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Items: 1 to 20 of 136

1.

Developing a clinical utility framework to evaluate prediction models in radiogenomics.

Wu Y, Liu J, Del Rio AM, Page DC, Alagoz O, Peissig P, Onitilo AA, Burnside ES.

Proc SPIE Int Soc Opt Eng. 2015 Feb 21;9416. pii: 941617. Epub 2015 Mar 17.

2.

Improved prediction of complex diseases by common genetic markers: state of the art and further perspectives.

Müller B, Wilcke A, Boulesteix AL, Brauer J, Passarge E, Boltze J, Kirsten H.

Hum Genet. 2016 Mar;135(3):259-72. doi: 10.1007/s00439-016-1636-z. Epub 2016 Feb 2.

3.

Developing a utility decision framework to evaluate predictive models in breast cancer risk estimation.

Wu Y, Abbey CK, Chen X, Liu J, Page DC, Alagoz O, Peissig P, Onitilo AA, Burnside ES.

J Med Imaging (Bellingham). 2015 Oct;2(4):041005. doi: 10.1117/1.JMI.2.4.041005. Epub 2015 Aug 17.

PMID:
26835489
4.

Effects of EZH2 promoter polymorphisms and methylation status on oral squamous cell carcinoma susceptibility and pathology.

Su KJ, Lin CW, Chen MK, Yang SF, Yu YL.

Am J Cancer Res. 2015 Oct 15;5(11):3475-84. eCollection 2015.

5.

Machine learning derived risk prediction of anorexia nervosa.

Guo Y, Wei Z, Keating BJ; Genetic Consortium for Anorexia Nervosa; Wellcome Trust Case Control Consortium 3; Price Foundation Collaborative Group, Hakonarson H.

BMC Med Genomics. 2016 Jan 20;9:4. doi: 10.1186/s12920-016-0165-x.

6.

Breast Cancer Risk Prediction Using Clinical Models and 77 Independent Risk-Associated SNPs for Women Aged Under 50 Years: Australian Breast Cancer Family Registry.

Dite GS, MacInnis RJ, Bickerstaffe A, Dowty JG, Allman R, Apicella C, Milne RL, Tsimiklis H, Phillips KA, Giles GG, Terry MB, Southey MC, Hopper JL.

Cancer Epidemiol Biomarkers Prev. 2016 Feb;25(2):359-65. doi: 10.1158/1055-9965.EPI-15-0838. Epub 2015 Dec 16.

PMID:
26677205
7.

A steroid metabolizing gene variant in a polyfactorial model improves risk prediction in a high incidence breast cancer population.

Jupe ER, Dalessandri KM, Mulvihill JJ, Miike R, Knowlton NS, Pugh TW, Zhao LP, DeFreese DC, Manjeshwar S, Gramling BA, Wiencke JK, Benz CC.

BBA Clin. 2014 Nov 8;2:94-102. doi: 10.1016/j.bbacli.2014.11.001. eCollection 2014 Dec.

8.

SNPs and breast cancer risk prediction for African American and Hispanic women.

Allman R, Dite GS, Hopper JL, Gordon O, Starlard-Davenport A, Chlebowski R, Kooperberg C.

Breast Cancer Res Treat. 2015 Dec;154(3):583-9. doi: 10.1007/s10549-015-3641-7. Epub 2015 Nov 20.

9.

Gene-expression patterns in peripheral blood classify familial breast cancer susceptibility.

Piccolo SR, Andrulis IL, Cohen AL, Conner T, Moos PJ, Spira AE, Buys SS, Johnson WE, Bild AH.

BMC Med Genomics. 2015 Nov 4;8:72. doi: 10.1186/s12920-015-0145-6.

10.

Comparing Mammography Abnormality Features to Genetic Variants in the Prediction of Breast Cancer in Women Recommended for Breast Biopsy.

Burnside ES, Liu J, Wu Y, Onitilo AA, McCarty CA, Page CD, Peissig PL, Trentham-Dietz A, Kitchner T, Fan J, Yuan M.

Acad Radiol. 2016 Jan;23(1):62-9. doi: 10.1016/j.acra.2015.09.007. Epub 2015 Oct 26.

PMID:
26514439
11.

The impact of direct-to-consumer personal genomic testing on perceived risk of breast, prostate, colorectal, and lung cancer: findings from the PGen study.

Carere DA, VanderWeele T, Moreno TA, Mountain JL, Roberts JS, Kraft P, Green RC; PGen Study Group.

BMC Med Genomics. 2015 Oct 15;8:63. doi: 10.1186/s12920-015-0140-y.

12.

Mortality Risk Prediction: Can Comorbidity Indices Be Improved With Psychosocial Data?

Chapman BP, Weiss A, Fiscella K, Muennig P, Kawachi I, Duberstein P.

Med Care. 2015 Nov;53(11):909-15. doi: 10.1097/MLR.0000000000000428.

PMID:
26421372
13.

Lung Cancer Risk Prediction Using Common SNPs Located in GWAS-Identified Susceptibility Regions.

Weissfeld JL, Lin Y, Lin HM, Kurland BF, Wilson DO, Fuhrman CR, Pennathur A, Romkes M, Nukui T, Yuan JM, Siegfried JM, Diergaarde B.

J Thorac Oncol. 2015 Nov;10(11):1538-45. doi: 10.1097/JTO.0000000000000666.

PMID:
26352532
14.

Leveraging Interaction between Genetic Variants and Mammographic Findings for Personalized Breast Cancer Diagnosis.

Liu J, Wu Y, Ong I, Page D, Peissig P, McCarty C, Onitilo AA, Burnside E.

AMIA Jt Summits Transl Sci Proc. 2015 Mar 25;2015:107-11. eCollection 2015.

15.

Risk Classification with an Adaptive Naive Bayes Kernel Machine Model.

Minnier J, Yuan M, Liu JS, Cai T.

J Am Stat Assoc. 2015 Apr 22;110(509):393-404.

16.

Genetic architecture of colorectal cancer.

Peters U, Bien S, Zubair N.

Gut. 2015 Oct;64(10):1623-36. doi: 10.1136/gutjnl-2013-306705. Epub 2015 Jul 17. Review.

PMID:
26187503
17.

Targeted Cancer Screening in Average-Risk Individuals.

Marcus PM, Freedman AN, Khoury MJ.

Am J Prev Med. 2015 Nov;49(5):765-71. doi: 10.1016/j.amepre.2015.04.030. Epub 2015 Jul 10.

18.

Comparing the value of mammographic features and genetic variants in breast cancer risk prediction.

Wu Y, Liu J, Page D, Peissig P, McCarty C, Onitilo AA, Burnside ES.

AMIA Annu Symp Proc. 2014 Nov 14;2014:1228-37. eCollection 2014.

19.

Genetic polymorphisms associated with breast cancer in malaysian cohort.

Chahil JK, Munretnam K, Samsudin N, Lye SH, Hashim NA, Ramzi NH, Velapasamy S, Wee LL, Alex L.

Indian J Clin Biochem. 2015 Apr;30(2):134-9. doi: 10.1007/s12291-013-0414-0. Epub 2014 Jan 23.

20.

Associations between breast density and a panel of single nucleotide polymorphisms linked to breast cancer risk: a cohort study with digital mammography.

Keller BM, McCarthy AM, Chen J, Armstrong K, Conant EF, Domchek SM, Kontos D.

BMC Cancer. 2015 Mar 18;15:143. doi: 10.1186/s12885-015-1159-3.

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