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Showing 1 to 12 of 163 entries
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Quantitative analysis of ex vivo colorectal epithelium using an automated feature extraction algorithm for microendoscopy image data.

Journal of medical imaging (Bellingham, Wash.)

Prieto SP, Lai KK, Laryea JA, Mizell JS, Muldoon TJ.
PMID: 27335893
J Med Imaging (Bellingham). 2016 Apr;3(2):024502. doi: 10.1117/1.JMI.3.2.024502. Epub 2016 Jun 03.

Qualitative screening for colorectal polyps via fiber bundle microendoscopy imaging has shown promising results, with studies reporting high rates of sensitivity and specificity, as well as low interobserver variability with trained clinicians. A quantitative image quality control and image...

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Prieto SP, Lai KK, Laryea JA, et al. Quantitative analysis of ex vivo colorectal epithelium using an automated feature extraction algorithm for microendoscopy image data. J Med Imaging (Bellingham). 2016;3(2):024502doi: 10.1117/1.JMI.3.2.024502.
Prieto, S. P., Lai, K. K., Laryea, J. A., Mizell, J. S., & Muldoon, T. J. (2016). Quantitative analysis of ex vivo colorectal epithelium using an automated feature extraction algorithm for microendoscopy image data. Journal of medical imaging (Bellingham, Wash.), 3(2), 024502. https://doi.org/10.1117/1.JMI.3.2.024502
Prieto, Sandra P, et al. "Quantitative analysis of ex vivo colorectal epithelium using an automated feature extraction algorithm for microendoscopy image data." Journal of medical imaging (Bellingham, Wash.) vol. 3,2 (2016): 024502. doi: https://doi.org/10.1117/1.JMI.3.2.024502
Prieto SP, Lai KK, Laryea JA, Mizell JS, Muldoon TJ. Quantitative analysis of ex vivo colorectal epithelium using an automated feature extraction algorithm for microendoscopy image data. J Med Imaging (Bellingham). 2016 Apr;3(2):024502. doi: 10.1117/1.JMI.3.2.024502. Epub 2016 Jun 03. PMID: 27335893; PMCID: PMC4891528.
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The Rideal-Walker Co-Efficient.

The Indian medical gazette

Rideal S, Ainslie-Walker JT.
PMID: 29004998
Ind Med Gaz. 1907 Oct;42(10):395.

No abstract available.

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Rideal S, Ainslie-Walker JT. The Rideal-Walker Co-Efficient. Ind Med Gaz. 1907;42(10):395
Rideal, S., & Ainslie-Walker, J. T. (1907). The Rideal-Walker Co-Efficient. The Indian medical gazette, 42(10), 395.
Rideal, Samuel, and Ainslie-Walker, J T. "The Rideal-Walker Co-Efficient." The Indian medical gazette vol. 42,10 (1907): 395.
Rideal S, Ainslie-Walker JT. The Rideal-Walker Co-Efficient. Ind Med Gaz. 1907 Oct;42(10):395. PMID: 29004998; PMCID: PMC5165861.
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The Association between Treatment for Metabolic Disorders and Breast Cancer Characteristics.

International journal of endocrinology

Goldvaser H, Rizel S, Hendler D, Neiman V, Shepshelovich D, Shochat T, Sulkes A, Brenner B, Yerushalmi R.
PMID: 27648070
Int J Endocrinol. 2016;2016:4658469. doi: 10.1155/2016/4658469. Epub 2016 Aug 28.

Purpose. To evaluate the associations between metformin, insulin, statins, and levothyroxine and breast cancer characteristics and outcome. Methods. Retrospective chart review of patients treated in our institute for early estrogen receptor (ER) positive, human epidermal growth factor receptor 2...

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Goldvaser H, Rizel S, Hendler D, et al. The Association between Treatment for Metabolic Disorders and Breast Cancer Characteristics. Int J Endocrinol. 2016;2016:4658469doi: 10.1155/2016/4658469.
Goldvaser, H., Rizel, S., Hendler, D., Neiman, V., Shepshelovich, D., Shochat, T., Sulkes, A., Brenner, B., & Yerushalmi, R. (2016). The Association between Treatment for Metabolic Disorders and Breast Cancer Characteristics. International journal of endocrinology, 20164658469. https://doi.org/10.1155/2016/4658469
Goldvaser, Hadar, et al. "The Association between Treatment for Metabolic Disorders and Breast Cancer Characteristics." International journal of endocrinology vol. 2016 (2016): 4658469. doi: https://doi.org/10.1155/2016/4658469
Goldvaser H, Rizel S, Hendler D, Neiman V, Shepshelovich D, Shochat T, Sulkes A, Brenner B, Yerushalmi R. The Association between Treatment for Metabolic Disorders and Breast Cancer Characteristics. Int J Endocrinol. 2016;2016:4658469. doi: 10.1155/2016/4658469. Epub 2016 Aug 28. PMID: 27648070; PMCID: PMC5018344.
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The Visible Cement Data Set.

Journal of research of the National Institute of Standards and Technology

Bentz DP, Mizell S, Satterfield S, Devaney J, George W, Ketcham P, Graham J, Porterfield J, Quenard D, Vallee F, Sallee H, Boller E, Baruchel J.
PMID: 27446723
J Res Natl Inst Stand Technol. 2002 Apr 01;107(2):137-48. doi: 10.6028/jres.107.013. Print 2002.

With advances in x-ray microtomography, it is now possible to obtain three-dimensional representations of a material's microstructure with a voxel size of less than one micrometer. The Visible Cement Data Set represents a collection of 3-D data sets obtained...

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Bentz DP, Mizell S, Satterfield S, et al. The Visible Cement Data Set. J Res Natl Inst Stand Technol. 2002;107(2):137-48doi: 10.6028/jres.107.013.
Bentz, D. P., Mizell, S., Satterfield, S., Devaney, J., George, W., Ketcham, P., Graham, J., Porterfield, J., Quenard, D., Vallee, F., Sallee, H., Boller, E., & Baruchel, J. (2002). The Visible Cement Data Set. Journal of research of the National Institute of Standards and Technology, 107(2), 137-48. https://doi.org/10.6028/jres.107.013
Bentz, Dale P, et al. "The Visible Cement Data Set." Journal of research of the National Institute of Standards and Technology vol. 107,2 (2002): 137-48. doi: https://doi.org/10.6028/jres.107.013
Bentz DP, Mizell S, Satterfield S, Devaney J, George W, Ketcham P, Graham J, Porterfield J, Quenard D, Vallee F, Sallee H, Boller E, Baruchel J. The Visible Cement Data Set. J Res Natl Inst Stand Technol. 2002 Apr 01;107(2):137-48. doi: 10.6028/jres.107.013. Print 2002. PMID: 27446723; PMCID: PMC4859256.
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High Proliferation Predicts Pathological Complete Response to Neoadjuvant Chemotherapy in Early Breast Cancer.

The oncologist

Alba E, Lluch A, Ribelles N, Anton-Torres A, Sanchez-Rovira P, Albanell J, Calvo L, García-Asenjo JA, Palacios J, Chacon JI, Ruiz A, De la Haba-Rodriguez J, Segui-Palmer MA, Cirauqui B, Margeli M, Plazaola A, Barnadas A, Casas M, Caballero R, Carrasco E, Rojo F.
PMID: 27317735
Oncologist. 2016 Jun;21(6):778. doi: 10.1634/theoncologist.2015-0312erratum.

No abstract available.

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Alba E, Lluch A, Ribelles N, et al. High Proliferation Predicts Pathological Complete Response to Neoadjuvant Chemotherapy in Early Breast Cancer. Oncologist. 2016;21(6):778doi: 10.1634/theoncologist.2015-0312erratum.
Alba, E., Lluch, A., Ribelles, N., Anton-Torres, A., Sanchez-Rovira, P., Albanell, J., Calvo, L., García-Asenjo, J. A., Palacios, J., Chacon, J. I., Ruiz, A., De la Haba-Rodriguez, J., Segui-Palmer, M. A., Cirauqui, B., Margeli, M., Plazaola, A., Barnadas, A., Casas, M., Caballero, R., Carrasco, E., & Rojo, F. (2016). High Proliferation Predicts Pathological Complete Response to Neoadjuvant Chemotherapy in Early Breast Cancer. The oncologist, 21(6), 778. https://doi.org/10.1634/theoncologist.2015-0312erratum
Alba, Emilio, et al. "High Proliferation Predicts Pathological Complete Response to Neoadjuvant Chemotherapy in Early Breast Cancer." The oncologist vol. 21,6 (2016): 778. doi: https://doi.org/10.1634/theoncologist.2015-0312erratum
Alba E, Lluch A, Ribelles N, Anton-Torres A, Sanchez-Rovira P, Albanell J, Calvo L, García-Asenjo JA, Palacios J, Chacon JI, Ruiz A, De la Haba-Rodriguez J, Segui-Palmer MA, Cirauqui B, Margeli M, Plazaola A, Barnadas A, Casas M, Caballero R, Carrasco E, Rojo F. High Proliferation Predicts Pathological Complete Response to Neoadjuvant Chemotherapy in Early Breast Cancer. Oncologist. 2016 Jun;21(6):778. doi: 10.1634/theoncologist.2015-0312erratum. PMID: 27317735; PMCID: PMC4912359.
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In-sample and out-of-sample model selection and error estimation for support vector machines.

IEEE transactions on neural networks and learning systems

Anguita D, Ghio A, Oneto L, Ridella S.
PMID: 24807923
IEEE Trans Neural Netw Learn Syst. 2012 Sep;23(9):1390-406. doi: 10.1109/TNNLS.2012.2202401.

In-sample approaches to model selection and error estimation of support vector machines (SVMs) are not as widespread as out-of-sample methods, where part of the data is removed from the training set for validation and testing purposes, mainly because their...

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Anguita D, Ghio A, Oneto L, et al. In-sample and out-of-sample model selection and error estimation for support vector machines. IEEE Trans Neural Netw Learn Syst. 2012;23(9):1390-406doi: 10.1109/TNNLS.2012.2202401.
Anguita, D., Ghio, A., Oneto, L., & Ridella, S. (2012). In-sample and out-of-sample model selection and error estimation for support vector machines. IEEE transactions on neural networks and learning systems, 23(9), 1390-406. https://doi.org/10.1109/TNNLS.2012.2202401
Anguita, Davide, et al. "In-sample and out-of-sample model selection and error estimation for support vector machines." IEEE transactions on neural networks and learning systems vol. 23,9 (2012): 1390-406. doi: https://doi.org/10.1109/TNNLS.2012.2202401
Anguita D, Ghio A, Oneto L, Ridella S. In-sample and out-of-sample model selection and error estimation for support vector machines. IEEE Trans Neural Netw Learn Syst. 2012 Sep;23(9):1390-406. doi: 10.1109/TNNLS.2012.2202401. PMID: 24807923.
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Assessment of the effectiveness of aircraft noise regulation.

Noise & health

Fidell S.
PMID: 12689497
Noise Health. 1999;1(3):17-26.

A fundamental goal of aircraft noise regulation is control of the prevalence of noise-induced annoyance in airport communities. A common regulatory strategy is to identify values of long-term, time-weighted average aircraft noise exposure that may not be exceeded in...

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Fidell S. Assessment of the effectiveness of aircraft noise regulation. Noise Health. 1999;1(3):17-26
Fidell, S. (1999). Assessment of the effectiveness of aircraft noise regulation. Noise & health, 1(3), 17-26.
Fidell, Sanford. "Assessment of the effectiveness of aircraft noise regulation." Noise & health vol. 1,3 (1999): 17-26.
Fidell S. Assessment of the effectiveness of aircraft noise regulation. Noise Health. 1999;1(3):17-26. PMID: 12689497.
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Endometrial thickness as measured by transvaginal sonography: interobserver variation.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology

Karlsson B, Granberg S, Ridell B, Wikland M.
PMID: 12797168
Ultrasound Obstet Gynecol. 1994 Jul 01;4(4):320-5. doi: 10.1046/j.1469-0705.1994.04040320.x.

Transvaginal sonography of the uterus has become an important tool for diagnosing endometrial pathology in women with postmenopausal bleeding. One parameter that has been claimed to be important for curly detection of endometrial pathology in this group of women...

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Karlsson B, Granberg S, Ridell B, et al. Endometrial thickness as measured by transvaginal sonography: interobserver variation. Ultrasound Obstet Gynecol. 1994;4(4):320-5doi: 10.1046/j.1469-0705.1994.04040320.x.
Karlsson, B., Granberg, S., Ridell, B., & Wikland, M. (1994). Endometrial thickness as measured by transvaginal sonography: interobserver variation. Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology, 4(4), 320-5. https://doi.org/10.1046/j.1469-0705.1994.04040320.x
Karlsson, B, et al. "Endometrial thickness as measured by transvaginal sonography: interobserver variation." Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology vol. 4,4 (1994): 320-5. doi: https://doi.org/10.1046/j.1469-0705.1994.04040320.x
Karlsson B, Granberg S, Ridell B, Wikland M. Endometrial thickness as measured by transvaginal sonography: interobserver variation. Ultrasound Obstet Gynecol. 1994 Jul 01;4(4):320-5. doi: 10.1046/j.1469-0705.1994.04040320.x. PMID: 12797168.
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Second-harmonic generation in waveguides induced by photorefractive spatial solitons.

Optics letters

Lan S, Shih MF, Mizell G, Giordmaine JA, Chen Z, Anastassiou C, Martin J, Segev M.
PMID: 18073967
Opt Lett. 1999 Aug 15;24(16):1145-7. doi: 10.1364/ol.24.001145.

We demonstrate experimentally second-harmonic generation in waveguides induced by photorefractive solitons and show that the conversion efficiency is improved considerably. These induced waveguides are flexible and can be generated in any crystalline direction that allows soliton formation, and thus...

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Lan S, Shih MF, Mizell G, et al. Second-harmonic generation in waveguides induced by photorefractive spatial solitons. Opt Lett. 1999;24(16):1145-7doi: 10.1364/ol.24.001145.
Lan, S., Shih, M. F., Mizell, G., Giordmaine, J. A., Chen, Z., Anastassiou, C., Martin, J., & Segev, M. (1999). Second-harmonic generation in waveguides induced by photorefractive spatial solitons. Optics letters, 24(16), 1145-7. https://doi.org/10.1364/ol.24.001145
Lan, S, et al. "Second-harmonic generation in waveguides induced by photorefractive spatial solitons." Optics letters vol. 24,16 (1999): 1145-7. doi: https://doi.org/10.1364/ol.24.001145
Lan S, Shih MF, Mizell G, Giordmaine JA, Chen Z, Anastassiou C, Martin J, Segev M. Second-harmonic generation in waveguides induced by photorefractive spatial solitons. Opt Lett. 1999 Aug 15;24(16):1145-7. doi: 10.1364/ol.24.001145. PMID: 18073967.
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Empirical measure of multiclass generalization performance: the K-winner machine case.

IEEE transactions on neural networks

Ridella S, Zunino R.
PMID: 18249984
IEEE Trans Neural Netw. 2001;12(6):1525-9. doi: 10.1109/72.963791.

Combining the K-winner machine (KWM) model with empirical measurements of a classifier's Vapnik-Chervonenkis (VC)-dimension gives two major results. First, analytical derivations refine the theory that characterizes the generalization performances of binary classifiers. Second, a straightforward extension of the theoretical...

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Ridella S, Zunino R. Empirical measure of multiclass generalization performance: the K-winner machine case. IEEE Trans Neural Netw. 2001;12(6):1525-9doi: 10.1109/72.963791.
Ridella, S., & Zunino, R. (2001). Empirical measure of multiclass generalization performance: the K-winner machine case. IEEE transactions on neural networks, 12(6), 1525-9. https://doi.org/10.1109/72.963791
Ridella, S, and Zunino, R. "Empirical measure of multiclass generalization performance: the K-winner machine case." IEEE transactions on neural networks vol. 12,6 (2001): 1525-9. doi: https://doi.org/10.1109/72.963791
Ridella S, Zunino R. Empirical measure of multiclass generalization performance: the K-winner machine case. IEEE Trans Neural Netw. 2001;12(6):1525-9. doi: 10.1109/72.963791. PMID: 18249984.
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Digital implementation of hierarchical vector quantization.

IEEE transactions on neural networks

Bracco M, Ridella S, Zunino R.
PMID: 18244561
IEEE Trans Neural Netw. 2003;14(5):1072-84. doi: 10.1109/TNN.2003.816355.

A formal methodology drives the design and realization of a digital very large-scale integration (VLSI) device supporting hierarchical vector quantization (HVQ) in computation-intensive coding applications. The hardware-oriented model-selection approach enhances the Minimum Description Length criterion with circuit-related aspects that...

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Bracco M, Ridella S, Zunino R. Digital implementation of hierarchical vector quantization. IEEE Trans Neural Netw. 2003;14(5):1072-84doi: 10.1109/TNN.2003.816355.
Bracco, M., Ridella, S., & Zunino, R. (2003). Digital implementation of hierarchical vector quantization. IEEE transactions on neural networks, 14(5), 1072-84. https://doi.org/10.1109/TNN.2003.816355
Bracco, M, et al. "Digital implementation of hierarchical vector quantization." IEEE transactions on neural networks vol. 14,5 (2003): 1072-84. doi: https://doi.org/10.1109/TNN.2003.816355
Bracco M, Ridella S, Zunino R. Digital implementation of hierarchical vector quantization. IEEE Trans Neural Netw. 2003;14(5):1072-84. doi: 10.1109/TNN.2003.816355. PMID: 18244561.
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Special treatment during slaughtering in Finland of cattle carrying an excessive load of dung; Meat hygienic aspects.

Meat science

Ridell J, Korkeala H.
PMID: 22061033
Meat Sci. 1993;35(2):223-8. doi: 10.1016/0309-1740(93)90052-J.

The aim of the study was to evaluate the microbiological consequences of the Finnish special hide regulations. These were agreed upon, by a committee including members representing meat production, industry and the state, to reduce the number of cattle...

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Ridell J, Korkeala H. Special treatment during slaughtering in Finland of cattle carrying an excessive load of dung; Meat hygienic aspects. Meat Sci. 1993;35(2):223-8doi: 10.1016/0309-1740(93)90052-J.
Ridell, J., & Korkeala, H. (1993). Special treatment during slaughtering in Finland of cattle carrying an excessive load of dung; Meat hygienic aspects. Meat science, 35(2), 223-8. https://doi.org/10.1016/0309-1740(93)90052-J
Ridell, J, and Korkeala, H. "Special treatment during slaughtering in Finland of cattle carrying an excessive load of dung; Meat hygienic aspects." Meat science vol. 35,2 (1993): 223-8. doi: https://doi.org/10.1016/0309-1740(93)90052-J
Ridell J, Korkeala H. Special treatment during slaughtering in Finland of cattle carrying an excessive load of dung; Meat hygienic aspects. Meat Sci. 1993;35(2):223-8. doi: 10.1016/0309-1740(93)90052-J. PMID: 22061033.
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Showing 1 to 12 of 163 entries