Zobrazeno 1 - 10
of 228
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:
Jones, P. W.
Publikováno v:
Technometrics, 1992 Feb 01. 34(1), 99-100.
Externí odkaz:
https://www.jstor.org/stable/1269559
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,
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
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::40a4615bcbb098569e3b63094c7695dd
http://link.springer.com/article/10.1186/s12859-020-03638-8
http://link.springer.com/article/10.1186/s12859-020-03638-8
Autor:
Richard E Neapolitan, Xia Jiang
Publikováno v:
PLoS ONE, Vol 10, Iss 2, p e0117658 (2015)
Studies show that thousands of genes are associated with prognosis of breast cancer. Towards utilizing available genetic data, efforts have been made to predict outcomes using gene expression data, and a number of commercial products have been develo
Externí odkaz:
https://doaj.org/article/1c2aae835a2240f5b7c803245a74a3dc
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ff1910cdb2fdda6c95e73ac2f6d04e2c
https://doi.org/10.1080/15305058.2019.1635604
https://doi.org/10.1080/15305058.2019.1635604
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::d24ab9728e413f604b338694b1a1ba8f
https://pubmed.ncbi.nlm.nih.gov/32982603
https://pubmed.ncbi.nlm.nih.gov/32982603
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::de9786bcbad0d8f2d72fb3c82c08ad53
https://doi.org/10.1093/jamia/ocx003
https://doi.org/10.1093/jamia/ocx003