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Comment
. 2024 Jan;6(1):e230222.
doi: 10.1148/rycan.230222.

Implications of Data Representation in Health Care Innovation

Randy C Miles  1 , Antonio R Porras  1
Affiliations
Comment

Implications of Data Representation in Health Care Innovation

Randy C Miles et al. Radiol Imaging Cancer. 2024 Jan.
No abstract available

PubMed Disclaimer

Conflict of interest statement

Disclosures of conflicts of interest: R.C.M. Honoraria from GE and Hologic for educational lectures; associate editor for Radiology: Imaging Cancer. A.R.P. Grants or contracts from the National Institutes of Health/National Institute of Dental and Craniofacial Research, National Institute of Biomedical Imaging and Bioengineering, and Clinical and Translational Science Awards Program, and the Colorado Clinical and Translational Sciences Institute (grant nos. R00 DE027993, R13 EB032243, R01DE030286, R01DE032681, R21DEP31824, and CO-J-23-99/CTSA UM1 TR004933); member of the advisory board of mGeneRX (unpaid), a startup from one of the author’s previous research works (no overlap with the work and/or contents of this article); equity option for 0.5% in mGeneRX.

Figures

Randy C. Miles, MD, MPH, serves as the chief of breast imaging at Denver Health, with oversight over the breast division’s clinical, research, and educational programs. He also serves as the Associate Director for Research in the radiology department. Dr Miles’ clinical, research, and public health efforts center around using innovative techniques to identify barriers to breast cancer screening, create patient-centered initiatives to improve access to breast imaging services, and examine how to improve delivery of high-quality, guideline-concordant breast care for all patients.
Randy C. Miles, MD, MPH, serves as the chief of breast imaging at Denver Health, with oversight over the breast division’s clinical, research, and educational programs. He also serves as the Associate Director for Research in the radiology department. Dr Miles’ clinical, research, and public health efforts center around using innovative techniques to identify barriers to breast cancer screening, create patient-centered initiatives to improve access to breast imaging services, and examine how to improve delivery of high-quality, guideline-concordant breast care for all patients.
Antonio R. Porras, PhD, is an assistant professor of biostatistics and informatics at the Colorado School of Public Health and director of the Medical Image Phenotyping Lab at the University of Colorado Anschutz Medical Campus. He is an expert in medical image computing and machine learning, and his main research interest is the identification and characterization of medical conditions by using imaging data.
Antonio R. Porras, PhD, is an assistant professor of biostatistics and informatics at the Colorado School of Public Health and director of the Medical Image Phenotyping Lab at the University of Colorado Anschutz Medical Campus. He is an expert in medical image computing and machine learning, and his main research interest is the identification and characterization of medical conditions by using imaging data.
See this image and copyright information in PMC

Comment on

References

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