Digital Pathology: Triangulating Our Path by Looking at Radiology's Experience

There's a steadily rising number of articles about digital pathology in the mainstream pathology journals and trade journals.   See:

• "A look ahead to AI based assistance in anatomic pathology" - CAP TODAY, February 2022 here.
• "Cytopathology - At the center of AI implementation" - CAP TODAY, August 2021, here.
• CAP has a home page for "AI in Pathology" - here.  
• Citing, for example, Haymond, "Rise of the Machines: AI and the Clinical Laboratory" here and Rashidi, "Machine learning in healthcare and laboratory medicine," here.
• See also...a survey, how pathology stakeholders are reacting to digital pathology, Heinz 2022, here.  See a review of breast cancer and machine learning, Lee et al,  here.
• CAP also has a standing AI committee now, here.
• Fall of 2021 brought the first AI approval in anatomic pathology, for PAIGE and assisted or second-reading use in prostate biopsy pathology -
• See coverage at Fierce Biotech here, at FDA here, at 360DX here.
• Summary of Effectiveness, DEN200080, recently released by FDA here.

AMA

On the pure policy side, AMA has a workgroup on digital medicine, its Digital Medicine Payment Advisory Group, DMPAG, here.  

CMS

And CMS is now devoting several pages of its annual outpatient rulemaking (Part B rulemaking) to how to dollarize the RVU's and value of artificial intelligence, software, and licensing or per-click fees.   (E.g. 86 Fed Reg 65037ff, 65100ff, etc, November 19, 2021).  On the Part A side, CMS has granted temporary new technology add on payments (NTAPs) to radiology software that prioritizes a reading cue for the cases with the mostly-likely-dangerous conditions (VizAI here.)  

Journal of the American College of Radiology

While important policy or research articles on AI appear now "at regular intervals" in the major pathology journals, I think none of our lab journals approach the density of activity on AI innovation that can be seen in Journal of the American College of Radiology.  

I've been following JACR for over a decade (I used to have a lot of projects involving PET scans), and it's a fascinating journal.  

While it publishes original clinical research, a large proportion of all articles are devoted to breaking technologies, new policy initiatives, and "technology of change" issues.    Such topics certainly do occur in pathology journals, like J Molec Diagnostics, and when they appear, they are likely to be a committee's high quality position paper, but they're much less common on an issue-to-issue basis.

JACR has its main website here.   For example, as I'm writing today, one current top title is:

• "Liquid Biopsy, Diagnostic Imaging, and Future Synergies" by Petranovic et al. (19:P336), 
• ...which would probably be of a lot of interest to the  diagnostics part of the precision oncology community.  Mostly Harvard authors.

JACR: Over 100 Recent Titles on Radiology and Artificial Intelligence

Over at PubMed, you can search all articles by "journal name."  Instructions here.  A pre-made search on the JACR journal title here.   For example, a crude search of the journal title JACR and the simple keyword "intelligence" (for artificial intelligence) yielded 195 unselected articles out of 5,568 in JACR as a whole.

click to enlarge

To allow the reader to scan the headlines, from present towards the past, I've clipped 111 manually selected titles from JACR on artificial intelligence or machine learning, and pasted them in a separate blog here, as well as below the break in this article.  The articles run from current (February 2022) backwards to the end of 2018.  I've also put a bibliography export file in citation BIB format in the cloud here.

Separately, I informally classified the 111 articles below, into five general categories - 

#22 classified as "business,"

#40 classified as "implementation,"

#14 classified as performance and clinical reports,

#27 classed as "AI and people," (e.g. "How residents view AI"),

#8 classed as directly related to FDA, basic development, or other.

• ORGANIZED BY GROUP:  I've taken the 100 recent article titles from JACR and displayed them in the five groups, over here.  
• ORGANIZED REVERSE CHRONOLOGICAL:  Directly below, in this blog, the 100 recent articles on AI from JACR are displayed in backward chronological order.

• See another Radiology-AI article here: "AI attempts to tack radiology provider shortage," MedCity, nere.  
• See FDA approval documents for the Radiology-AI system GLEAMER for AI-enabled fracture detection, here.
• See a 2021 JAMA article, on the theme, "AI research in COVID is mismatched to the clinic," for example, 84% of clinical studies used CT but only 39% of AI studies.  Here.

Update - See an April 2022 headline, "First autonomous X-ray analyzing AI cleared in the EU," here.  VIZ.AI nabs $100M in new funding, April 2022.  And AIDOC nabs its 9th FDA approval, here.

JACR - Titles About Artificial Intelligence

 - from PubMed - 

Reverse Chronologic from 2022 to 2018

Trivedi, H. (2022). "The Business of Artificial Intelligence in Radiology Has Little to Do With Radiologists." J Am Coll Radiol.

Alkasab, T. K. and B. C. Bizzo (2022). "Response to Drs Sammer, Sher, and Seghers' Letter on "Lessons Learned From the Front Lines of Artificial Intelligence Implementation"." J Am Coll Radiol.

Banja, J. D., et al. (2022). "When Artificial Intelligence Models Surpass Physician Performance: Medical Malpractice Liability in an Era of Advanced Artificial Intelligence." J Am Coll Radiol.

Anderson, A. W., et al. (2022). "Independent External Validation of Artificial Intelligence Algorithms for Automated Interpretation of Screening Mammography: A Systematic Review." J Am Coll Radiol 19(2 Pt A): 259-273.

Dreyer, K. J., et al. (2022). "Real-World Surveillance of FDA-Cleared Artificial Intelligence Models: Rationale and Logistics." J Am Coll Radiol 19(2 Pt A): 274-277.

Sammer, M. B. K., et al. (2022). "Re: "Lessons Learned From the Front Lines of Artificial Intelligence Implementation"." J Am Coll Radiol.

Benjamin, M., et al. (2021). "Accelerating Development and Clinical Deployment of Diagnostic Imaging Artificial Intelligence." J Am Coll Radiol 18(11): 1514-1516.

Alkasab, T. K. and B. C. Bizzo (2021). "Lessons Learned From the Front Lines of Artificial Intelligence Implementation." J Am Coll Radiol 18(11): 1474-1475.

Bizzo, B. C., et al. (2021). "Data Management in Artificial Intelligence-Assisted Radiology Reporting." J Am Coll Radiol 18(11): 1485-1488.

Tartar, M., et al. (2021). "Artificial Intelligence Support for Mammography: In-Practice Clinical Experience." J Am Coll Radiol 18(11): 1510-1513.

Gish, D. S., et al. (2021). "Retrospective Evaluation of Artificial Intelligence Leveraging Free-Text Imaging Order Entry to Facilitate Federally Required Clinical Decision Support." J Am Coll Radiol 18(11): 1476-1484.

Allen, B., et al. (2021). "Evaluation and Real-World Performance Monitoring of Artificial Intelligence Models in Clinical Practice: Try It, Buy It, Check It." J Am Coll Radiol 18(11): 1489-1496.

Jain, R. (2021). "Introducing Artificial Intelligence Applications at Our Community Hospital: A Contrarian Approach." J Am Coll Radiol 18(11): 1506-1509.

Pierce, J. D., et al. (2021). "Seamless Integration of Artificial Intelligence Into the Clinical Environment: Our Experience With a Novel Pneumothorax Detection Artificial Intelligence Algorithm." J Am Coll Radiol 18(11): 1497-1505.

Strand, F., et al. (2021). "A Call for Controlled Validation Data Sets: Promoting the Safe Introduction of Artificial Intelligence in Breast Imaging." J Am Coll Radiol 18(11): 1564-1565.

Weisberg, E. M., et al. (2021). "Using Artificial Intelligence to Interpret CT Scans: Getting Closer to Standard of Care." J Am Coll Radiol 18(11): 1569-1571.

Puri, P. and S. Jha (2021). "Artificial Intelligence, Automation, and Medical Education: Lessons From Economic History." J Am Coll Radiol 18(9): 1345-1347.

Allen, B., et al. (2021). "2020 ACR Data Science Institute Artificial Intelligence Survey." J Am Coll Radiol 18(8): 1153-1159.

Voter, A. F., et al. (2021). "Diagnostic Accuracy and Failure Mode Analysis of a Deep Learning Algorithm for the Detection of Intracranial Hemorrhage." J Am Coll Radiol 18(8): 1143-1152.

Burdorf, B. T. (2021). "A Prospective Applicant's Outlook on Radiology in Light of Artificial Intelligence." J Am Coll Radiol 18(7): 893.

Chonde, D. B., et al. (2021). "RadTranslate: An Artificial Intelligence-Powered Intervention for Urgent Imaging to Enhance Care Equity for Patients With Limited English Proficiency During the COVID-19 Pandemic." J Am Coll Radiol 18(7): 1000-1008.

Wildman-Tobriner, B., et al. (2021). "Missed Incidental Pulmonary Embolism: Harnessing Artificial Intelligence to Assess Prevalence and Improve Quality Improvement Opportunities." J Am Coll Radiol 18(7): 992-999.

Weisberg, E. M., et al. (2021). "Man Versus Machine? Radiologists and Artificial Intelligence Work Better Together." J Am Coll Radiol 18(6): 887-889.

Adams, S. J., et al. (2021). "Development and Cost Analysis of a Lung Nodule Management Strategy Combining Artificial Intelligence and Lung-RADS for Baseline Lung Cancer Screening." J Am Coll Radiol 18(5): 741-751.

Tejani, A. S. (2021). "Identifying and Addressing Barriers to an Artificial Intelligence Curriculum." J Am Coll Radiol 18(4): 605-607.

Purkayastha, S., et al. (2021). "Failures Hiding in Success for Artificial Intelligence in Radiology." J Am Coll Radiol 18(3 Pt B): 517-519.

Larson, D. B., et al. (2021). "Regulatory Frameworks for Development and Evaluation of Artificial Intelligence-Based Diagnostic Imaging Algorithms: Summary and Recommendations." J Am Coll Radiol 18(3 Pt A): 413-424.

Rajiah, P. and P. Bhargava (2021). "Leadership Lessons From Equity Theory: The Interplay Between Radiologist Compensation and Motivation." J Am Coll Radiol 18(1 Pt B): 211-213.

Kotsenas, A. L., et al. (2021). "Rethinking Patient Consent in the Era of Artificial Intelligence and Big Data." J Am Coll Radiol 18(1 Pt B): 180-184.

Thrall, J. H., et al. (2021). "Rethinking the Approach to Artificial Intelligence for Medical Image Analysis: The Case for Precision Diagnosis." J Am Coll Radiol 18(1 Pt B): 174-179.

Ongena, Y. P., et al. (2021). "Artificial Intelligence in Screening Mammography: A Population Survey of Women's Preferences." J Am Coll Radiol 18(1 Pt A): 79-86.

Smith, J., et al. (2021). "The Age of Artificial Intelligence: Does "Why" Still Matter?" J Am Coll Radiol 18(1 Pt A): 87-89.

Slanetz, P. J., et al. (2020). "Artificial Intelligence and Machine Learning in Radiology Education Is Ready for Prime Time." J Am Coll Radiol 17(12): 1705-1707.

Lui, Y. W., et al. (2020). "How to Implement AI in the Clinical Enterprise: Opportunities and Lessons Learned." J Am Coll Radiol 17(11): 1394-1397.

Bhatia, N., et al. (2020). "Artificial Intelligence in Quality Improvement: Reviewing Uses of Artificial Intelligence in Noninterpretative Processes from Clinical Decision Support to Education and Feedback." J Am Coll Radiol 17(11): 1382-1387.

Tariq, A., et al. (2020). "Current Clinical Applications of Artificial Intelligence in Radiology and Their Best Supporting Evidence." J Am Coll Radiol 17(11): 1371-1381.

Kapoor, N., et al. (2020). "Workflow Applications of Artificial Intelligence in Radiology and an Overview of Available Tools." J Am Coll Radiol 17(11): 1363-1370.

Filice, R. W., et al. (2020). "Evaluating Artificial Intelligence Systems to Guide Purchasing Decisions." J Am Coll Radiol 17(11): 1405-1409.

Kottler, N. (2020). "Artificial Intelligence: A Private Practice Perspective." J Am Coll Radiol 17(11): 1398-1404.

Simpson, S. A. and T. S. Cook (2020). "Artificial Intelligence and the Trainee Experience in Radiology." J Am Coll Radiol 17(11): 1388-1393.

Goehler, A., et al. (2020). "Three-Dimensional Neural Network to Automatically Assess Liver Tumor Burden Change on Consecutive Liver MRIs." J Am Coll Radiol 17(11): 1475-1484.

Fishman, E. K., et al. (2020). "Mapping Your Career in the Era of Artificial Intelligence: It's Up to You, Not Google." J Am Coll Radiol 17(11): 1537-1538.

Fleishon, H. B. and C. Wald (2020). "Patient Safety: Considerations for Artificial Intelligence Implementation in Radiology." J Am Coll Radiol 17(10): 1192-1193.

Enzmann, D. R., et al. (2020). "Radiology's Information Architecture Could Migrate to One Emulating That of Smartphones." J Am Coll Radiol 17(10): 1299-1306.

Chu, L. C., et al. (2020). "The Potential Dangers of Artificial Intelligence for Radiology and Radiologists." J Am Coll Radiol 17(10): 1309-1311.

Woloshyn, O., et al. (2020). "Found in Translation: Unpacking the Artificial Intelligence Revolution That Has Already Arrived." J Am Coll Radiol 17(10): 1307-1308.

Lotan, E., et al. (2020). "Medical Imaging and Privacy in the Era of Artificial Intelligence: Myth, Fallacy, and the Future." J Am Coll Radiol 17(9): 1159-1162.

Adams, S. J., et al. (2020). "Patient Perspectives and Priorities Regarding Artificial Intelligence in Radiology: Opportunities for Patient-Centered Radiology." J Am Coll Radiol 17(8): 1034-1036.

Montaque, T., et al. (2020). "The Future of Digital Communication: Improved Messaging Context, Artificial Intelligence, and Your Privacy." J Am Coll Radiol 17(6): 821-823.

Kambadakone, A. (2020). "Artificial Intelligence and CT Image Reconstruction: Potential of a New Era in Radiation Dose Reduction." J Am Coll Radiol 17(5): 649-651.

Sigler, R., et al. (2020). "The Importance of Data Analytics and Business Intelligence for Radiologists." J Am Coll Radiol 17(4): 511-514.

Allen, B., et al. (2020). "Integrating Artificial Intelligence Into Radiologic Practice: A Look to the Future." J Am Coll Radiol 17(2): 280-283.

Fernandez, C., et al. (2020). "Feasibility and Impact of Emotional Intelligence Evaluation in Radiation Oncology Residency Interviews." J Am Coll Radiol 17(2): 289-292.

Valtchinov, V. I., et al. (2020). "Comparing Artificial Intelligence Approaches to Retrieve Clinical Reports Documenting Implantable Devices Posing MRI Safety Risks." J Am Coll Radiol 17(2): 272-279.

Mayo, R. C., et al. (2020). "Financing Artificial Intelligence in Medical Imaging: Show Me the Money." J Am Coll Radiol 17(1 Pt B): 175-177.

Browning, T., et al. (2020). "Special Considerations for Integrating Artificial Intelligence Solutions in Urban Safety-Net Hospitals." J Am Coll Radiol 17(1 Pt B): 171-174.

Alexander, A., et al. (2020). "An Intelligent Future for Medical Imaging: A Market Outlook on Artificial Intelligence for Medical Imaging." J Am Coll Radiol 17(1 Pt B): 165-170.

Geis, J. R., et al. (2019). "Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement." J Am Coll Radiol 16(11): 1516-1521.

Burdorf, B. (2019). "A Medical Student's Outlook on Radiology in Light of Artificial Intelligence." J Am Coll Radiol 16(11): 1514-1515.

Allen, B., Jr. (2019). "Machine Learning With Deep Neural Nets Artificially Augmenting My Intelligence in a Narrow but Occasionally Superhuman Kind of Way." J Am Coll Radiol 16(10): 1480-1481.

Kohli, M., et al. (2019). "Bending the Artificial Intelligence Curve for Radiology: Informatics Tools From ACR and RSNA." J Am Coll Radiol 16(10): 1464-1470.

Haan, M., et al. (2019). "A Qualitative Study to Understand Patient Perspective on the Use of Artificial Intelligence in Radiology." J Am Coll Radiol 16(10): 1416-1419.

Golding, L. P. and G. N. Nicola (2019). "A Business Case for Artificial Intelligence Tools: The Currency of Improved Quality and Reduced Cost." J Am Coll Radiol 16(9 Pt B): 1357-1361.

Bizzo, B. C., et al. (2019). "Artificial Intelligence and Clinical Decision Support for Radiologists and Referring Providers." J Am Coll Radiol 16(9 Pt B): 1351-1356.

Pisano, E. D. and L. R. Garnett (2019). "Big Data and Radiology Research." J Am Coll Radiol 16(9 Pt B): 1347-1350.

Akkus, Z., et al. (2019). "A Survey of Deep-Learning Applications in Ultrasound: Artificial Intelligence-Powered Ultrasound for Improving Clinical Workflow." J Am Coll Radiol 16(9 Pt B): 1318-1328.

Rubin, D. L. (2019). "Artificial Intelligence in Imaging: The Radiologist's Role." J Am Coll Radiol 16(9 Pt B): 1309-1317.

Filice, R. W. (2019). "Radiology-Pathology Correlation to Facilitate Peer Learning: An Overview Including Recent Artificial Intelligence Methods." J Am Coll Radiol 16(9 Pt B): 1279-1285.

Pillai, M., et al. (2019). "Using Artificial Intelligence to Improve the Quality and Safety of Radiation Therapy." J Am Coll Radiol 16(9 Pt B): 1267-1272.

Vey, B. L., et al. (2019). "The Role of Generative Adversarial Networks in Radiation Reduction and Artifact Correction in Medical Imaging." J Am Coll Radiol 16(9 Pt B): 1273-1278.

Makeeva, V., et al. (2019). "The Application of Machine Learning to Quality Improvement Through the Lens of the Radiology Value Network." J Am Coll Radiol 16(9 Pt B): 1254-1258.

Martín Noguerol, T., et al. (2019). "Strengths, Weaknesses, Opportunities, and Threats Analysis of Artificial Intelligence and Machine Learning Applications in Radiology." J Am Coll Radiol 16(9 Pt B): 1239-1247.

Pfeifer, C. M. (2019). "Limitations of Ascribing Autonomy, Purpose, and Mastery as Primary Physician Motivators." J Am Coll Radiol 16(9 Pt A): 1130-1131.

Larson, D. B. and G. W. Boland (2019). "Imaging Quality Control in the Era of Artificial Intelligence." J Am Coll Radiol 16(9 Pt B): 1259-1266.

Luh, J. Y., et al. (2019). "Clinical Documentation and Patient Care Using Artificial Intelligence in Radiation Oncology." J Am Coll Radiol 16(9 Pt B): 1343-1346.

Filice, R. W. (2019). "Deep-Learning Language-Modeling Approach for Automated, Personalized, and Iterative Radiology-Pathology Correlation." J Am Coll Radiol 16(9 Pt B): 1286-1291.

Allen, B., Jr., et al. (2019). "A Road Map for Translational Research on Artificial Intelligence in Medical Imaging: From the 2018 National Institutes of Health/RSNA/ACR/The Academy Workshop." J Am Coll Radiol 16(9 Pt A): 1179-1189.

Mazurowski, M. A. (2019). "Artificial Intelligence May Cause a Significant Disruption to the Radiology Workforce." J Am Coll Radiol 16(8): 1077-1082.

Allen, B., et al. (2019). "Democratizing AI." J Am Coll Radiol 16(7): 961-963.

Feng, Q. X., et al. (2019). "An Intelligent Clinical Decision Support System for Preoperative Prediction of Lymph Node Metastasis in Gastric Cancer." J Am Coll Radiol 16(7): 952-960.

Harrington, S. G. and M. K. Johnson (2019). "The FDA and Artificial Intelligence in Radiology: Defining New Boundaries." J Am Coll Radiol 16(5): 743-744.

Allen, B. and K. Dreyer (2019). "The Role of the ACR Data Science Institute in Advancing Health Equity in Radiology." J Am Coll Radiol 16(4 Pt B): 644-648.

McIntosh-Clarke, D. R., et al. (2019). "Incentivizing Physician Diversity in Radiology." J Am Coll Radiol 16(4 Pt B): 624-630.

Wang, S. S., et al. (2019). "The Resilient Radiologist: You Will Still Feel the Burn." J Am Coll Radiol 16(4 Pt A): 523-525.

Alexander, A., et al. (2019). "Scanning the Future of Medical Imaging." J Am Coll Radiol 16(4 Pt A): 501-507.

Sensakovic, W. F. and M. Mahesh (2019). "Role of the Medical Physicist in the Health Care Artificial Intelligence Revolution." J Am Coll Radiol 16(3): 393-394.

Allen, B. (2019). "The Role of the FDA in Ensuring the Safety and Efficacy of Artificial Intelligence Software and Devices." J Am Coll Radiol 16(2): 208-210.

Powell, K., et al. (2019). "What Health Care Can Learn From Self-Driving Vehicles." J Am Coll Radiol 16(2): 261-263.

Ghosh, A. (2019). "Artificial Intelligence Using Open Source BI-RADS Data Exemplifying Potential Future Use." J Am Coll Radiol 16(1): 64-72.

Allen, B. (2018). "How Structured Use Cases Can Drive the Adoption of Artificial Intelligence Tools in Clinical Practice." J Am Coll Radiol 15(12): 1758-1760.

Collado-Mesa, F., et al. (2018). "The Role of Artificial Intelligence in Diagnostic Radiology: A Survey at a Single Radiology Residency Training Program." J Am Coll Radiol 15(12): 1753-1757.

Allen, B. and K. Dreyer (2018). "The Artificial Intelligence Ecosystem for the Radiological Sciences: Ideas to Clinical Practice." J Am Coll Radiol 15(10): 1455-1457.

Schoppe, K. (2018). "Artificial Intelligence: Who Pays and How?" J Am Coll Radiol 15(9): 1240-1242.

Kohli, M. and R. Geis (2018). "Ethics, Artificial Intelligence, and Radiology." J Am Coll Radiol 15(9): 1317-1319.

Nguyen, G. K. and A. S. Shetty (2018). "Artificial Intelligence and Machine Learning: Opportunities for Radiologists in Training." J Am Coll Radiol 15(9): 1320-1321.

Sana, M. (2018). "Machine Learning and Artificial Intelligence in Radiology." J Am Coll Radiol 15(8): 1139-1142.

Schier, R. (2018). "Artificial Intelligence and the Practice of Radiology: An Alternative View." J Am Coll Radiol 15(7): 1004-1007.

Yi, P. H., et al. (2018). "Artificial Intelligence and Radiology: Collaboration Is Key." J Am Coll Radiol 15(5): 781-783.

Dreyer, K. and B. Allen (2018). "Artificial Intelligence in Health Care: Brave New World or Golden Opportunity?" J Am Coll Radiol 15(4): 655-657.

Brink, J. A. (2018). "Artificial Intelligence for Operations: The Untold Story." J Am Coll Radiol 15(3 Pt A): 375-377.

Thrall, J. H., et al. (2018). "Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success." J Am Coll Radiol 15(3 Pt B): 504-508.

Carlos, R. C., et al. (2018). "Data Science: Big Data, Machine Learning, and Artificial Intelligence." J Am Coll Radiol 15(3 Pt B): 497-498.

Syeda-Mahmood, T. (2018). "Role of Big Data and Machine Learning in Diagnostic Decision Support in Radiology." J Am Coll Radiol 15(3 Pt B): 569-576.

Balthazar, P., et al. (2018). "Protecting Your Patients' Interests in the Era of Big Data, Artificial Intelligence, and Predictive Analytics." J Am Coll Radiol 15(3 Pt B): 580-586.

Jha, S. and E. J. Topol (2018). "Information and Artificial Intelligence." J Am Coll Radiol 15(3 Pt B): 509-511.

McGinty, G. B. and B. Allen, Jr. (2018). "The ACR Data Science Institute and AI Advisory Group: Harnessing the Power of Artificial Intelligence to Improve Patient Care." J Am Coll Radiol 15(3 Pt B): 577-579.

Giger, M. L. (2018). "Machine Learning in Medical Imaging." J Am Coll Radiol 15(3 Pt B): 512-520.

King, B. F., Jr. (2018). "Artificial Intelligence and Radiology: What Will the Future Hold?" J Am Coll Radiol 15(3 Pt B): 501-503.

Kirk, I. R., et al. (2018). "The Triumph of the Machines." J Am Coll Radiol 15(3 Pt B): 587-588.

Lakhani, P., et al. (2018). "Machine Learning in Radiology: Applications Beyond Image Interpretation." J Am Coll Radiol 15(2): 350-359.

Recht, M. and R. N. Bryan (2017). "Artificial Intelligence: Threat or Boon to Radiologists?" J Am Coll Radiol 14(11): 1476-1480.