gpt 4 Logo Screen Smartphone
Using AI with mammography can help select women for breast MRI
By Amerigo Allegretto
Using AI with mammography can help select women at high risk of breast cancer for supplemental MRI.
February 4, 2025
Images depict a 55-year-old woman with a family history of breast cancer who underwent combined mammography and MRI screening. (A) Right and (B) left mediolateral oblique and (C) right and (D) left craniocaudal mammograms show a large known cyst in the left breast (arrow in B and D), but were otherwise assessed as being unremarkable. Breast tissue was judged to be extremely dense. (E) Concurrent axial subtraction MRI scan shows a large, diffuse, invasive lobular cancer (circle) in the right breast. The AI system provided a case-based cancer suspicion score of 8 on a scale of 0-10, which would have led to selection for MRI screening using both the score 5 and score 8 thresholds, but not the score 9 threshold.
Samsung Medison debuts AI-powered ob/gyn ultrasound system
By AuntMinnie.com staff writers
Korea-based Samsung Medison has launched a new AI-powered ob/gyn ultrasound system in the U.S.
January 31, 2025
Ultrasound Exam Transducer 66d214b1d4014
Use ChatGPT-4 to extract additional imaging recs in radiology reports
By Kate Madden Yee
ChatGPT-4 is an effective way to extract recommendations for additional imaging in radiology reports, according to a study published January 29.
January 29, 2025
Chat Gpt2
Experts call for CPT codes for imaging AI reimbursement
By Amerigo Allegretto
Imaging AI tools and algorithms continue to be rapidly developed, but experts say reimbursement through CPT codes is needed.
January 24, 2025
Insurance Computer 400
AI guidance leads to better LUS image acquisition by novice users
By Amerigo Allegretto
Healthcare professionals who are not sonography experts can successfully acquire lung ultrasound (LUS) images with AI assistance.
January 15, 2025
Ultrasound Probe2 Social
ML model using CCTA, MRI data predicts MACE in cardiac patients
By Amerigo Allegretto
A machine-learning (ML) model that includes both CCTA and stress cardiac MRI data can accurately predict major adverse cardiovascular events (MACE).
January 14, 2025
Heart Valves 3 D Base Thumbnail
AI will transform early cancer detection, save lives in 2025
By Roland Rott
In a new column, Roland Rott of GE HealthCare makes the case that 2025 will be a watershed year for AI in radiology.
January 13, 2025
Roland Rott Thumbnail
CEM-, radiomics-based models predict breast biopsy outcomes
By Amerigo Allegretto
Machine-learning models combining features from radiomics and contrast-enhanced mammography (CEM) can predict breast biopsy outcomes in women.
January 13, 2025
Mammo Reading Social
Page 1 of 373
Next Page