 Connection
Jayashree Kalpathy-Cramer to Diagnostic Imaging
This is a "connection" page, showing publications Jayashree Kalpathy-Cramer has written about Diagnostic Imaging.
|
|
| |
Connection Strength |
|
 |
|
 |
| |
2.359 |
|
|
|
-
Chang K, Balachandar N, Lam C, Yi D, Brown J, Beers A, Rosen B, Rubin DL, Kalpathy-Cramer J. Distributed deep learning networks among institutions for medical imaging. J Am Med Inform Assoc. 2018 08 01; 25(8):945-954.
Score: 0.514
-
Kalpathy-Cramer J, Bedrick S, Radhouani S, Hersh W, Eggel I, Kahn CE, M?ller H. Retrieving similar cases from the medical literature - the ImageCLEF experience. Stud Health Technol Inform. 2010; 160(Pt 2):1189-93.
Score: 0.284
-
Hersh W, M?ller H, Kalpathy-Cramer J. The ImageCLEFmed medical image retrieval task test collection. J Digit Imaging. 2009 Dec; 22(6):648-55.
Score: 0.259
-
Kalpathy-Cramer J, Hersh W. Automatic image modality based classification and annotation to improve medical image retrieval. Stud Health Technol Inform. 2007; 129(Pt 2):1334-8.
Score: 0.230
-
Balachandar N, Chang K, Kalpathy-Cramer J, Rubin DL. Accounting for data variability in multi-institutional distributed deep learning for medical imaging. J Am Med Inform Assoc. 2020 05 01; 27(5):700-708.
Score: 0.145
-
Bellsmith KN, Brown J, Kim SJ, Goldstein IH, Coyner A, Ostmo S, Gupta K, Chan RVP, Kalpathy-Cramer J, Chiang MF, Campbell JP. Aggressive Posterior Retinopathy of Prematurity: Clinical and Quantitative Imaging Features in a Large North American Cohort. Ophthalmology. 2020 08; 127(8):1105-1112.
Score: 0.143
-
Langlotz CP, Allen B, Erickson BJ, Kalpathy-Cramer J, Bigelow K, Cook TS, Flanders AE, Lungren MP, Mendelson DS, Rudie JD, Wang G, Kandarpa K. A Roadmap for Foundational Research on Artificial Intelligence in Medical Imaging: From the 2018 NIH/RSNA/ACR/The Academy Workshop. Radiology. 2019 06; 291(3):781-791.
Score: 0.135
-
Obuchowski NA, Barnhart HX, Buckler AJ, Pennello G, Wang XF, Kalpathy-Cramer J, Kim HJ, Reeves AP. Statistical issues in the comparison of quantitative imaging biomarker algorithms using pulmonary nodule volume as an example. Stat Methods Med Res. 2015 Feb; 24(1):107-40.
Score: 0.096
-
Obuchowski NA, Reeves AP, Huang EP, Wang XF, Buckler AJ, Kim HJ, Barnhart HX, Jackson EF, Giger ML, Pennello G, Toledano AY, Kalpathy-Cramer J, Apanasovich TV, Kinahan PE, Myers KJ, Goldgof DB, Barboriak DP, Gillies RJ, Schwartz LH, Sullivan DC. Quantitative imaging biomarkers: a review of statistical methods for computer algorithm comparisons. Stat Methods Med Res. 2015 Feb; 24(1):68-106.
Score: 0.096
-
Fedorov A, Beichel R, Kalpathy-Cramer J, Finet J, Fillion-Robin JC, Pujol S, Bauer C, Jennings D, Fennessy F, Sonka M, Buatti J, Aylward S, Miller JV, Pieper S, Kikinis R. 3D Slicer as an image computing platform for the Quantitative Imaging Network. Magn Reson Imaging. 2012 Nov; 30(9):1323-41.
Score: 0.084
-
Kahn CE, Kalpathy-Cramer J, Lam CA, Eldredge CE. Accurate determination of imaging modality using an ensemble of text- and image-based classifiers. J Digit Imaging. 2012 Feb; 25(1):37-42.
Score: 0.082
-
M?ller H, Kalpathy-Cramer J, Hersh W, Geissbuhler A. Using medline queries to generate image retrieval tasks for benchmarking. Stud Health Technol Inform. 2008; 136:523-8.
Score: 0.062
-
Zhang M, Qu L, Singh P, Kalpathy-Cramer J, Rubin DL. SplitAVG: A Heterogeneity-Aware Federated Deep Learning Method for Medical Imaging. IEEE J Biomed Health Inform. 2022 09; 26(9):4635-4644.
Score: 0.043
-
Cole ED, Park SH, Kim SJ, Kang KB, Valikodath NG, Al-Khaled T, Patel SN, Jonas KE, Ostmo S, Coyner A, Berrocal A, Drenser KA, Nagiel A, Horowitz JD, Lee TC, Kalpathy-Cramer J, Chiang MF, Campbell JP, Chan RVP. Variability in Plus Disease Diagnosis using Single and Serial Images. Ophthalmol Retina. 2022 12; 6(12):1122-1129.
Score: 0.042
-
Lu C, Hanif A, Singh P, Chang K, Coyner AS, Brown JM, Ostmo S, Chan RVP, Rubin D, Chiang MF, Campbell JP, Kalpathy-Cramer J. Federated Learning for Multicenter Collaboration in Ophthalmology: Improving Classification Performance in Retinopathy of Prematurity. Ophthalmol Retina. 2022 08; 6(8):657-663.
Score: 0.041
-
Campbell JP, Chiang MF, Chen JS, Moshfeghi DM, Nudleman E, Ruambivoonsuk P, Cherwek H, Cheung CY, Singh P, Kalpathy-Cramer J, Ostmo S, Eydelman M, Chan RVP, Capone A. Artificial Intelligence for Retinopathy of Prematurity: Validation of a Vascular Severity Scale against International Expert Diagnosis. Ophthalmology. 2022 07; 129(7):e69-e76.
Score: 0.041
-
Fedorov A, Beichel R, Kalpathy-Cramer J, Clunie D, Onken M, Riesmeier J, Herz C, Bauer C, Beers A, Fillion-Robin JC, Lasso A, Pinter C, Pieper S, Nolden M, Maier-Hein K, Herrmann MD, Saltz J, Prior F, Fennessy F, Buatti J, Kikinis R. Quantitative Imaging Informatics for Cancer Research. JCO Clin Cancer Inform. 2020 05; 4:444-453.
Score: 0.036
-
Ataer-Cansizoglu E, Kalpathy-Cramer J, You S, Keck K, Erdogmus D, Chiang MF. Analysis of underlying causes of inter-expert disagreement in retinopathy of prematurity diagnosis. Application of machine learning principles. Methods Inf Med. 2015; 54(1):93-102.
Score: 0.025
|
Connection Strength
The connection strength for concepts is the sum of the scores for each matching publication.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
|