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Items: 1 to 50 of 140

1.

Machine learning techniques for personalized breast cancer risk prediction: comparison with the BCRAT and BOADICEA models.

Ming C, Viassolo V, Probst-Hensch N, Chappuis PO, Dinov ID, Katapodi MC.

Breast Cancer Res. 2019 Jun 20;21(1):75. doi: 10.1186/s13058-019-1158-4.

2.

Impact of using a broad-based multi-institutional approach to build capacity for non-communicable disease research in Thailand.

Potempa K, Rajataramya B, Barton DL, Singha-Dong N, Stephenson R, Smith EML, Davis M, Dinov I, Hampstead BM, Aikens JE, Saslow L, Furspan P, Sarakshetrin A, Pupjain S.

Health Res Policy Syst. 2019 Jun 14;17(1):62. doi: 10.1186/s12961-019-0464-8.

3.

The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services.

Avesani P, McPherson B, Hayashi S, Caiafa CF, Henschel R, Garyfallidis E, Kitchell L, Bullock D, Patterson A, Olivetti E, Sporns O, Saykin AJ, Wang L, Dinov I, Hancock D, Caron B, Qian Y, Pestilli F.

Sci Data. 2019 May 23;6(1):69. doi: 10.1038/s41597-019-0073-y.

4.

Imputation Strategy for Reliable Regional MRI Morphological Measurements.

Sta Cruz S, Dinov ID, Herting MM, González-Zacarías C, Kim H, Toga AW, Sepehrband F.

Neuroinformatics. 2019 May 4. doi: 10.1007/s12021-019-09426-x. [Epub ahead of print]

PMID:
31054076
5.

Predictive Big Data Analytics using the UK Biobank Data.

Zhou Y, Zhao L, Zhou N, Zhao Y, Marino S, Wang T, Sun H, Toga AW, Dinov ID.

Sci Rep. 2019 Apr 12;9(1):6012. doi: 10.1038/s41598-019-41634-y.

6.

Quant Data Science meets Dexterous Artistry.

Dinov ID.

Int J Data Sci Anal. 2019 Mar;7(2):81-86. doi: 10.1007/s41060-018-0138-6. Epub 2018 Jun 16.

PMID:
30923735
7.

Age-Related Differences in Brain Morphology and the Modifiers in Middle-Aged and Older Adults.

Zhao L, Matloff W, Ning K, Kim H, Dinov ID, Toga AW.

Cereb Cortex. 2019 Sep 13;29(10):4169-4193. doi: 10.1093/cercor/bhy300.

PMID:
30535294
8.

Model-Based and Model-Free Techniques for Amyotrophic Lateral Sclerosis Diagnostic Prediction and Patient Clustering.

Tang M, Gao C, Goutman SA, Kalinin A, Mukherjee B, Guan Y, Dinov ID.

Neuroinformatics. 2019 Jul;17(3):407-421. doi: 10.1007/s12021-018-9406-9.

PMID:
30460455
9.

Publisher Correction: 3D Shape Modeling for Cell Nuclear Morphological Analysis and Classification.

Kalinin AA, Allyn-Feuer A, Ade A, Fon GV, Meixner W, Dilworth D, Husain SS, de Wet JR, Higgins GA, Zheng G, Creekmore A, Wiley JW, Verdone JE, Veltri RW, Pienta KJ, Coffey DS, Athey BD, Dinov ID.

Sci Rep. 2018 Oct 26;8(1):16142. doi: 10.1038/s41598-018-33574-w.

10.

Randomization-Based Statistical Inference: A Resampling and Simulation Infrastructure.

Dinov ID, Palanimalai S, Khare A, Christou N.

Teach Stat. 2018 Summer;40(2):64-73. doi: 10.1111/test.12156. Epub 2018 Apr 11.

11.

Hypothesis: Caco-2 cell rotational 3D mechanogenomic turing patterns have clinical implications to colon crypts.

Zheng G, Kalinin AA, Dinov ID, Meixner W, Zhu S, Wiley JW.

J Cell Mol Med. 2018 Dec;22(12):6380-6385. doi: 10.1111/jcmm.13853. Epub 2018 Sep 25.

12.

3D Shape Modeling for Cell Nuclear Morphological Analysis and Classification.

Kalinin AA, Allyn-Feuer A, Ade A, Fon GV, Meixner W, Dilworth D, Husain SS, de Wet JR, Higgins GA, Zheng G, Creekmore A, Wiley JW, Verdone JE, Veltri RW, Pienta KJ, Coffey DS, Athey BD, Dinov ID.

Sci Rep. 2018 Sep 12;8(1):13658. doi: 10.1038/s41598-018-31924-2. Erratum in: Sci Rep. 2018 Oct 26;8(1):16142.

13.

Controlled feature selection and compressive big data analytics: Applications to biomedical and health studies.

Marino S, Xu J, Zhao Y, Zhou N, Zhou Y, Dinov ID.

PLoS One. 2018 Aug 30;13(8):e0202674. doi: 10.1371/journal.pone.0202674. eCollection 2018.

14.

Model-based and Model-free Machine Learning Techniques for Diagnostic Prediction and Classification of Clinical Outcomes in Parkinson's Disease.

Gao C, Sun H, Wang T, Tang M, Bohnen NI, Müller MLTM, Herman T, Giladi N, Kalinin A, Spino C, Dauer W, Hausdorff JM, Dinov ID.

Sci Rep. 2018 May 8;8(1):7129. doi: 10.1038/s41598-018-24783-4.

15.

Deep learning in pharmacogenomics: from gene regulation to patient stratification.

Kalinin AA, Higgins GA, Reamaroon N, Soroushmehr S, Allyn-Feuer A, Dinov ID, Najarian K, Athey BD.

Pharmacogenomics. 2018 May;19(7):629-650. doi: 10.2217/pgs-2018-0008. Epub 2018 Apr 26. Review.

16.

SOCRAT Platform Design: A Web Architecture for Interactive Visual Analytics Applications.

Kalinin AA, Palanimalai S, Dinov ID.

Proc 2nd Workshop Hum Loop Data Anal (2017). 2017 Apr;2017. pii: 8. doi: 10.1145/3077257.3077262.

17.

Neuroanatomical morphometric characterization of sex differences in youth using statistical learning.

Sepehrband F, Lynch KM, Cabeen RP, Gonzalez-Zacarias C, Zhao L, D'Arcy M, Kesselman C, Herting MM, Dinov ID, Toga AW, Clark KA.

Neuroimage. 2018 May 15;172:217-227. doi: 10.1016/j.neuroimage.2018.01.065. Epub 2018 Feb 3.

18.

HDDA: DataSifter: statistical obfuscation of electronic health records and other sensitive datasets.

Marino S, Zhou N, Zhao Y, Wang L, Wu Q, Dinov ID.

J Stat Comput Simul. 2018;89(2):249-271. doi: 10.1080/00949655.2018.1545228. Epub 2018 Nov 11.

19.

Complete hazard ranking to analyze right-censored data: An ALS survival study.

Huang Z, Zhang H, Boss J, Goutman SA, Mukherjee B, Dinov ID, Guan Y; Pooled Resource Open-Access ALS Clinical Trials Consortium.

PLoS Comput Biol. 2017 Dec 18;13(12):e1005887. doi: 10.1371/journal.pcbi.1005887. eCollection 2017 Dec.

20.

Translational MRI Volumetry with NeuroQuant: Effects of Version and Normative Data on Relationships with Memory Performance in Healthy Older Adults and Patients with Mild Cognitive Impairment.

Stelmokas J, Yassay L, Giordani B, Dodge HH, Dinov ID, Bhaumik A, Sathian K, Hampstead BM.

J Alzheimers Dis. 2017;60(4):1499-1510. doi: 10.3233/JAD-170306.

21.

T2-Imaging Changes in the Nigrosome-1 Relate to Clinical Measures of Parkinson's Disease.

Fu KA, Nathan R, Dinov ID, Li J, Toga AW.

Front Neurol. 2016 Oct 20;7:174. eCollection 2016.

22.

Predictive Big Data Analytics: A Study of Parkinson's Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations.

Dinov ID, Heavner B, Tang M, Glusman G, Chard K, Darcy M, Madduri R, Pa J, Spino C, Kesselman C, Foster I, Deutsch EW, Price ND, Van Horn JD, Ames J, Clark K, Hood L, Hampstead BM, Dauer W, Toga AW.

PLoS One. 2016 Aug 5;11(8):e0157077. doi: 10.1371/journal.pone.0157077. eCollection 2016.

23.

Comparison of genomic data via statistical distribution.

Amiri S, Dinov ID.

J Theor Biol. 2016 Oct 21;407:318-327. doi: 10.1016/j.jtbi.2016.07.032. Epub 2016 Jul 25.

24.

Probability Distributome: A Web Computational Infrastructure for Exploring the Properties, Interrelations, and Applications of Probability Distributions.

Dinov ID, Siegrist K, Pearl DK, Kalinin A, Christou N.

Comput Stat. 2016 Jun;31(2):559-577. Epub 2015 Jun 26.

25.

Volume and Value of Big Healthcare Data.

Dinov ID.

J Med Stat Inform. 2016;4. pii: 3.

26.

Methodological challenges and analytic opportunities for modeling and interpreting Big Healthcare Data.

Dinov ID.

Gigascience. 2016 Feb 25;5:12. doi: 10.1186/s13742-016-0117-6. eCollection 2016. Review.

27.

Structural Neuroimaging Genetics Interactions in Alzheimer's Disease.

Moon SW, Dinov ID, Kim J, Zamanyan A, Hobel S, Thompson PM, Toga AW.

J Alzheimers Dis. 2015;48(4):1051-63. doi: 10.3233/JAD-150335.

28.
29.

Big biomedical data as the key resource for discovery science.

Toga AW, Foster I, Kesselman C, Madduri R, Chard K, Deutsch EW, Price ND, Glusman G, Heavner BD, Dinov ID, Ames J, Van Horn J, Kramer R, Hood L.

J Am Med Inform Assoc. 2015 Nov;22(6):1126-31. doi: 10.1093/jamia/ocv077. Epub 2015 Jul 21.

30.

Structural Brain Changes in Early-Onset Alzheimer's Disease Subjects Using the LONI Pipeline Environment.

Moon SW, Dinov ID, Hobel S, Zamanyan A, Choi YC, Shi R, Thompson PM, Toga AW; Alzheimer's Disease Neuroimaging Initiative.

J Neuroimaging. 2015 Sep-Oct;25(5):728-37. doi: 10.1111/jon.12252. Epub 2015 May 4.

31.

Gene interactions and structural brain change in early-onset Alzheimer's disease subjects using the pipeline environment.

Moon SW, Dinov ID, Zamanyan A, Shi R, Genco A, Hobel S, Thompson PM, Toga AW; Alzheimer's Disease Neuroimaging Initiative (ADNI).

Psychiatry Investig. 2015 Jan;12(1):125-35. doi: 10.4306/pi.2015.12.1.125. Epub 2015 Jan 12.

32.

Interacting with the National Database for Autism Research (NDAR) via the LONI Pipeline workflow environment.

Torgerson CM, Quinn C, Dinov I, Liu Z, Petrosyan P, Pelphrey K, Haselgrove C, Kennedy DN, Toga AW, Van Horn JD.

Brain Imaging Behav. 2015 Mar;9(1):89-103. doi: 10.1007/s11682-015-9354-z.

33.

Sharing big biomedical data.

Toga AW, Dinov ID.

J Big Data. 2015;2. pii: 7. Epub 2015 Jun 27.

34.
35.

Hippocampal abnormalities and age in chronic schizophrenia: morphometric study across the adult lifespan.

Pujol N, Penadés R, Junqué C, Dinov I, Fu CH, Catalán R, Ibarretxe-Bilbao N, Bargalló N, Bernardo M, Toga A, Howard RJ, Costafreda SG.

Br J Psychiatry. 2014 Nov;205(5):369-75. doi: 10.1192/bjp.bp.113.140384. Epub 2014 Sep 11.

36.

An automatic framework for quantitative validation of voxel based morphometry measures of anatomical brain asymmetry.

Pepe A, Dinov I, Tohka J.

Neuroimage. 2014 Oct 15;100:444-59. doi: 10.1016/j.neuroimage.2014.06.029. Epub 2014 Jun 18.

37.

High-throughput neuroimaging-genetics computational infrastructure.

Dinov ID, Petrosyan P, Liu Z, Eggert P, Hobel S, Vespa P, Woo Moon S, Van Horn JD, Franco J, Toga AW.

Front Neuroinform. 2014 Apr 23;8:41. doi: 10.3389/fninf.2014.00041. eCollection 2014.

38.

Coiling and maturation of a high-performance fibre in hagfish slime gland thread cells.

Winegard T, Herr J, Mena C, Lee B, Dinov I, Bird D, Bernards M Jr, Hobel S, Van Valkenburgh B, Toga A, Fudge D.

Nat Commun. 2014 Apr 4;5:3534. doi: 10.1038/ncomms4534.

39.

Voxelwise spectral diffusional connectivity and its applications to Alzheimer's disease and intelligence prediction.

Li J, Jin Y, Shi Y, Dinov ID, Wang DJ, Toga AW, Thompson PM.

Med Image Comput Comput Assist Interv. 2013;16(Pt 1):655-62.

40.

Regional neuroplastic brain changes in patients with chronic inflammatory and non-inflammatory visceral pain.

Hong JY, Labus JS, Jiang Z, Ashe-Mcnalley C, Dinov I, Gupta A, Shi Y, Stains J, Heendeniya N, Smith SR, Tillisch K, Mayer EA.

PLoS One. 2014 Jan 8;9(1):e84564. doi: 10.1371/journal.pone.0084564. eCollection 2014. Erratum in: PLoS One. 2014;9(2):e91490.

41.

Irritable bowel syndrome in female patients is associated with alterations in structural brain networks.

Labus JS, Dinov ID, Jiang Z, Ashe-McNalley C, Zamanyan A, Shi Y, Hong JY, Gupta A, Tillisch K, Ebrat B, Hobel S, Gutman BA, Joshi S, Thompson PM, Toga AW, Mayer EA.

Pain. 2014 Jan;155(1):137-49. doi: 10.1016/j.pain.2013.09.020. Epub 2013 Sep 26.

42.

Sex-related differences of cortical thickness in patients with chronic abdominal pain.

Jiang Z, Dinov ID, Labus J, Shi Y, Zamanyan A, Gupta A, Ashe-McNalley C, Hong JY, Tillisch K, Toga AW, Mayer EA.

PLoS One. 2013 Sep 5;8(9):e73932. doi: 10.1371/journal.pone.0073932. eCollection 2013.

43.

The perfect neuroimaging-genetics-computation storm: collision of petabytes of data, millions of hardware devices and thousands of software tools.

Dinov ID, Petrosyan P, Liu Z, Eggert P, Zamanyan A, Torri F, Macciardi F, Hobel S, Moon SW, Sung YH, Jiang Z, Labus J, Kurth F, Ashe-McNalley C, Mayer E, Vespa PM, Van Horn JD, Toga AW; Alzheimer’s Disease Neuroimaging Initiative.

Brain Imaging Behav. 2014 Jun;8(2):311-22. doi: 10.1007/s11682-013-9248-x.

44.

Fast local trust region technique for diffusion tensor registration using exact reorientation and regularization.

Li J, Shi Y, Tran G, Dinov I, Wang DJ, Toga A.

IEEE Trans Med Imaging. 2014 May;33(5):1005-22. doi: 10.1109/TMI.2013.2274051. Epub 2013 Jul 18.

45.

Spatial-temporal atlas of human fetal brain development during the early second trimester.

Zhan J, Dinov ID, Li J, Zhang Z, Hobel S, Shi Y, Lin X, Zamanyan A, Feng L, Teng G, Fang F, Tang Y, Zang F, Toga AW, Liu S.

Neuroimage. 2013 Nov 15;82:115-26. doi: 10.1016/j.neuroimage.2013.05.063. Epub 2013 May 31.

46.

FKBP5 and attention bias for threat: associations with hippocampal function and shape.

Fani N, Gutman D, Tone EB, Almli L, Mercer KB, Davis J, Glover E, Jovanovic T, Bradley B, Dinov ID, Zamanyan A, Toga AW, Binder EB, Ressler KJ.

JAMA Psychiatry. 2013 Apr;70(4):392-400. doi: 10.1001/2013.jamapsychiatry.210.

47.

Fast diffusion tensor registration with exact reorientation and regularization.

Li J, Shi Y, Tran G, Dinov I, Wang DJ, Toga AW.

Med Image Comput Comput Assist Interv. 2012;15(Pt 2):138-45.

48.

Locally Weighted Multi-atlas Construction.

Li J, Shi Y, Dinov ID, Toga AW.

Multimodal Brain Image Anal (2013). 2013 Jan 1;8159:1-8.

49.

Next generation sequence analysis and computational genomics using graphical pipeline workflows.

Torri F, Dinov ID, Zamanyan A, Hobel S, Genco A, Petrosyan P, Clark AP, Liu Z, Eggert P, Pierce J, Knowles JA, Ames J, Kesselman C, Toga AW, Potkin SG, Vawter MP, Macciardi F.

Genes (Basel). 2012 Aug 30;3(3):545-75. doi: 10.3390/genes3030545.

50.

A role for ephrin-A5 in axonal sprouting, recovery, and activity-dependent plasticity after stroke.

Overman JJ, Clarkson AN, Wanner IB, Overman WT, Eckstein I, Maguire JL, Dinov ID, Toga AW, Carmichael ST.

Proc Natl Acad Sci U S A. 2012 Aug 14;109(33):E2230-9. doi: 10.1073/pnas.1204386109. Epub 2012 Jul 25.

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