K. Dreyer

发表

Extraction of recommendation features in radiology with natural language processing: exploratory study.

Pragya A. Dang, M. Kalra, E. Halpern, 2008, AJR. American journal of roentgenology.

Decision support for radiologist report recommendations.

James H Thrall, Tarik K Alkasab, Keith J Dreyer, 2011, Journal of the American College of Radiology : JACR.

Artificial intelligence in radiology: the ecosystem essential to improving patient care.

K. Dreyer, Bibb Allen, G. McGinty, 2020, Clinical imaging.

Current Applications and Future Impact of Machine Learning in Radiology.

Oleg S. Pianykh, Mark H. Michalski, A. Samir, 2018, Radiology.

When Machines Think: Radiology's Next Frontier.

K. Dreyer, J. R. Geis, 2017, Radiology.

Federated Learning used for predicting outcomes in SARS-COV-2 patients

Colin B. Compas, Yu Rim Lee, Mona G. Flores, 2021, Research square.

Clinical deployment and validation of a radiology artificial intelligence system for COVID-19

Matthew D. Li, Jayashree Kalpathy-Cramer, K. Andriole, 2020 .

Effect of computerized order entry with integrated decision support on the growth of outpatient procedure volumes: seven-year time series analysis.

James H Thrall, Keith J Dreyer, Pragya A. Dang, 2009, Radiology.

Do picture archiving and communication systems improve Report turnaround times?

Keith Dreyer, K. Dreyer, G. Boland, 2009, Journal of Digital Imaging.

Use of Imaging Appropriateness Criteria for Decision Support During Radiology Order Entry: The MGH Experience

J. Thrall, J. Weilburg, K. Dreyer, 2014 .

Federated Learning for Breast Density Classification: A Real-World Implementation pdf

Daguang Xu, Jesse Tetreault, Ahmed Harouni, 2020, DART/DCL@MICCAI.

PATHOLOGY INFORMATICS SUMMIT 2018

David E. Breen, William B. Lober, Hamid R. Tizhoosh, 2018, Journal of Pathology Informatics.

When does a radiologist's recommendation for follow-up result in high-cost imaging?

M. Chatterji, P. Hahn, J. Thrall, 2012, Radiology.

Validation pipeline for machine learning algorithm assessment for multiple vendors

Katherine P. Andriole, Mark H. Michalski, Tarik K. Alkasab, 2022, PloS one.

Images of imaging: how to process and display imaging utilization for large populations.

T. Ferris, J. Weilburg, K. Dreyer, 2015, AJR. American journal of roentgenology.

Implementing the DICOM Standard for Digital Pathology

Ron Kikinis, Katherine P. Andriole, Keith J. Dreyer, 2018, Journal of pathology informatics.

A review of current concepts and practices

Flint, J., M., 2020 .

Utilization Management of High-Cost Imaging in an Outpatient Setting in a Large Stable Patient and Provider Cohort over 7 Years.

T. Ferris, J. Thrall, J. Weilburg, 2017, Radiology.

Provider Feedback about Imaging Appropriateness by Using Scores from Order Entry Decision Support: Raw Rates Misclassify Outliers.

T. Ferris, J. Weilburg, K. Dreyer, 2015, Radiology.

Does radiologist recommendation for follow-up with the same imaging modality contribute substantially to high-cost imaging volume?

A. Saokar, P. Hahn, J. Thrall, 2007, Radiology.

Integrating artificial intelligence into the clinical practice of radiology: challenges and recommendations

Barbara Prainsack, Wiro Niessen, Marc Dewey, 2020, European Radiology.

Appropriateness, Scheduling, and Patient

K. Dreyer, R. Duszak, G. Boland, 2014 .

10 TH ANNIVERSARY MUSINGS 394 Imaging Informatics : Lead , Follow , or Become Irrelevant

K. Dreyer, J. Dreyer, 2013 .

Recommendations for additional imaging in radiology reports: multifactorial analysis of 5.9 million examinations.

James H Thrall, Keith J Dreyer, Giles W Boland, 2009, Radiology.

Auto-Detection of Motion Artifacts on CT Pulmonary Angiograms with a Physician-Trained AI Algorithm

M. Kalra, S. Digumarthy, K. Dreyer, 2022, medRxiv.

Performance of a Chest Radiography AI Algorithm for Detection of Missed or Mislabeled Findings: A Multicenter Study

M. Kalra, Preetham Putha, S. Digumarthy, 2022, Diagnostics.

Real-World Surveillance of FDA-Cleared Artificial Intelligence Models: Rationale and Logistics.

K. Dreyer, Bibb Allen, C. Wald, 2021, Journal of the American College of Radiology : JACR.

Association of Artificial Intelligence–Aided Chest Radiograph Interpretation With Reader Performance and Efficiency

M. Kalra, V. Muse, S. Digumarthy, 2022, JAMA network open.

Machine Learning for Adrenal Gland Segmentation and Classification of Normal and Adrenal Masses at CT.

Katherine P. Andriole, Jayashree Kalpathy-Cramer, D. Glazer, 2022, Radiology.

Proceedings from the first Global Summit on Radiological Quality and Safety.

P. Vock, G. Frija, P. Mildenberger, 2014, Journal of the American College of Radiology : JACR.

Large-Scale Model Validation in Healthcare White Paper

Colin B. Compas, Katherine P. Andriole, Matthew D. Li, 2022 .

Evaluation of an artificial intelligence model for detection of pneumothorax and tension pneumothorax on chest radiograph

V. Muse, S. Digumarthy, K. Dreyer, 2022, medRxiv.

Implementation of Clinical Artificial Intelligence in Radiology: Who Decides and How?

Tarik K. Alkasab, Walter F. Wiggins, D. Daye, 2022, Radiology.

Frequency of Missed Findings on Chest Radiographs (CXRs) in an International, Multicenter Study: Application of AI to Reduce Missed Findings

M. Kalra, Preetham Putha, S. Digumarthy, 2022, Diagnostics.

Head CT deep learning model is highly accurate for early infarct estimation

Katherine P. Andriole, Walter F. Wiggins, F. Kitamura, 2023, Scientific Reports.

Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success.

James H Thrall, Quanzheng Li, Xiang Li, 2018, Journal of the American College of Radiology : JACR.

Machine Learning in Radiology: Applications Beyond Image Interpretation.

Luciano M Prevedello, C Matthew Hawkins, Jose Morey, 2017, Journal of the American College of Radiology : JACR.

Assessing the Utility of ChatGPT Throughout the Entire Clinical Workflow

A. Landman, K. Dreyer, M. Succi, 2023, medRxiv.

Artificial Intelligence has Similar Performance to Subjective Assessment of Emphysema Severity on Chest CT.

M. Kalra, S. Digumarthy, A. Primak, 2021, Academic radiology.

Discrepancies in reporting the vertebral level of abnormality in MR of the spine.

M. Kalra, A. Yoo, Rajiv Gupta, 2009, Journal of the American College of Radiology : JACR.

PACS: A Guide to the Digital Revolution

Amit Mehta, Keith J. Dreyer, James H. Thrall, 2005 .

Radiology order entry with decision support: initial clinical experience.

James H Thrall, Keith J Dreyer, Daniel I Rosenthal, 2006, Journal of the American College of Radiology : JACR.

Federated Learning for Breast Density Classification: A Real-World Implementation

Colin B. Compas, Richard D. White, Mona G. Flores, 2020, DART/DCL@MICCAI.

FDA-regulated AI Algorithms: Trends, Strengths, and Gaps of Validation Studies.

M. Kalra, K. Dreyer, B. Bizzo, 2021, Academic radiology.

Addressing the Challenges of Implementing Artificial Intelligence Tools in Clinical Practice: Principles From Experience.

Tarik K. Alkasab, M. Kalra, Thomas J. Schultz, 2023, Journal of the American College of Radiology : JACR.

Complex Relationship Between Artificial Intelligence and CT Radiation Dose.

M. Kalra, A. Primak, K. Dreyer, 2021, Academic radiology.

Suboptimal Chest Radiography and Artificial Intelligence: The Problem and the Solution

M. Kalra, L. Saba, K. Dreyer, 2023, Diagnostics.

Multi-Institutional Assessment and Crowdsourcing Evaluation of Deep Learning for Automated Classification of Breast Density.

Ken Chang, Jayashree Kalpathy-Cramer, Laura Brink, 2020, Journal of the American College of Radiology : JACR.

Quantitative analysis of cardiac imaging using expert systems

Keith J. Dreyer, A. C. Held, Joseph Simko, 1991, Medical Imaging.

Segmenting Echocardiographic Image Sequences Using Expert Labeling

Ishwar K. Sethi, Keith J. Dreyer, A. C. Held, 1990, Other Conferences.

The imaging 3.0 informatics scorecard.

Keith J Dreyer, J Raymond Geis, Marc Kohli, 2015, Journal of the American College of Radiology : JACR.

Reengineering the radiology enterprise: a summary of the 2014 Intersociety Committee Summer Conference.

J. Seibert, R. Zane, G. Dodd, 2015, Journal of the American College of Radiology : JACR.

Expanding Role of Certified Electronic Health Records Technology in Radiology: The MACRA Mandate.

M. Recht, A. Rosenkrantz, J. Hirsch, 2018, Journal of the American College of Radiology : JACR.

Provider Feedback about imaging appropriateness by Using s cores from Order entry Decision s upport: Raw Rates

Chris L. Sistrom, Jeffrey B. Weilburg, Keith J. Dreyer, 2015 .

Application of Recently Developed Computer Algorithm for Automatic Classification of Unstructured Radiology Reports: Validation Study 1

James H Thrall, Thomas Schultz, Keith J Dreyer, 2004 .

The Role of an Artificial Intelligence Ecosystem in Radiology

Keith J. Dreyer, Bibb Allen, Robert Gish, 2019, Artificial Intelligence in Medical Imaging.

Automatic segmentation and measurement of tracheal collapsibility in tracheomalacia.

M. Kalra, S. Digumarthy, K. Dreyer, 2022, Clinical imaging.

Performance of threshold-based stone segmentation and radiomics for determining the composition of kidney stones from single-energy CT

M. Kalra, A. Primak, S. Saini, 2022, Japanese Journal of Radiology.

Implementation of Clinical Artificial Intelligence in Radiology: Who Decides and How?

Tarik K. Alkasab, Walter F. Wiggins, D. Daye, 2022, Radiology.

Errare humanum est: frequency of laterality errors in radiology reports.

Keith J Dreyer, Mannudeep K Kalra, M. Kalra, 2009, AJR. American journal of roentgenology.

Clinical imaging guidelines part 4: challenges in identifying, engaging and collaborating with stakeholders.

Madan M. Rehani, M. Bettmann, M. Rehani, 2015, Journal of the American College of Radiology : JACR.

Radiologist-Trained AI Model for Identifying Suboptimal Chest-Radiographs.

M. Kalra, S. Digumarthy, K. Dreyer, 2023, Academic Radiology.

Predictive values of AI-based triage model in suboptimal CT pulmonary angiography.

M. Kalra, Fatemeh Homayounieh, S. Digumarthy, 2022, Clinical imaging.

Provider Feedback about Imaging Appropriateness by Using Scores from Order Entry Decision Support: Raw Rates Misclassify Outliers.

T. Ferris, J. Weilburg, K. Dreyer, 2015, Radiology.

Utilization Management of High-Cost Imaging in an Outpatient Setting in a Large Stable Patient and Provider Cohort over 7 Years.

T. Ferris, J. Thrall, J. Weilburg, 2017, Radiology.

Viewing Imaging Studies: How Patient Location and Imaging Site Affect Referring Physicians

Fatemeh Homayounieh, Mannudeep K. Kalra, Keith J. Dreyer, 2019, Journal of Digital Imaging.

A Case Tracking System with Electronic Medical Record Integration to Automate Outcome Tracking for Radiologists

Mitchell A. Harris, Keith J. Dreyer, Daniel I. Rosenthal, 2009, Journal of Digital Imaging.

Meaningful use for radiology: current status and future directions.

Ramin Khorasani, David E Avrin, Ronald L Arenson, 2013, Radiology.

Using Microsoft PowerPoint for electronic presentations.

K. Dreyer, 2001, Radiographics : a review publication of the Radiological Society of North America, Inc.

Use of Radcube for Extraction of Finding Trends in a Large Radiology Practice

Mannudeep K. Kalra, Michael A. Blake, Keith J. Dreyer, 2009, Journal of Digital Imaging.

Natural language processing using online analytic processing for assessing recommendations in radiology reports.

Keith J Dreyer, Pragya A. Dang, Markus Stout, 2008, Journal of the American College of Radiology : JACR.

Big Data and Machine Learning-Strategies for Driving This Bus: A Summary of the 2016 Intersociety Summer Conference.

Paul Nagy, J Raymond Geis, Jonathan B Kruskal, 2017, Journal of the American College of Radiology : JACR.