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Items: 1 to 50 of 254

1.

A New Multimodel Machine Learning Framework to Improve Hepatic Fibrosis Grading Using Ultrasound Elastography Systems from Different Vendors.

Durot I, Akhbardeh A, Sagreiya H, Loening AM, Rubin DL.

Ultrasound Med Biol. 2019 Oct 11. pii: S0301-5629(19)31504-2. doi: 10.1016/j.ultrasmedbio.2019.09.004. [Epub ahead of print]

PMID:
31611074
2.

Geographic atrophy segmentation in SD-OCT images using synthesized fundus autofluorescence imaging.

Wu M, Cai X, Chen Q, Ji Z, Niu S, Leng T, Rubin DL, Park H.

Comput Methods Programs Biomed. 2019 Sep 28;182:105101. doi: 10.1016/j.cmpb.2019.105101. [Epub ahead of print]

PMID:
31600644
3.

Natural Language Processing Approaches to Detect the Timeline of Metastatic Recurrence of Breast Cancer.

Banerjee I, Bozkurt S, Caswell-Jin JL, Kurian AW, Rubin DL.

JCO Clin Cancer Inform. 2019 Oct;3:1-12. doi: 10.1200/CCI.19.00034.

4.

Lower Extremity Venous Stent Placement: A Large Retrospective Single-Center Analysis.

Mabud TS, Cohn DM, Arendt VA, Jeon GS, An X, Fu J, Souffrant AD, Sailer AM, Shah R, Wang D, Sze DY, Kuo WT, Rubin DL, Hofmann LV.

J Vasc Interv Radiol. 2019 Sep 18. pii: S1051-0443(19)30573-1. doi: 10.1016/j.jvir.2019.06.011. [Epub ahead of print]

PMID:
31542273
5.

Automated Quantitative Imaging Measurements of Disease Severity in Patients with Nonthrombotic Iliac Vein Compression.

Reposar AL, Mabud TS, Eifler AC, Hoogi A, Arendt V, Cohn DM, Rubin DL, Hofmann LV.

J Vasc Interv Radiol. 2019 Sep 18. pii: S1051-0443(19)30428-2. doi: 10.1016/j.jvir.2019.04.034. [Epub ahead of print]

PMID:
31542272
6.

Artificial Intelligence in Imaging: The Radiologist's Role.

Rubin DL.

J Am Coll Radiol. 2019 Sep;16(9 Pt B):1309-1317. doi: 10.1016/j.jacr.2019.05.036.

PMID:
31492409
7.

Putting the data before the algorithm in big data addressing personalized healthcare.

Cahan EM, Hernandez-Boussard T, Thadaney-Israni S, Rubin DL.

NPJ Digit Med. 2019 Aug 19;2:78. doi: 10.1038/s41746-019-0157-2. eCollection 2019. Review.

8.

Automatic Staging of Cancer Tumors Using AIM Image Annotations and Ontologies.

Luque EF, Miranda N, Rubin DL, Moreira DA.

J Digit Imaging. 2019 Aug 8. doi: 10.1007/s10278-019-00251-x. [Epub ahead of print]

PMID:
31396778
9.

Development and Performance of the Pulmonary Embolism Result Forecast Model (PERFORM) for Computed Tomography Clinical Decision Support.

Banerjee I, Sofela M, Yang J, Chen JH, Shah NH, Ball R, Mushlin AI, Desai M, Bledsoe J, Amrhein T, Rubin DL, Zamanian R, Lungren MP.

JAMA Netw Open. 2019 Aug 2;2(8):e198719. doi: 10.1001/jamanetworkopen.2019.8719.

10.

Is it possible to automatically assess pretreatment digital rectal examination documentation using natural language processing? A single-centre retrospective study.

Bozkurt S, Kan KM, Ferrari MK, Rubin DL, Blayney DW, Hernandez-Boussard T, Brooks JD.

BMJ Open. 2019 Jul 18;9(7):e027182. doi: 10.1136/bmjopen-2018-027182.

11.

Automated Detection of Measurements and Their Descriptors in Radiology Reports Using a Hybrid Natural Language Processing Algorithm.

Bozkurt S, Alkim E, Banerjee I, Rubin DL.

J Digit Imaging. 2019 Aug;32(4):544-553. doi: 10.1007/s10278-019-00237-9.

12.

Point Shear Wave Elastography Using Machine Learning to Differentiate Renal Cell Carcinoma and Angiomyolipoma.

Sagreiya H, Akhbardeh A, Li D, Sigrist R, Chung BI, Sonn GA, Tian L, Rubin DL, Willmann JK.

Ultrasound Med Biol. 2019 Aug;45(8):1944-1954. doi: 10.1016/j.ultrasmedbio.2019.04.009. Epub 2019 May 25.

PMID:
31133445
13.

Weakly supervised natural language processing for assessing patient-centered outcome following prostate cancer treatment.

Banerjee I, Li K, Seneviratne M, Ferrari M, Seto T, Brooks JD, Rubin DL, Hernandez-Boussard T.

JAMIA Open. 2019 Apr;2(1):150-159. doi: 10.1093/jamiaopen/ooy057. Epub 2019 Jan 4.

14.

Imaging, Genetic, and Demographic Factors Associated With Conversion to Neovascular Age-Related Macular Degeneration: Secondary Analysis of a Randomized Clinical Trial.

Hallak JA, de Sisternes L, Osborne A, Yaspan B, Rubin DL, Leng T.

JAMA Ophthalmol. 2019 Jul 1;137(7):738-744. doi: 10.1001/jamaophthalmol.2019.0868.

PMID:
31021381
15.

Reproductive Factors and Mammographic Density: Associations Among 24,840 Women and Comparison of Studies Using Digitized Film-Screen Mammography and Full-Field Digital Mammography.

Alexeeff SE, Odo NU, McBride R, McGuire V, Achacoso N, Rothstein JH, Lipson JA, Liang RY, Acton L, Yaffe MJ, Whittemore AS, Rubin DL, Sieh W, Habel LA.

Am J Epidemiol. 2019 Jun 1;188(6):1144-1154. doi: 10.1093/aje/kwz033.

PMID:
30865217
16.

ePAD: An Image Annotation and Analysis Platform for Quantitative Imaging.

Rubin DL, Ugur Akdogan M, Altindag C, Alkim E.

Tomography. 2019 Mar;5(1):170-183. doi: 10.18383/j.tom.2018.00055.

17.

A Probabilistic Model to Support Radiologists' Classification Decisions in Mammography Practice.

Zeng J, Gimenez F, Burnside ES, Rubin DL, Shachter R.

Med Decis Making. 2019 Apr;39(3):208-216. doi: 10.1177/0272989X19832914. Epub 2019 Feb 28.

PMID:
30819048
18.

An Automated Feature Engineering for Digital Rectal Examination Documentation using Natural Language Processing.

Bozkurt S, Park JI, Kan KM, Ferrari M, Rubin DL, Brooks JD, Hernandez-Boussard T.

AMIA Annu Symp Proc. 2018 Dec 5;2018:288-294. eCollection 2018.

19.

A Scalable Machine Learning Approach for Inferring Probabilistic US-LI-RADS Categorization.

Banerjee I, Choi HH, Desser T, Rubin DL.

AMIA Annu Symp Proc. 2018 Dec 5;2018:215-224. eCollection 2018.

20.

Automatic inference of BI-RADS final assessment categories from narrative mammography report findings.

Banerjee I, Bozkurt S, Alkim E, Sagreiya H, Kurian AW, Rubin DL.

J Biomed Inform. 2019 Apr;92:103137. doi: 10.1016/j.jbi.2019.103137. Epub 2019 Feb 23.

PMID:
30807833
21.

Advancing Semantic Interoperability of Image Annotations: Automated Conversion of Non-standard Image Annotations in a Commercial PACS to the Annotation and Image Markup.

Swinburne NC, Mendelson D, Rubin DL.

J Digit Imaging. 2019 Feb 25. doi: 10.1007/s10278-019-00191-6. [Epub ahead of print]

PMID:
30805778
22.

A multi-model framework to estimate perfusion parameters using contrast-enhanced ultrasound imaging.

Akhbardeh A, Sagreiya H, El Kaffas A, Willmann JK, Rubin DL.

Med Phys. 2019 Feb;46(2):590-600. doi: 10.1002/mp.13340. Epub 2019 Jan 21.

PMID:
30554408
23.

Comparative effectiveness of convolutional neural network (CNN) and recurrent neural network (RNN) architectures for radiology text report classification.

Banerjee I, Ling Y, Chen MC, Hasan SA, Langlotz CP, Moradzadeh N, Chapman B, Amrhein T, Mong D, Rubin DL, Farri O, Lungren MP.

Artif Intell Med. 2019 Jun;97:79-88. doi: 10.1016/j.artmed.2018.11.004. Epub 2018 Nov 23.

PMID:
30477892
24.

The use of texture-based radiomics CT analysis to predict outcomes in early-stage non-small cell lung cancer treated with stereotactic ablative radiotherapy.

Starkov P, Aguilera TA, Golden DI, Shultz DB, Trakul N, Maxim PG, Le QT, Loo BW, Diehn M, Depeursinge A, Rubin DL.

Br J Radiol. 2019 Feb;92(1094):20180228. doi: 10.1259/bjr.20180228. Epub 2018 Nov 20.

PMID:
30457885
25.

Assessment of Convolutional Neural Networks for Automated Classification of Chest Radiographs.

Dunnmon JA, Yi D, Langlotz CP, Ré C, Rubin DL, Lungren MP.

Radiology. 2019 Feb;290(2):537-544. doi: 10.1148/radiol.2018181422. Epub 2018 Nov 13.

PMID:
30422093
26.

Automated Survival Prediction in Metastatic Cancer Patients Using High-Dimensional Electronic Medical Record Data.

Gensheimer MF, Henry AS, Wood DJ, Hastie TJ, Aggarwal S, Dudley SA, Pradhan P, Banerjee I, Cho E, Ramchandran K, Pollom E, Koong AC, Rubin DL, Chang DT.

J Natl Cancer Inst. 2018 Oct 21. doi: 10.1093/jnci/djy178. [Epub ahead of print]

27.

A radiogenomic dataset of non-small cell lung cancer.

Bakr S, Gevaert O, Echegaray S, Ayers K, Zhou M, Shafiq M, Zheng H, Benson JA, Zhang W, Leung ANC, Kadoch M, Hoang CD, Shrager J, Quon A, Rubin DL, Plevritis SK, Napel S.

Sci Data. 2018 Oct 16;5:180202. doi: 10.1038/sdata.2018.202.

28.

Magnetic resonance imaging and molecular features associated with tumor-infiltrating lymphocytes in breast cancer.

Wu J, Li X, Teng X, Rubin DL, Napel S, Daniel BL, Li R.

Breast Cancer Res. 2018 Sep 3;20(1):101. doi: 10.1186/s13058-018-1039-2.

29.

Automated dendritic spine detection using convolutional neural networks on maximum intensity projected microscopic volumes.

Xiao X, Djurisic M, Hoogi A, Sapp RW, Shatz CJ, Rubin DL.

J Neurosci Methods. 2018 Nov 1;309:25-34. doi: 10.1016/j.jneumeth.2018.08.019. Epub 2018 Aug 18.

PMID:
30130608
30.

Relevance feedback for enhancing content based image retrieval and automatic prediction of semantic image features: Application to bone tumor radiographs.

Banerjee I, Kurtz C, Devorah AE, Do B, Rubin DL, Beaulieu CF.

J Biomed Inform. 2018 Aug;84:123-135. doi: 10.1016/j.jbi.2018.07.002. Epub 2018 Jul 5.

31.

Probabilistic Prognostic Estimates of Survival in Metastatic Cancer Patients (PPES-Met) Utilizing Free-Text Clinical Narratives.

Banerjee I, Gensheimer MF, Wood DJ, Henry S, Aggarwal S, Chang DT, Rubin DL.

Sci Rep. 2018 Jul 3;8(1):10037. doi: 10.1038/s41598-018-27946-5.

32.

The Use of Quantitative Imaging in Radiation Oncology: A Quantitative Imaging Network (QIN) Perspective.

Press RH, Shu HG, Shim H, Mountz JM, Kurland BF, Wahl RL, Jones EF, Hylton NM, Gerstner ER, Nordstrom RJ, Henderson L, Kurdziel KA, Vikram B, Jacobs MA, Holdhoff M, Taylor E, Jaffray DA, Schwartz LH, Mankoff DA, Kinahan PE, Linden HM, Lambin P, Dilling TJ, Rubin DL, Hadjiiski L, Buatti JM.

Int J Radiat Oncol Biol Phys. 2018 Nov 15;102(4):1219-1235. doi: 10.1016/j.ijrobp.2018.06.023. Epub 2018 Jun 30. Review.

33.

Toward Automated Pre-Biopsy Thyroid Cancer Risk Estimation in Ultrasound.

Galimzianova A, Siebert SM, Kamaya A, Desser TS, Rubin DL.

AMIA Annu Symp Proc. 2018 Apr 16;2017:734-741. eCollection 2017.

34.

Intelligent Word Embeddings of Free-Text Radiology Reports.

Banerjee I, Madhavan S, Goldman RE, Rubin DL.

AMIA Annu Symp Proc. 2018 Apr 16;2017:411-420. eCollection 2017.

35.

The LOINC RSNA radiology playbook - a unified terminology for radiology procedures.

Vreeman DJ, Abhyankar S, Wang KC, Carr C, Collins B, Rubin DL, Langlotz CP.

J Am Med Inform Assoc. 2018 Jul 1;25(7):885-893. doi: 10.1093/jamia/ocy053.

36.

Intratumoral Spatial Heterogeneity at Perfusion MR Imaging Predicts Recurrence-free Survival in Locally Advanced Breast Cancer Treated with Neoadjuvant Chemotherapy.

Wu J, Cao G, Sun X, Lee J, Rubin DL, Napel S, Kurian AW, Daniel BL, Li R.

Radiology. 2018 Jul;288(1):26-35. doi: 10.1148/radiol.2018172462. Epub 2018 May 1.

37.

Distributed deep learning networks among institutions for medical imaging.

Chang K, Balachandar N, Lam C, Yi D, Brown J, Beers A, Rosen B, Rubin DL, Kalpathy-Cramer J.

J Am Med Inform Assoc. 2018 Aug 1;25(8):945-954. doi: 10.1093/jamia/ocy017.

38.

Proposing New RadLex Terms by Analyzing Free-Text Mammography Reports.

Bulu H, Sippo DA, Lee JM, Burnside ES, Rubin DL.

J Digit Imaging. 2018 Oct;31(5):596-603. doi: 10.1007/s10278-018-0064-0.

39.

Inferring Generative Model Structure with Static Analysis.

Varma P, He B, Bajaj P, Banerjee I, Khandwala N, Rubin DL, Ré C.

Adv Neural Inf Process Syst. 2017 Dec;30:239-249.

40.

Integrative Personal Omics Profiles during Periods of Weight Gain and Loss.

Piening BD, Zhou W, Contrepois K, Röst H, Gu Urban GJ, Mishra T, Hanson BM, Bautista EJ, Leopold S, Yeh CY, Spakowicz D, Banerjee I, Chen C, Kukurba K, Perelman D, Craig C, Colbert E, Salins D, Rego S, Lee S, Zhang C, Wheeler J, Sailani MR, Liang L, Abbott C, Gerstein M, Mardinoglu A, Smith U, Rubin DL, Pitteri S, Sodergren E, McLaughlin TL, Weinstock GM, Snyder MP.

Cell Syst. 2018 Feb 28;6(2):157-170.e8. doi: 10.1016/j.cels.2017.12.013. Epub 2018 Jan 17.

41.

Automatic information extraction from unstructured mammography reports using distributed semantics.

Gupta A, Banerjee I, Rubin DL.

J Biomed Inform. 2018 Feb;78:78-86. doi: 10.1016/j.jbi.2017.12.016. Epub 2018 Jan 9.

42.

Beyond Retinal Layers: A Deep Voting Model for Automated Geographic Atrophy Segmentation in SD-OCT Images.

Ji Z, Chen Q, Niu S, Leng T, Rubin DL.

Transl Vis Sci Technol. 2018 Jan 2;7(1):1. doi: 10.1167/tvst.7.1.1. eCollection 2018 Jan.

43.

A curated mammography data set for use in computer-aided detection and diagnosis research.

Lee RS, Gimenez F, Hoogi A, Miyake KK, Gorovoy M, Rubin DL.

Sci Data. 2017 Dec 19;4:170177. doi: 10.1038/sdata.2017.177.

44.

Radiology report annotation using intelligent word embeddings: Applied to multi-institutional chest CT cohort.

Banerjee I, Chen MC, Lungren MP, Rubin DL.

J Biomed Inform. 2018 Jan;77:11-20. doi: 10.1016/j.jbi.2017.11.012. Epub 2017 Nov 23.

45.

Association of Omics Features with Histopathology Patterns in Lung Adenocarcinoma.

Yu KH, Berry GJ, Rubin DL, Ré C, Altman RB, Snyder M.

Cell Syst. 2017 Dec 27;5(6):620-627.e3. doi: 10.1016/j.cels.2017.10.014. Epub 2017 Nov 15.

46.

Assessing treatment response in triple-negative breast cancer from quantitative image analysis in perfusion magnetic resonance imaging.

Banerjee I, Malladi S, Lee D, Depeursinge A, Telli M, Lipson J, Golden D, Rubin DL.

J Med Imaging (Bellingham). 2018 Jan;5(1):011008. doi: 10.1117/1.JMI.5.1.011008. Epub 2017 Nov 2.

47.

Locally adaptive magnetic resonance intensity models for unsupervised segmentation of multiple sclerosis lesions.

Galimzianova A, Lesjak Ž, Rubin DL, Likar B, Pernuš F, Špiclin Ž.

J Med Imaging (Bellingham). 2018 Jan;5(1):011007. doi: 10.1117/1.JMI.5.1.011007. Epub 2017 Nov 1.

48.

Quantitative Image Feature Engine (QIFE): an Open-Source, Modular Engine for 3D Quantitative Feature Extraction from Volumetric Medical Images.

Echegaray S, Bakr S, Rubin DL, Napel S.

J Digit Imaging. 2018 Aug;31(4):403-414. doi: 10.1007/s10278-017-0019-x.

49.

Automated detection of foveal center in SD-OCT images using the saliency of retinal thickness maps.

Niu S, Chen Q, de Sisternes L, Leng T, Rubin DL.

Med Phys. 2017 Dec;44(12):6390-6403. doi: 10.1002/mp.12614. Epub 2017 Nov 3.

PMID:
28976639
50.

Prediction of EGFR and KRAS mutation in non-small cell lung cancer using quantitative 18F FDG-PET/CT metrics.

Minamimoto R, Jamali M, Gevaert O, Echegaray S, Khuong A, Hoang CD, Shrager JB, Plevritis SK, Rubin DL, Leung AN, Napel S, Quon A.

Oncotarget. 2017 May 10;8(32):52792-52801. doi: 10.18632/oncotarget.17782. eCollection 2017 Aug 8.

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