Zobrazeno 1 - 10
of 109
pro vyhledávání: '"Richard E. Neapolitan"'
Publikováno v:
BMC Bioinformatics, Vol 21, Iss 1, Pp 1-17 (2020)
Abstract Background Even though we have established a few risk factors for metastatic breast cancer (MBC) through epidemiologic studies, these risk factors have not proven to be effective in predicting an individual’s risk of developing metastasis.
Externí odkaz:
https://doaj.org/article/9ff744eb5f3d49eca879e78e082e1bd8
Autor:
Richard E. Neapolitan, Xia Jiang
Publikováno v:
Entropy, Vol 16, Iss 7, Pp 4004-4014 (2014)
The Principle of Maximum Entropy is often used to update probabilities due to evidence instead of performing Bayesian updating using Bayes’ Theorem, and its use often has efficacious results. However, in some circumstances the results seem unaccept
Externí odkaz:
https://doaj.org/article/8f750b698554402baf9bb42bf1b92053
Autor:
Richard E. Neapolitan, Xia Jiang
Probabilistic Methods for Financial and Marketing Informatics aims to provide students with insights and a guide explaining how to apply probabilistic reasoning to business problems. Rather than dwelling on rigor, algorithms, and proofs of theorems,
Publikováno v:
BMC Bioinformatics, Vol 21, Iss 1, Pp 1-17 (2020)
BMC Bioinformatics
BMC Bioinformatics
Background Even though we have established a few risk factors for metastatic breast cancer (MBC) through epidemiologic studies, these risk factors have not proven to be effective in predicting an individual’s risk of developing metastasis. Therefor
Publikováno v:
International Journal of Testing. 20:146-168
The standard error (SE) stopping rule, which terminates a computer adaptive test (CAT) when the SE is less than a threshold, is effective when there are informative questions for all trait levels. However, in domains such as patient reported outcomes
Publikováno v:
Int J Test
The standard error (SE) stopping rule, which terminates a computer adaptive test (CAT) when the SE is less than a threshold, is effective when there are informative questions for all trait levels. However, in domains such as patient reported outcomes
Autor:
Xia Jiang, Richard E Neapolitan
Publikováno v:
PLoS ONE, Vol 7, Iss 10, p e46771 (2012)
BackgroundThe interaction between loci to affect phenotype is called epistasis. It is strict epistasis if no proper subset of the interacting loci exhibits a marginal effect. For many diseases, it is likely that unknown epistatic interactions affect
Externí odkaz:
https://doaj.org/article/e585593f398545f6863c98425f5dd319
Publikováno v:
Journal of the American Medical Informatics Association. 24:897-902
Objective: The Patient Reported Outcomes Measurement Information System (PROMIS) initiative developed an array of patient reported outcome (PRO) measures. To reduce the number of questions administered, PROMIS utilizes unidimensional item response th
Autor:
Xia Jiang, Yuan Luo, Xiaoyu Li, Richard E. Neapolitan, Susan E. Clare, Ankita Roy, Sasa Espino, Zexian Zeng, Seema A. Khan
Publikováno v:
BMC Bioinformatics
BMC Bioinformatics, Vol 19, Iss S17, Pp 65-74 (2018)
BMC Bioinformatics, Vol 19, Iss S17, Pp 65-74 (2018)
Background Identifying local recurrences in breast cancer from patient data sets is important for clinical research and practice. Developing a model using natural language processing and machine learning to identify local recurrences in breast cancer
Autor:
Richard E. Neapolitan, Kwang Hee Nam
Publikováno v:
AC Motor Control and Electrical Vehicle Applications ISBN: 9781315200149
AC Motor Control and Electrical Vehicle Applications
AC Motor Control and Electrical Vehicle Applications
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f3bbb167d27b70291ce82fc9d101d4e7
https://doi.org/10.1201/9781315200149-7
https://doi.org/10.1201/9781315200149-7